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Previous Webinar Agenda

Name: Karanpreet Singh

Designation: AGM, Paytm; Conversational AI Program Manager, ex-Google

Title of the talk: Generative AI powered Customer Experience

Biography: Karan has around 10 years of work experience in program management, especially for emerging technologies like Conversational AI & NLP. He is currently working as AGM, program management at Paytm and has worked previously as Program Manager for Conversational AI program at Google India and USA. He has completed his graduation in technology from IIT Ropar, and likes working in the intersection of engineering, products, business and emerging technologies. Customer Experience as a function and Ed-tech, Fin-tech & AI as domains are closer to his heart.


Abstract: Customer experience, largely a function of how organizations converse with their customers during sales as well as post-sales lifecycle, has been evolving continuosly with automation in the last decade. Conversational AI technology, mainly chatbots, voice call-bots and voice assistants, have powered the customer experience over the last few years. These bots uses NLP (Natural Language Processing), ML & AI models to automate specific use-cases like lead generation chatbots for sales, smart-journeys for customer support and voice bots self-servicing customers to some extent.

Now can you imagine what the customer experience of the future, powered by genAI and platforms like ChatGPT and Bard, is going to look like? Generative AI technology will bring significant disruption to the customer experience we provide today. The future of customer experience is so exciting – where the user journey and conversations are going to be personalized with conversational and generative bots – contextually trained based on data like your specific info, demographics obtained from CRM platforms.

Enterprise Conversational AI platforms are evolving very quickly to launch the re-imagined customer experience products with ever-changing Conversational & Generative AI capabilities. And so eager the organisations are, who don’t want to miss the train of transforming the experience for their customers in the genAI era.

Join me during my session at World Data Congress to learn in-depth about the next level evolution in customer experience driven by Generative AI.

Name: Surabhi Sinha

Designation: Adobe, California, USA

Title of the talk: Efficient Generative AI – Unlocking the true potential of Gen AI

Biography: Surabhi is an ML engineer at Adobe with ~5 years of industry experience in the domain of Machine Learning and Big Data. She has filed patents in the domain of efficient generative AI and has been involved in research in the domain of AI in healthcare under Professor Paul Thompson at USC. Additionally, she has been a part of the jury at hackathons and major tech awards and is a member of technical program committees at various ML conferences. Her work has received multiple recognitions and she was invited to be a part of industry expert circles such as Criya. 

Email: surabhi413@gmail.com

Abstract: Chat GPT and generative AI have captivated the tech landscape in recent months. Every day, we are inundated with new applications and products based on them, unraveling massive economic opportunities and empowering more individuals with the power of AI. However, one major challenge of these models is their enormous size and sometimes high latency or time taken to generate outputs. Researchers are currently concentrating their efforts on making these models smaller and more efficient for them to be easily applicable to end products. It will enable a faster time-to-market, by reducing the latency of generative AI models, businesses can develop and deploy new products and services faster, leading to a competitive advantage over their peers. Additionally, smaller models mean reduced costs of hardware and infrastructure needed to support them, resulting in significant cost savings for businesses. It is also critical for businesses to focus on enhancing customer experience, and efficient models may lead to faster and improved responses resulting in a better customer experience. As models become more complex, they require a larger amount of computing power and data to train effectively. Smaller and more efficient generative AI models can be more easily scaled up or down, making it easier for businesses to adapt to changes in demand.

Finally, with all these groundbreaking advancements, it’s important to make generative AI efficient to reduce energy consumption and carbon emissions, for a positive impact on the environment.

Overall, just generative AI is not sufficient, efficient generative AI is the key to success.

Name: Bhushan Desam, Ph.D.

Designation: Chief Business Development Officer Add Value Machine, Inc. Austin, TX, USA

Title of the talk: Unlocking Business Value in Enterprises with Generative AI

Biography: Bhushan Desam is the co-founder and Chief Business Development Officer at Add Value Machine, Inc., an enterprise Generative AI company based out of Austin, Texas. Before his current role, he led machine learning business development at Amazon Web Services in the US and APJ region, helping customers develop and deploy ML at scale including LLMs. Prior to that, he was the global director of AI business at Lenovo Data Center group and brought multiple award-winning AI hardware and software products to market. He also led business development at NVIDIA during the period of its transformation as an AI company. Bhushan has a Ph.D. in mechanical engineering from the University of Utah and a management degree from MIT Sloan School of Management. He consistently contributes to the industry as a frequent publisher of thought leadership articles and as a keynote speaker, sharing his insights and expertise.

Email: bhushan@addvaluemachine.com

Abstract: Generative AI, enabled by tools like ChatGPT, is revolutionizing the way we create content, using machine learning techniques to generate text, music, images, and more. According to Goldman Sachs estimates, it is projected to contribute to a $7 trillion increase in global GDP (nearly 7%) and enhance productivity by 1.5% over the next decade. Leading enterprises, such as Morgan Stanley, Morningstar, and Goldman Sachs, have already embraced this technology to improve employee productivity. A recent survey conducted by Salesforce Inc. involving over 500 IT executives revealed that 67% of enterprises have identified Generative AI as a top priority for their business within the next 18 months. Despite the anticipation and potential opportunities, enterprises are encountering various challenges that necessitate them to either restrict or ban the usage of Generative AI tools (Samsung, J.P. Morgan, Amazon are some examples). Unlike for individual productivity or creative endeavors, adopting this technology within a business setting demands a strategic approach to maximize its impact. This presentation will examine three crucial challenges that enterprises must tackle in order to unlock the full potential of Generative AI within an enterprise context. These challenges include ensuring compliance with enterprise security standards, contextualizing Generative AI for specific use cases by combining foundational models with proprietary data, and customizing Generative AI to meet internal needs and integrate with existing systems. By effectively addressing these challenges, enterprises can fully harness the potential of Generative AI, resulting in improved efficiency and growth.

Name: Gourisha Sethi

Designation: Deep Armor Technologies, India

Title of the talk: Exploitation and automated detection of threats to modern cloud  infrastructure 

Biography: Gourisha is a Security Analyst at Deep Armor. She specialises in product penetration testing, software hardening and DevSecOps. She provides analysis, implementation, and support for clients to improve their security posture and consultation along with training services to multinational corporations to mitigate risks. As a result of her work, overall vulnerability production has dropped by 65.4%, false-positive noise by 92.1%. She holds a Bachelor of Engineering in Computer Science from BITS Pilani Dubai Campus and has graduated as the President of their Literary club. Gourisha is a member of IEEE, SANS and WiCyS and has been a recipient of WiCyS BlackHat Europe 2022 scholarship.

Abstract: Cloud infrastructure security is an oft-neglected topic when businesses invest in securing their web apps. Securing web applications deployed on modern cloud platforms (such as AWS, GCP, Azure, etc.) is challenging. It should involve securing Console/portal/web pages, APIs and 3rd party integrations and Cloud infrastructure. While security assessments and penetration tests may help discover and remediate vulnerabilities, ensuring that a once-secured cloud environment remains secure is a harder problem to solve. Cloud configurations are dynamic and change constantly. New feature deployments, code fixes, updates, and network changes introduce new vulnerabilities. It’s imperative that such environments are monitored frequently for vulnerabilities and misconfigurations. This presentation, demonstrates the attacks against cloud environments & automated detection of such threats. Due to increased threats associated with misconfigured cloud environments, standards have evolved for validating common cloud services such as IAM, Logging & Monitoring, Databases, etc. This talk dives into the cloud security standards published by the Centre for Internet Security (CIS) – how they can benefit your cloud deployments, and more importantly – where they fall short. Additional capabilities and security checks that should be included in future revisions of the standard are proposed. Lastly, demonstration will provide a proof-of-concept solution that can be used for automated scanning of any AWS environment, without having to disclose any business or user data to the scanner tool. Deep Armor’s tool will perform reconnaissance and security scanning on a host of services and resources and present an easy-to-read dashboard, all while compliant with the CIS benchmarks.

Name: Jessica Tucker

Designation: JTucker Consulting, IL USA

Title of the talk: Artificial Intelligence and Artificial Intelligence Ethics

Biography: Jessica Tucker Software Engineer, STEM Champion, renowned international speaker, and founder of JTucker Consulting. With 7+ years in corporate spaces Jessica brings fresh and new ideas on how to improve tech companies’ business practices, technology strategies and DEI implementation. As a software developer Jessica is up to date with emerging technologies. Engineering principles etc.

Abstract: Artificial intelligence is one of several hot technologies that have the potential to transform the face of history and our everyday lives. AI has become one of the most popular and fast-growing technologies in the world, but the explanation of AI is still complex and not easily understood. The public doesn’t understand AI, but they know the bias’, discrimination, and untrustworthiness around AI technology. It is our job to educate the public about where technology is moving and regulate the power of AI and be careful not to remove the human aspect from technology.I have studied AI ethics and public trust and look forward to sharing my knowledge and ideas around the topic. Our world is in the “Tech Era”, as technologists we must understand where we are headed and why in order to create technology that is morally sound and technologically advanced.

Shiksha Gallow

Designation: Holistic Integrative healing Institute, South Africa.

Title of the talk: The largest technological device on the planet remains a mystery. A deep dive into the brain and neuroscience techniques to empower yourself.

Biography: Dr Shiksha Gallow is global multi award winner in the healthcare field. In 2022 she was named “Africas leading medical personality of the year”. She is a Holistic Integrative Medical Practioner, Medical Scientists in Clinical Pathology, Neuroscientsist and Medical Researcher. She started her own research company Cannabis Research Council as well as her medical company Holistic here Integrative Healing Institute a few years ago and has had many successes in treating patients with various ailments such as Cancer and Auto immune disease. She serves on the board of the Society of CAnnabsi Clinicans in the US, and on the EXCO of BRICS healthcare chapter. She has vast academic qualifications including 3 masters’ degrees: Masters in Medicine in Public Health and Medical Science, MBA and 2 PHDs. Dr Gallow is completing her third PHD, in Medical Science and is investigating cannabis as a treatment for prostate cancer. Dr Gallow is heading up Global Clinical trials for cannabinoids and a range of Ethno medicines to treat various ailments. Dr Gallow has published 3 academic books in Medicine and business as well as many reputable journals. Her fourth book is an anthology of stories called “African women who inspires” This is a global book which empowers and inspires women, as she narrates her story of successes and failures. She is now completing her 5th book called: “The Cure: A holistic approach to healing” which offers patients guidance on how to manage and treat their various medical conditions, using medical cannabis, natural medicines as well as Neuroscience techniques.

Abstract: The brain remains one of the biggest mysteries on earth. As neuroscientist we study the mind and how the different parts of the brain function and can be used to heal patients. The perfect example is the “Placebo effect” Even though placebos contain no real treatment, researchers have found they can have a variety of both physical and psychological effects. Participants in placebo groups have displayed changes in heart rate, blood pressure, anxiety levels, pain perception, fatigue, and even brain activity. Your mind can be a powerful healing tool when given the chance. The idea that your brain can convince your body a fake treatment is the real thing — the so-called placebo effect — and thus stimulate healing has been around for millennia. Neuroscientists have been studying this phenomena for years, and the results are simply short of amazing. The presenter will discuss Neuroplasticity, the placebo effect and the Hebbs law and how we can use these to heal ourselves as well as manifest the life that we want. Technology has advanced allowing clinical trials to be conducted showing the power of the mind. When a “virus: or negative thought pattern enters the mind, what “ant-viral” effects can we use to change this. The time of people to be enlightened is now, we are facing a global pandemic relating to depression, anxiety and a high amount of people committing suicide, the only technology that can fix that is the mind and our brain. This session will provide you with tools to change your life and empower yourself.

Name: Virginia Mijes Martin

Designation: Founder Innovation Enterprise Advocate at European Technology Chamber

Title of the talk: Technologies at the heart of competitive, scalable and sustainable businesses 

Biography: Virginia Mijes is a 25+ year veteran in the technology sector with extensive international experience. A leader in the Blockchain and Crypto industry, she is a firm believer in technology as an economic and social game changer with global impact. Has extensive networking worldwide in the industry and works on application design as well as Fintech platforms with teams in EMEA, APAC, UAE. Technology evangelist, trainer, and international speaker, she pays special attention to empowering education, research and entrepreneurship giving visibility to projects in the industry. She also collaborates with different initiatives in other emerging technologies. Belongs to different groups of women in technology globally. Executive MBA by Eada Business School- LeaderTech- International Speaker – Senior Consultant-Trainer-Entrepreneur- Research & Writer Tech. Executive Member at Associations TIC – Organizational Behavor Virginia is recognized and awarded among other prizes such as  TOP 100 Women in Social Enterprise 2023, Global Leadership Women in Network 2021, Women Who Break the Bias List 202 Issued by 130 Women Who Break the Bias List 2022 · Apr 2022, TOP 10 Thought Leader- Digital Disruption, Advocate at European Technology Chamber

Abstract: Technology contributes to the growth of business environments, corporations, governments, institutions as well as society in general. We live in a highly innovative technological moment following the development mainly in the transition to Industry 4.0. Emerging technologies, together with the knowledge of more mature technologies are the point of innovation for business being today a global need to be integrating trends as well as knowledge, not only in the tools themselves but in the talent of technological culture.The ability to grow, scalability, cost savings, time make companies more competitive, especially in a future oriented economy and digital ecosystems. In the challenges of business for its sustainability, competitive positioning and its own survival are key to know how technologies are advancing, increasingly transverse and implement them in its value chain. Technologies such as Blockchain, AI, IoT, Robotics … boost business in a global marketplace where companies and corporations are adapting quickly in an increasingly complex and fast-paced tech environment.Technological development is going through a historic moment, joining the knowledge of previous decades and placing a highly qualified panorama with options and opportunities to develop high impact projects in markets and industries.

Name: Jackie Carter

University of Manchester, United Kingdom

Title of the talk: Developing a future pipeline of applied social researchers through experiential learning: The case of a data fellows programme 

Biography: Jackie Carter a professor of statistical literacy at The University of Manchester. In 2020 she achieved a Women in Data industry award and a National Teaching Fellowship. Jackie works to connect education and skills to workplace needs.  Her 2021 book “Work placements, internships and applied social research” covers the theory and practice of learning by doing. She is an elected member of the International Statistical Institute, a Fellow of the Academy of Social Sciences, and a member of the Economic and Social Research Council’s (ESRC) Strategic Advisory Council and a member of ESRC’s CLOSER Expert Group.

Abstract: This paper presents an innovative model for developing data and statistical literacy in the undergraduate population through an experiential learning model developed in the UK. The national Q-Step (Quantitative Step change) programme (2013–2021) aimed to (i) create a step change in teaching undergraduate social science students quantitative research skills, and (ii) develop a talent pipeline for future careers in applied social research. We focus on a model developed at the University of Manchester, which has created paid work placement projects in industry, for students to practise their data and statistical skills in the workplace. We call these students data fellows.Our findings have informed the development of the undergraduate curriculum and enabled reflection on the skills and software that we teach. Data fellows are graduating into careers in fields that would previously have been difficult to enter without a STEM (Science, Technology, Engineering and Mathematics) degree. 70% of data fellows to date are female, with 25% from disadvantaged backgrounds or under-represented groups. Hence the programme also addresses equality and diversity.The paper documents some of the successes and challenges of the programme and shares insight into non-STEM pipelines into social research careers that require data and statistical literacy, A major advantage of our approach is the development of hybrid data analysts, who are able to bring social science subject expertise to their research as well as data and statistical skills.Focusing on the value of experiential learning to develop quantitative research skills in professional environments, we provoke a discussion about how this activity could not only be sustained but also scaled up. subsections.

Name: Moshood

Founder and Lightning, UK

Title of the talk: Critical Evaluation of The Future Role of Ai in Business and Society

Biography: Moshood has two Msc degrees, with his most recent in Applied Artificial Intelligence and Data Analytics, at the University of Bradford. He is a passionate, reliable data scientist and machine learning engineer with multiple years of experience, wholly dedicated to creative problem-solving approaches to tackling challenges, with broad experience in consulting, investment, finance, energy and retail. Expertise is placed within machine learning and data science modelling, market analysis, forecasting, making informed decisions, business intelligence, business process optimisation, revenue assurance, performance analysis and customer need assessments. He is an avid community builder with research interests in responsible AI and data governance, as well as the application of AI in the energy, finance and healthcare sector, with huge rave acclaims.

Abstract: In contemporary economies, artificial intelligence (AI) and machine learning (ML) algorithms are frequently utilised in generating judgments that have far-reaching consequences for employment, education, access to finance, and a variety of other fields. The increasing level of advancements in artificial intelligence (AI) has substantially affected the functionality of societies and economies, prompting extensive debate over the merits and demerits of AI on the society and humanity at large. This research critically explored the benefits and demerits of artificial intelligence, in view of its impact on people, businesses, economies and the society, from an ethical, legal and governance point of view. However, while it is imperative that public welfare is religiously promoted and guarded, it is equally necessary to consider the interest and success of AI developer and their organisations. Therefore, it is essential to maintain an optimum balance between ethical principles. Our findings shows that experts are proposing an era of AI ethics that focuses on utilitarianism, which presents a balance between risks and benefits, and a movement from fundamental duty of care to civil responsibility for public good. National and continental associations have reacted promptly by establishing various regulations for the conduct of AI implementation in their jurisdictions. The General Data Protection Regulation (GDPR) for example, permits individuals to provide general consent in relation to their information. The continuous investment and research focus on further development of artificial intelligence, shows that the future of individual lives, businesses and economies will continuously be influenced by numerous everyday artificial intelligence functions.

Name: Marina Sol

Designation: Diagnio, UAE

Title of the talk: Women’s empowerment in reproductive health: early at-home diagnostics, education, & digital health

Biography: Marina Sol is the CEO and Founder of Diagnio, rapid at-home hormonal and fertility diagnostics for women. Marina comes from a family of OBGYN doctor and has learned and seen much about the industry from a very young age. She was one of the first IVF babies in her country and now, being a grown woman, went through IVF treatment herself. She chose the way of technology to battle infertility and now has more than 20 years of experience in the MedTech industry and has sold her previous MedTech startup to a pharma corporation.

Abstract: 30M women globally struggle to get pregnant every year. From an official health system standpoint – infertility is not even considered a disease until 1 or 2 years of unsuccessful trials. It then takes, on average, 4 IVF cycles to reach just a 45% success rate, which would cost roughly $120,000 for a family to get to that stage. Simply put: Women do not have the diagnostics they deserve. The only solution is – earlier screening at higher fidelity.Innovative technologies in diagnostics and AI in reproductive health can provide valuable insights into a woman’s overall health and fertility and enable women to monitor their reproductive health and detect potential issues early on. At-home diagnostics also plays a critical role in empowering women to take a proactive approach to their health. It gives the solution for women who want to save time and money on lab appointments for simple testing to get done, want a more private and comfortable approach to their reproductive healthcare, or may not have easy access to the traditional healthcare system.In addition to AI and at-home diagnostics, education is critical to reproductive health empowerment. Women should have access to comprehensive and accurate information about their bodies and reproductive health, which can help them make informed decisions about their health and well-being. Digital health solutions and online resources can be powerful tools for delivering this information in a way that is accessible and user-friendly.

Name: Saleh A.S. AlAbdulhadi

Designation: Prince Sattam bin Abdulaziz University, KSA

Title of the talk: Artificial intelligence in medical genetic diagnostics and medical genetic laboratory training

Biography: Saleh Al Abdulahdi has completed his PhD at the age of 28 years from UK, University of Aberdeen and postdoctoral studies from Aberdeen Children Hospital, Scotland, UK. He is Assistant Professor & Consultant, Medical Molecular Genetic, Founder and Chairman of Medical Molecular Genetic Unit, Applied Medical Science College, and Founder and chairman of Dr. Saleh office for Medical Genetics and Genetic Consultation (house of expertise). He has published more than 25 papers in reputed journals and has been serving as an editorial board member of repute.

Abstract: Artificial intelligence (AI) is the science and engineering of making intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. Deep learning is part of this evolution technology impower products and services that users are unaware of the complex data processing that is taking place in healthcare services. in medical molecular genomics diagnosis, a specific type of AI algorithm known as deep learning and the graphics processing units (GPUs) is used to process variant types and complex genetic databases. In this study, we examine different classes of problems that AI systems to solve and describe the clinical genetic diagnostic cases that benefit from these solutions for patient care and medical laboratory education and training in our medical genetic unite, here in Saudi Arabia. This includes emerging methods for tasks in genetic counselling, pedigree evaluation, gene to gene interaction, haplotyping and phenotype-to-genotype correlation. We found out that current modern DNA sequencing technology allows for the generation of genomic data uniformly and at scale, but integrating the phenotype data requires extension of work multi data collection modes, this tend to be slow, expensive, and loss of information. AI technology is an essential for improving the quality assurance in the field of clinical genomic diagnosis.

Name: Francisco Garcia

Designation: Founder Direcly, United States

Biography: Francisco is the founder of Direcly, a Google Cloud, Google Marketing Platform, and Adobe Analytics partner company. He has a background in marketing and is a certified data engineer, having previously worked at top ad agencies before transitioning to the tech industry. Francisco has received recognition from Google as a Champion Innovator in Data Analytics, and is actively involved in the community. He advises entrepreneurs through Google for Startups, leads the Google Developer Groups Cloud Miami, and conducts analytics and marketing seminars at universities.

Title of the talk: Using Data to Persuade and Influence

Abstract: With the vast amount of data available to us today, it can be overwhelming to try and process and make sense of it all. Our brains were not designed to handle this volume of information, and it can be difficult to cut through the noise and make informed decisions. This session aims to help attendees navigate these challenges and use data as a powerful tool for persuasion and influence.leveraging concepts from cognitive psychology, this session aims to help attendees understand the psychological principles behind effective data storytelling. By understanding how the brain processes and retains information, attendees will learn how to craft a narrative that is more engaging and persuasive. The session will also cover the use of visualizations to help illustrate data and make it more accessible to the audience, as well as strategies for building trust and overcoming objections. By the end of the session attendees will have a deep understanding of how to use data to persuade and influence others in a way that is both effective and practical.

Name: Patrick Henz

Designation: Primetals Technologies – a Mitsubishi Heavy Industries entity, United States

Title of the talk: From Avatars to Virtual Beings

Biography: Patrick Henz is a Compliance Officer with over a decade of experience in the field. He started his career in 2007 at the Corporate Information Office and Compliance at Siemens, where he implemented the company’s Anti-Corruption program in Mexico and other Latin American countries. He is Head of Governance, Risk & Compliance at a leading engineering and plan construction company, based in Atlanta. He is a frequent speaker at university workshops and conferences, and also wrote the book “Into the Metaverse”, published in 2023.

Abstract: This is a discussion of the history and evolution of the term “avatar” and its usage in technology. The origins of the word come from Hinduism and was later used by science fiction author Philip K. Dick in his work “The Exegesis of Philip K. Dick,” where he posits that humans are avatars of God with amnesia. The modern usage of the term as a graphical representation of a user in technology was popularized by game designer Richard Garriott in the 1980s with his role-playing game series Ultima. The discussion also explores the potential for avatars to be combined with Artificial Intelligence to create “Virtual Beings” that can act autonomously within virtual platforms, and the use of avatars in social media and meeting platforms. It also mentions that the more information the platform has about the user, the more realistic the avatar can act autonomously, and the existence of a “Personal Digital Twin” in the cloud that can be used to continue the activity of the avatar even when the user is disconnected.

Name: Murad M. Badarna

Designation: Yezreel Valley Academic College, Israel

Biography: Murad M. Badarna received his B.Sc. were in information systems from the University of Haifa. His M.Sc. in computer science from the University of Haifa and his Ph.D. in machine learning from the University of Haifa. Murad joined the department of Information Systems in both the University of Haifa and the Max Stern Yezreel Valley College. Murad Badarna’s main research interests are in the fields of machine learning especially selective sampling, active learning, and deep learning. Murad is also active in the high-tech industry field, He is the head of Research and Development department of the xBiDa company which provided combination of advanced video analytics technology and data science services.

Title of the talk: Unsupervised Methods to Deal with Unsupervised Mixed Data

Abstract: Background and goals: Clustering is an artificial intelligence technique that partitions objects into sub-groups. In clustering the goal is to group similar objects together and different objects into different groups. K-means is one of the well-known clustering algorithms and most popular. It works by assigning each point ( i.e. object) to the closest center and then update the centers based on those points. However, clustering data with mixed types (i.e., attributed with numerical and categorical types) is still a challenging open problem. In this study, we proposed a new k-means clustering algorithms for mixed datasets. Research method: Running K-means clustering algorithm requires a distance function in order to associate each point to the closest center, and mean formula in order to update the centers. Let {att_1, att_2…, att_N } assign the attributes, and let R_att={att_1,…,att_l },and C_att={att_(l+1),…,att_N} contains the numerical and categorical attributes, respectively. Then, the distance between two points X={x_1,x_2,…,x_N },Y={y_1,y_2,…,y_N } will be: dist(X,Y)=∑_(i=1)^l▒(x_i-y_i )^2 +∑_(i=l+1)^N▒〖¬(x_i=y_i ) 〗 Were, ¬(x_i=y_i )={█(1,if x_i≠y_i@0,if x_i=y_i )┤ Using this distance, we built a distance matrix that include all the distances between the points. Then we use the multi-dimensional-scaling technique in order to represent the objects in a continues form. As a result, the new space will include only continues attributes that reflects the actual similarity between the objects as in the original form. Then we run the original k-means clustering algorithm on the new space dataset.

Name: Loai Abdallah

Designation: Founder & CEO, Israel

Title of the talk: Unsupervised Methods to Deal with Unsupervised Mixed Data

Biography: Loai Abdallah is Working with a group of incredibly bright people who are obsessed with using innovative technological solutions to solve business challenges faced by other incredibly bright people. Analytics, Data, Adtech, and Marketing professional. Recognized as a Champion in Data Analytics by the Google Cloud Innovators program.Skilled in Google Cloud Platform, Google Marketing Platform, Google Analytics 4, data storytelling, business intelligence, innovative problem solving using the latest technology, product planning for design and road-mapping, team leadership, data engineering and cross-departmental work.

Abstract: Background and goals: Clustering is an artificial intelligence technique that partitions objects into sub-groups. In clustering the goal is to group similar objects together and different objects into different groups. K-means is one of the well-known clustering algorithms and most popular. It works by assigning each point ( i.e. object) to the closest centre and then update the centres based on those points. However, clustering data with mixed types (i.e., attributed with numerical and categorical types) is still a challenging open problem. In this study, we proposed a new k-means clustering algorithms for mixed datasets. Research method: Running K-means clustering algorithm requires a distance function in order to associate each point to the closest center, and mean formula in order to update the centres. Using this distance, we built a distance matrix that include all the distances between the points. Then we use the multi-dimensional-scaling technique in order to represent the objects in a continues form. As a result, the new space will include only continues attributes that reflects the actual similarity between the objects as in the original form. Then we run the original k-means clustering algorithm on the new space dataset.

Name: Gal Hever

Designation: Tel Aviv, Israel

Title of the talk:     WER We Are?

Biography: Francisco is the founder of Direcly, a Google Cloud, Google Marketing Platform, and Adobe Analytics partner company. He has a background in marketing and is a certified data engineer, having previously worked at top ad agencies before transitioning to the tech industry. Francisco has received recognition from Google as a Champion Innovator in Data Analytics, and is actively involved in the community. He advises entrepreneurs through Google for Startups, leads the Google Developer Groups Cloud Miami, and conducts analytics and marketing seminars at universities.

Abstract: Automatic speech recognition (ASR) is a rapidly evolving field that has made significant progress in recent years, but it still faces several challenges and difficulties. One major challenge is the variability of human speech, which can be affected by factors such as accent, background noise, and speaking style. Another challenge is the lack of large, high-quality annotated datasets, which are necessary for training and evaluating ASR systems. In addition, there are ongoing efforts to improve the performance of ASR systems on low-resource languages and underrepresented accents. Despite these challenges, there have been significant advances in ASR technology, including the development of deep learning models and the use of self-supervised learning techniques to improve performance on a wide range of tasks. In this talk, we will discuss the recent progress and ongoing challenges in ASR, as well as the potential future directions for the field.

Name: Dawei Wang

Designation: China University of Petroleum (East China), China States

Title of the talk: An improved deep learning model for oil spill detection by polarimetric features from SAR images

Biography: Dawei Wang has received the B.S.degree in electronic information science and technology from Qingdao Agricultural University, Qingdao, China, in 2017, the M.S. degree in Agricultural Information Technology from Qingdao Agricultural University, Qingdao, China, in 2020 and now is phD students in China University of Petroleum (Esat China). He research interests is SAR oil spill detection.

Abstract: Oil spill pollution at sea causes great damage to marine especially ecosystems environment. Quad-polarimetric Synthetic Aperture Radar (SAR) has become an important technology since it can provide polarization feature for marine oil spill detection. Oil spill detection can be achieved using deep learning models based on polarimetric features. However, insufficient feature extraction due to model depth, small reception field lend to loss of target information and fixed hyperparameter for models, effect of oil spill detection is still incomplete or misclassified. To solve the above problems, we propose an improved deep learning model named BO-DRNet. The model can obtain more sufficiently and fuller feature by ResNet-18 as backbone in encoder of DeepLabv3+ and Bayesian Optimization (BO) was used to optimize model’s hyperparameters. Experiments were conducted based on ten well-known polarimetric features were extracted from three quad-polarimetric SAR images obtained by RADASAT-2. Experimental results show that compared with other deep learning models, BO-DRNet perform best with mean accuracy of 74.70% and mean dice function of 0.8552. Current work in this paper provides a valuable tool to manage the upcoming disaster effectively.

Name: Lena Sasal Sorbonne

Designation: University, United Arab Emirates

Title of the talk: W-Transformer: A Wavelet-based Transformer Framework for Univariate Time Series Forecasting.

Biography: Léna Sasal is a phd Candidate from Sorbonne University. She is working in forecasting using Deep Learning techniques while applying it on oil and gas application with totalenergies in Abu Dhabi.

Abstract: Deep learning utilizing transformers has recently achieved a lot of success in many vital areas such as natural language processing, computer vision, anomaly detection, and recommendation systems, among many others. Among several merits of transformers, the ability to capture long-range temporal dependencies and interactions is desirable for time series forecasting, leading to its progress in various time series applications. In this paper, we build a transformer model for non-stationary time series. The problem is challenging yet crucially important. We present a novel framework for univariate time series representation learning based on the wavelet-based transformer encoder architecture and call it W-Transformer. The proposed W-Transformers utilize a maximal overlap discrete wavelet transformation (MODWT) to the time series data and build local transformers on the decomposed datasets to vividly capture the nonstationarity and long-range nonlinear dependencies in the time series. Evaluating our framework on several publicly available benchmark time series datasets from various domains and with diverse characteristics, we demonstrate that it performs, on average, significantly better than the baseline forecasters for short-term and long-term forecasting, even for datasets that consist of only a few hundred training samples.

Name: Gerry Wolff

Designation: CognitionResearch.org, UK

Biography: Gerard Wolff PhD CEng MIEEE is the Director of Cognition Research.org. He has held academic posts in the School of Computer Science and Electronic Engineering, Bangor University, the Department of Psychology, University of Dundee, and the University Hospital of Wales, Cardiff. He has held a Research Fellowship at IBM, Winchester, UK, and has been a Software Engineer with Praxis Systems plc. He received the Natural Sciences Tripos degree from Cambridge University, Cambridge, and the PhD degree from the University of Wales, Cardiff. He is also a Chartered Engineer and Member of the IEEE.


Abstract: The SP System, meaning the SP Theory of Intelligence and its realisation in the SP Computer Model, is the product of a lengthy programme of research, which now provides solutions or potential solutions to several problems in AI research. There is an extended overview of the SP System in ,and there is a much more comprehensive description in. This presentation is about how the SP System may prove useful in the development of intelligence in robots. A peer-reviewed, published, paper about this is in. The main theme of this presentation is generality, as described in the following subsections.

Generality needed for AI in robots: Where some degree of autonomy and intelligence are required in robots, it seems fair to say that capabilities that have been developed so far are quite narrowly specialised, such as vacuum cleaning an apartment or a house, navigating a factory floor, walking over rough ground, and so on. It seems fair to say that there is a pressing need to provide robots with human-like generality and adaptability in intelligence.

Generality in the development of the SP System: The overarching goal in the development of the SP System has been to search for a framework that would simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human learning, perception, and cognition. Despite the ambition of this goal, it seems that promising solutions have been found (next). There are of course reasons worry about the development of super-intelligence in robots, but that is outside the scope of this presentation.

Name: Shreyas Sundares

Designation: Course5 Intelligence, UAE

Biography: Professional with two decades into driving Hyper-growth & Strategic Transformation at Global Fortune Enterprises. Growth & Success Partner to 25+ organizations across industry, Paste your organization Logo here Awarded Data & Analytics leader for positively impacting Growth, Strategic Partnerships, Customer Experience, Risk Management, innovative Technological Advances, Operational innovation & efficiency & Culture Development. Directed multidisciplinary COE teamsthrough the build & Operationalization of Bespoke Solutions and Product Accelerators led by Technological Advances in Big Data Engineering, Cloud Platform Integration, Advanced Analytics & Insights, Artificial Intelligence, Intelligent Automation& Process Reengineering. Notable credentials in Business leadership from Stanford University and Business transformation from Northwestern University, USA


Abstract: Every organization and every business is today trying to create a unique and better experience for its customers. Everything from how we live to how we work to how we play is being monitored to analyse and arrive at offer something better the next time. This has not only led to enormous innovation but also continues to offer the best and consumers are at the receiving end of all the goodness. This also has created a very competitive world where each organization wants to better bigger and faster and be ahead in competition. With this, Data which is commons known as the new gold or oil or coal, is at the centre of all of this innovation, competitive landscape and enhanced customer experience. While every organization is trying and doing their bit in terms of taming the data and putting it into meaningful sense, Data Strategy & Governance emerges as a top priority for every organization and business. Having led Digital Transformation across several large entities and global fortune enterprises, the observation has been that there is no perfect recipe for Data and its success. However, how an organization is bringing in the data, how the data once brought in is being housed, safeguarded and processed, how the data is used for ambitious initiatives, monetization of the data and finally dissemination of data is an end to end life cycle that needs utmost care at each stage for an augmented impact. In my talk I would discuss the Data Strategy and Governance, its importance, some standards & best practices what some of the most successful organizations are doing in this field and key considerations for each entity.


Designation: Langtech, Poland

Biography: Andrew Ernest Ritz has Masters degrees in Ergonomics (London University) and Signal Processing and Machine intelligence (Surrey University). He has been working on Artificial Intelligence related problems since participating in the UK Alvey program in the 1980s. Recently, he is focusing on making the AI applications he has developed for teaching English, available on the web. These tools were created while working for his own company, Langtech, and funded in part by E NET Production, Katowice, Poland.


Abstract: The concept of Viewpoint Reasoning was proposed a number of years ago within the context of 3D Model Based Vision for representing viewpoint information about a scene and the objects therein. This concept is based on a representation that stores feature visibility in terms of 3D surfaces or solids that encapsulate individual objects or the whole scene, much in the same way as property spheres and the aspect graph. When the visibility of objects and their features are represented in this way, answers to questions about the joint visibility of features from viewpoints within a scene are at hand. With respect to computer graphics, viewpoint reasoning requires semantics to be routinely associated with 3D objects and the scenes they are placed in. Once this is done a large number of options become available for interacting with a scene and individual objects in a task-oriented way and not just in terms of geometry. Viewpoint Reasoning can be applied within the areas of Computer Graphics and Robotics to problems such as Good Viewpoint Selection, Sensor Placement, Motion Planning and Object Exploration. This talk describes a system, written in the programming language Python, which demonstrates how such tasks can be performed even when complex objects are involved


Designation: EMOJ, Italy

Biography: Luca Giraldi is CEO of EMOJ, offering advanced technologies based on Artificial Intelligence techniques to revolutionize the world of Customer Experience. Its motto is “we are an artificial intelligence company, but we put human at first before artificial”. EMOJ operates in the field of automotive, retail and culture and is considered by Unicredit Startlab and Bocconi among the 10 successful Italian startups. Luca received a PhD in Industrial Engineering in 2019 and he is expert of digital transformation, customer experience, emphatic marketing.


Abstract: Nowadays, driver monitoring is a topic of paramount importance, because distraction and inattention are a relevant safety concern crashes .Currently, Driver Monitoring Systems collect and process dynamic data from embedded sensors in the vehicle and RGB-D cameras detecting visual distraction and drowsiness, but neglect the driver’s emotional states, despite research demonstrated precisely that emotion and attention are linked, and both have an impact on performances For instance negative emotions can alter perception and decision-making

Consequently, explaining complicated phenomena such as the effects of emotions on driving and conceiving how to use emotions to decrease distraction need to be explored. Today several methods and technologies allow the recognition of human emotions, which differ in level of intrusiveness. Invasive instruments based on biofeedback sensors can affect the subjects’ behaviour and the experienced emotions. Non-intrusive emotion recognition systems, i.e., those based on speech recognition analysis and facial emotion analysis, implement Convolutional Neural Networks (CNN) for signal processing. However, no study has actually tested their effectiveness in a motor vehicle to enable emotion regulation. In this context the research focuses on the introduction of a multimedia sensing network and an affective intelligent interface able to monitor the emotional state and degree of driver’s attention by analysing the persons’ facial expressions and map the recognized emotions with the car interface in a responsive way to increase human wellbeing and safety. The adopted technology for emotion recognition is reported in and is extended with additional features specific for vehicle environment to implement emotion regulation strategies in the human-machine interface to improve driving safety. The result is an emotion-aware interface able to detect and monitor human emotions and to react in case of hazard, e.g. providing warning and proper stimuli for emotion regulation and even acting on the dynamics of the vehicle.

Name: Jemili Farah

Designation: University of Sousse, TUNISIA

Title of the talk: Deep Learning for Intrusion Detection

Biography: Farah JEMILI had the Engineer degree in Computer Science in 2002 and the Ph.D degree in 2010. She is currently Assistant Professor at Higher Institute of Computer Science and Telecom of Hammam Sousse (ISITCOM), University of Sousse, Tunisia. She is a senior Researcher at MARS Laboratory (ISITCOM –Tunisia). Her research interests include Artificial Intelligence, Cyber Security, Big Data Analysis, Cloud Computing and Distributed Systems. She served as reviewer for many international conferences and journals. She has many publications; 6 book chapters, 6 journal publications and more than 20 conference papers.

Abstract: In recent years, the world has seen a significant evolution in the different areas of connected technologies such as smart grids, the Internet of vehicles, long-term evolution, and 5G communication. By 2023, it is expected that the number of IP-connected devices will be three times larger than the global population, and the total number of DDoS attacks will double from 7.9 million in 2018 to 15.4 million by 2023 as reported by Cisco.As of 2020, the amount of data generated each day is exceeding petabytes and this includes the traces that internet users make when they access a website, mobile application or a network.

Name: Ghazal Azarfar

Designation: University of Saskatchewan, Canada

Biography: Data Scientist · Machine Learning Engineer · Applied Scientist · Associate Researcher · Computer Vision Engineer Title of the talk: Deep Learning to Estimate Age from Chest CT Scans Abstract: Purpose The objective of our study was to estimate a patient’s age from a chest CT scan and assess whether the CT estimated age is a better predictor of lung cancer risk than chronological age.Methods Composite images were created to develop an age prediction model based on Inception-ResNet-v2. We used 13824 chest CT scans from the National Lung Screening Trial (NLST) for training (91%), validation (5%), and testing (4%). We independently tested the model using 1849 CT scans collected in Saskatoon, Canada. We then assessed the CT estimated age as a risk factor for lung cancer screening using the NLST dataset. We calculated a relative lung cancer risk between two groups; group 1: those who are assigned a CT age older than their chronological age, and group 2: those who are assigned a CT age younger than their chronological age.Results Comparing the chronological age with the estimated CT age resulted in a mean absolute error of 1.91 years, and Pearson’s correlation coefficient of 0.9. The area associated with the lungs seemed to be the most activated region in the age estimation model. The relative lung cancer risk of 1.8 (95% confidence level) was calculated between the two groups, indicating a positive association between having an older Chest CT age (than chronological age) and having lung cancer.Conclusion Our results show that CT estimated age may be a better predictor of lung cancer than chronological age.

Abstract: In a smart city environment, the explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and entire network infrastructures, platforms as well as new resource management models. This poses significant challenges (and provides attractive development opportunities) for data-intensive and high-performance computing, i.e., how to turn enormous datasets into valuable information and meaningful knowledge efficiently. The variety of sources complicates the task of context data management such as data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time, rapid responses are needed for real-time applications. With the emergence of cloud infrastructures and platforms, achieving highly scalable data management in such contexts is a critical problem, as the overall urban application performance is highly dependent on the properties of the data management service. This means, continuously developing and adopting ICT technologies to create and use platforms for government, business and citizens can communicate and work together and provide the necessary connections between the networks that are the base for the services of the smart city .The main features of a generic Smart City Platform (SCP) are in the following Make data, information, people and organizations smarter Redesign the relationships between government, private sector, non-profits, communities and citizens Ensure synergies and interoperability within and across city policy domains and systems (e.g. transportation, energy, education, health & care, utilities, etc.)Drive innovation, for example, through so-called open data, living labs and tech-hub.In this work, the authors propose an approach and describe a methodology and a modular and scalable multi-layered ICT platform called ENEA Smart City Platform (ENEA-SCP) to address the problem of cross-domain interoperability in the context of smart city applications. The ENEA-SCP is implemented following the Software as a Service (SaaS) paradigm, exploiting cloud computing facilities to ensure flexibility and scalability. Interoperability and communication are addressed employing web services, and data format exchange is based on the JSON data format. By taking into account these guidelines as references, this work provides a description of the SCP developed by ENEA and its potential use for smart and IoT city applications. The solution provided by ENEA SCP to exploit potentials in Smart City environments is based on four fundamental concepts: Open Data,Interoperability, Scalability, Replicability. In this scenario, the ENEA SCP is going to tackle the issues concerning these two aspects providing a reference framework of modular [2] specifications for stakeholders willing to implement ICT platforms to exploit the Smart City vision potentials and therefore offer new services for the citizen. The ENEA Smart City Platform exploits computational resources of the ENEAGRID infrastructure [3], as it is deployed in the cloud hosted in the Portici Research Center site. The creation of a customized environment ENEA cloud-based platform is possible thanks to the virtualization technologies of VMWARE platform, which allows hosting the management, the transportation and the processing of project data services, ensuring their availability and protection over time. More in detail, the SCP is composed by six Virtual Machines (VMs), and each of them hosts a component with a specific role.


Designation: Interdisciplinary Analyst at EthicsNet, USA.

Biography: Adam Alonzi is a futurist, writer, biotechnologist, programmer, and documentary maker. He is an interdisciplinary analyst for EthicsNet, a nonprofit building a community with the purpose of co-creating a dataset for machine ethics algorithms. He also serves as the Head of New Media at BioViva Science, as an analyst for the Millennium Project, and as a consultant for a number of technology startups.


Abstract: Outcomes on the macro level often cannot be accurately extrapolated from the microbehaviors of individual agents. The interdependence of complex system’s components makes simulation a viable option for exploring cause and effect relationships within it (Miller and Page, 2009). Chaos theory emphasizes the sensitivity of such networks to starting conditions (Boccaletti, 2000), which strongly suggests thought should be put into the architecture of an AGI “society” before it begins to take shape. Protocols for emergency interventions should certainly be in place, but the network itself should be robust enough from the beginning  to handle sudden deviations from basic ethical precepts by one or more of its members.Outside of its context, and without any information about the parts to which it is connected, a cell or leaf or animal  can be studied, but not understood in a meaningful way (Mitchell, 2009). Creating moral agents in a hyperconnected world will involve modeling their interactions with entities like and unlike themselves in the face of both predictable and unforeseen events. This will be helpful as groups can behave differently than their individual parts (Schelling, 1969) Keeping AI friendly does not end with giving each AI a set of maxims before letting them loose, but satisfactorily explicating upon the emergent phenomena that arise from the interactions of similarly or differently “educated” machines. Because of the near certainty that synthetic intelligences will communicate rapidly and regularly, it is imperative that thought leaders in AI safety begin thinking about how groups of artificially intelligent agents will behave.

Name: Qamar Wali

Designation: National University of Technology, Pakistan

Biography: Dr. Qamar Wali has been working as Assistant Professor of Physics at National University of Technology since September 2018. He has earned PhD in Advanced Materials from Universiti Malaysia Pahang in 2016 and currently involved on renewable energy technology research, particularly perovskite solar cells. He has published more than 30 research articles so far in world renowned journals with citations > 1300. He has also obtained a Malaysian Patent on the topic of ‘multichannel nanotubular metal oxide’ and also is a recipient of the award of Research Fund for International Young Scientists (RFIS-I), funded by National Natural Science Foundation of China. During the teaching, he has successfully implemented the OBE system for Applied Physics in different engineering programs. He has been involved in a project “Third Generation Photovoltaics for Building Integration: A Smart and Sustainable Energy Solution” with US-PAK Center for Energy at University of Engineering and Technology, Peshawar, Pakistan.

Title of the talk: Semi-transparent solar panels for smart buildings

Abstract: Considering the ongoing energy crises in developing countries such as Pakistan, fast, reliable, simple, and less time-consuming as well as cost-effective methods of producing electricity are required to replace the complicated procedures of generating electricity using conventional methods. Global demand for energy is increasing rapidly, because of population and economic growth, especially in emerging market economies. Cities consume more than two-thirds of the world’s energy resources and are responsible for around the same share of CO2 emissions. Buildings alone are responsible for 36% of global energy consumption and nearly 40% of total direct and indirect CO2 emissions. At the current pace, the global energy use in buildings could double or even triple by 2050, as the world’s population living in cities is projected to increase further in the next decades. As per new policy, all new buildings that will be occupied by public authorities should be nearly zero energy rated. This means that new buildings must generate their own energy from renewable sources and not be wholly reliant on traditional grid-based forms of fossil fuel related energy. Integrating photovoltaics in buildings represents a feasible solution towards energy efficient buildings and in order to achieve sustainable goals in cities, harvesting the full potential of the building (facades, windows) for renewable energy generation is required. Building integrated photovoltaics (BIPV) potential to integrate into the building envelope holds aesthetic appeal for architects, builders, and property owners and is a market sector that is expected to grow dramatically over the next 5–10 years. Among all existing photovoltaic technologies, 3rd generation solar cells have attracted substantial interest in BIPV due to reduced cost and possess a number of key advantages, including low weight, aesthetic value for architects and can be printed in any pattern making relatively low cost BIPVs, without significant compromise in efficiency. Keywords: Solar energy material; Semi-transparent devices; nanomaterials; light weight; flexibility;

Name: Manju K Manohar

Designation: Founder of WinWithManju, India

Title of the talk: Women Managers in IT and the need for Equity

Biography: Manju K Manohar PMP (B.Tech[E&C], MS) is an alumnus of BITS Pilani & IIMK. She has 22+ years of experience in leading IT companies & as the founder/director of WinWithManju which focuses on providing coaching/career counselling and consulting services. She won the prestigious Times Ascent Top 100 Influential Coaching Leader (2023). She has touched the lives of more than 15000 people as a trainer or as a coach/consultant. She is an India Prime Top 100 Author Awardee. She has won numerous other awards and has been featured in newspapers in 4 languages. She has received the Outstanding Toastmaster & Extra-miler award from Toastmasters International. She helped set up 22 gavel clubs (children’s clubs) in a single year & is an award-winning Area Director, and has received “Distinguished Toastmasters” – the highest educational award from Toastmasters International. She is an Amazon Bestselling Author. She is a TEDx Coach(Massachussetts) & an Author Coach. She is a social ambassador of the national NGO IDF.

Abstract: Did you know that a recent study (which is one of the most comprehensive ever) conducted by Pittsburgh-based human resources consulting firm DDI together with non-profit business research group The Conference Board reveals that the companies that perform best financially have the greatest numbers of women in leadership roles? In the companies that have the top 20% of financial performance, 27% of leaders are women. Among the bottom 20% of financial performers, only 19% of leaders are women.However, despite this fantastic report, studies have revealed that only a mere 28% of people in senior management roles are women and only 19% of the C-suite is female. In fact, it is much worse in IT, where only 26% of computer-science-related jobs are held by women, compared to the overall job market, which is about half female.

Why? Why? Why?

Let’s examine the various factors that prevent a woman from getting promoted to a managerial rank.

Based on first-hand personal experience as a woman employee and then as a woman manager, and now as a coach helping several women and men leaders, I have come to the conclusion that embracing equity is more important than embracing equality. In this keynote, we also would look at how organizations embracing equity rather than equality would not only help women managers but also the organization itself in the long run.

Name: Parul Chaudhary

Designation: Microsoft , India

Title of the talk: Key Pillars of Secure Multitenancy

Biography: Parul Chaudhary is a Mission-driven engineering professional with 23+ years of experience managing and growing technology organizations while working with cross-functional teams, and quickly scale up the development and delivery capabilities based on business needs. She has a proven record in establishing competitive engineering strategies and translating those into a detailed delivery plan to build the next-generation platform. Parul is Principal Leader at Microsoft Security where she works closely with Azure security teams to help identify and understand cybersecurity risks to allow them to make better and more informed business decisions.

Abstract: With the aim of building security in every aspect of cloud services, having a robust foundation, to implement security by design in all that we build and deliver today is important. The advantages of multi-tenant architecture go beyond efficiency and cost savings for organizations. It offers substantial benefits to customers and end users. But there are risks, especially associated with security, that need to be considered as well. In this talk, we would like to share information on key components that form the basis of secure multitenancy principles and discuss the approach Microsoft is taking to build secure multitenant systems including network, compute, and storage isolation. The Microsoft Security Development Lifecycle (SDL) provides comprehensive guidance for developing secure systems; this talk will focus on key architectural guidance for secure multitenancy, giving an introduction to the concepts and provide some general guidelines around virtualization, and isolation.