Steven Astorino

VP of Development, Hybrid Cloud, z Analytics and Canada Lab Director at IBM

         

Data Science for Everyone

Monday, October 29th, 14:00 - 15:00

Short Abstract: Although an empirical approach to data is as old as the scientific method, the data driven transformation of business and society has initiated a renaissance, with data science and analytics emerging as a key engine of wealth and prosperity for the 21st century. Will better tools and better training satisfy the exploding demand? Should data science take its place with physics, chemistry and biology as a basic science everyone needs to learn? What opportunities will be created, and how will we take advantage of them?

Biography: Steven is a development executive with proven transformational leadership and expertise in leading large enterprise development teams and an experienced change agent with a proven track record to drive improvements and efficiency. Most recently he has been leading and driving the Machine Learning and Data Science strategy for IBM's analytics group and has delivered key strategic solutions including IBM Machine Learning and Data Science Experience.

Early in his career, Steven has spent several years working with network testing technologies for the telecom Industry and played a key role in providing VoIP testing solutions and has extensive experience with data technologies such as data movement and transformation from his days at DataMirror, to Database technologies such as DB2 LUW, DB2 for z/OS, IBM's latest Data and Analytics platform enabling data science and machine learning.

He has a Bachelor's Degree in Computer Science with a strong business background.


Jessica Pointing

Quantum Computing Researcher at Stanford, Harvard, MIT

         

The Quantum Computing Landscape

Tuesday, October 30th, 11:00 - 12:00

Short Abstract: Quantum computers have the potential to advance many other fields, such as machine learning, medicine, and energy systems. We could solve problems on quantum computers that are not possible to solve on our current classical computers in our lifetime. What are the potential applications of quantum computing? How do quantum computers actually work? How do we build quantum computers? How much progress have we made? Jessica Pointing will unpack the topic of quantum computing with a fascinating primer.

Biography: Jessica Pointing has conducted quantum computing research at Stanford, Harvard and MIT. She is currently a PhD student specializing in quantum computing at Stanford and has been awarded the Knight-Hennessy Fellowship. She completed her Bachelor's degree in Physics and Computer Science, with high honors and as a member of the academic honors society Phi Beta Kappa, from Harvard University after spending her first two years of university studies at the Massachusetts Institute of Technology (MIT). She also founded the Harvard College Quantum Computing Association. Jessica was the winner (audience vote) for the Quantum Matters Science Communication Competition and has been invited to talk about quantum computing at conferences, including IBM's conference in Las Vegas, the Chief Digital Officers conference in New York City and the Neo conference in Arizona. Jessica has interned as a software engineer at Google, management consultant at McKinsey & Company, investment banker at Goldman Sachs, and strategist at Morgan Stanley. She is the founder and editor-in-chief of Optimize Guide, a blog about life optimization, and founded the Now Know Organization, which received funding from Google to teach technology to young people. She has been awarded the McKinsey Women's Impact Award, MIT Award for Distinguished Achievement in Leadership, and has been named a Google Anita Borg Scholar and John Harvard Scholar (top 5% of class). She is also a Microsoft Scholar, Palantir Scholar, Adobe Research Scholar, Morgan Stanley Scholar, Goldman Sachs Scholar, Society of Women Engineers Scholar and Society of Geophysicists Scholar.


Walid Rjaibi

CTO, Data Security at IBM

         

Encryption, Key Management, and Quantum Computing

Tuesday, October 30th, 14:00 - 15:00

Short Abstract: Encryption is a fundamental technology for data protection. While Transport Layer Security (TLS) is widely accepted as the standard solution for encrypting data in transit, no single solution has achieved similar status for encrypting data at rest. We will review the most common strategies for encrypting data at rest and the use cases where each strategy is most appropriate. We will also discuss how exactly quantum computers will affect data encryption and how those concerns are being addressed.

Biography: Walid Rjaibi is Chief Technology Officer (CTO) for Data Security at IBM. As a Technical Executive and Distinguished Engineer, he drives the technical strategy and architecture for data security across products and cloud services (Guardium Database Activity Monitoring, Guardium Data Encryption, Security Key Lifecycle Manager, Guardium Multi-Cloud Data Encryption, and IBM Key Protect). Prior to his current role, he held several technical and management roles within IBM including Research Staff Member at the Zurich Research Lab, Security Architect for DB2 LUW, and Chief Security Architect for IBM Analytics. His Data Security work resulted in over 20 granted patents and several publications in leading scientific and academic conferences such as the international conference on Very Large Databases (VLDB), the International Conference on Data Engineering (ICDE), and the international conference on security and cryptography (SECRYPT). Walid is also a frequent speaker at industrial conferences such as IBM World of Watson, Interconnect, Security Congress, and the International DB2 User Group (IDUG).

Specialties: Information Technology, Software Development, Data Security, Application Security, Cloud Security, Security Compliance, Secure Engineering Deployment, Database Technology, Leadership, Staff Management and Team Building, Client Partnering


John Tsotsos

Distinguished Research Professor of Vision Science at York University's Lassonde School of Engineering, and Director of the Centre for Innovation in Computing at Lassonde

It Only Took 60 Years to Solve Artificial Intelligence - That Wasn't so Hard, Was it?

Wednesday, October 31st, 11:00 - 12:00

Short Abstract: It has been 62 years since the founding Dartmouth AI workshop. In the 1960's, researchers at MIT believed that developing a computer program to simulate a significant part of human vision could be accomplished by employing several undergraduate students over a summer. They quickly found out they were mistaken. Fast forward to the present day. AI is everywhere, solving all manner of hard problems and triggering debates about its ethics and societal impact. In contrast, scientists studying human (and animal) vision and intelligence have made no corresponding claims for breakthroughs in their understanding of human intelligence. Although a great deal has been learned in the past 60 years to be sure, each major discovery seems to emphasize how much remains unknown. Understanding the brain and how intelligent behaviour is produced remains a major challenge. Noting that the current AI successes are often claimed to be due to mimicking brain processes, is there a disconnect here? This presentation will suggest that there has been some tacit, gradual moving of the goalposts taking place and that there is indeed a disconnect. An understanding of the brain and behavioural sciences reveals many directions for future AI research, and importantly, how far there is still to go. Dramatically, this will require the abandonment of some of the longest held computational standards. Examples from my lab will illustrate.

Biography: John Tsotsos is Distinguished Research Professor of Vision Science in the Dept. of Electrical Engineering and Computer Science and Director of the Centre for Innovation in Computing at Lassonde, at York University. He has Adjunct Professorships in Computer Science and in Ophthalmology and Vision Sciences at the University of Toronto. He received his doctorate in Computer Science from the University of Toronto developing the first computer system to interpret visual motion depicted in digital image sequences, with application to heart motion analysis. After a postdoctoral fellowship in Cardiology at Toronto General Hospital, he joined the University of Toronto on faculty in both Computer Science and in Medicine. In 1980 he founded the highly respected Computer Vision Group at the University of Toronto, which he led for 20 years. He moved to York University in 2000 as Director of the Centre for Vision Research. Under his directorship, the centre was ranked in the top six interdisciplinary vision research organizations in the world. He has been a Canadian Heart Foundation Research Scholar (1981-83), a Fellow of the Canadian Institute for Advanced Research (1985-95) and currently holds the Canada Research Chair in Computational Vision (2003-2024). He has received many awards and honours including several best paper awards, among them a 1987 inaugural Marr Prize citation, the 1997 CITO Innovation Award for Leadership in Product Development, the 2006 Canadian Image Processing and Pattern Recognition Society Award for Research Excellence and Service, the 1st President's Research Excellence Award by York University on the occasion of the University's 50th anniversary in 2009, the 2011 Geoffrey J. Burton Memorial Lectureship from the United Kingdom's Applied Vision Association for significant contribution to vision science, has been an ACM Distinguished Speaker, and is an IEEE Fellow. He was elected as Fellow of the Royal Society of Canada in 2010, and was awarded its 2015 Sir John William Dawson Medal for sustained excellence in multidisciplinary research, the first computer scientist to be so honoured. He has co-founded or been a principal of several companies, and holds a number of patents and technology transfer licences. Visiting positions were held at: University of Hamburg, Germany; Polytechnical University of Crete, Greece; Center for Advanced Studies at IBM Canada; INRIA Sophia-Antipolis, France; and, the Massachusetts Institute of Technology, USA. His current research focuses on a comprehensive theory of visual attention in humans. A practical outlet for this theory forms a second focus, embodying elements of the theory into the vision systems of mobile robots.