Matteo Vanotti
CEO
xFarm
AI is revolutionizing the way we interact with our environment, even in the most extreme settings.
In this talk, we will explore two real-world case studies of how AI is being deployed to push the boundaries of what is possible. The first case study comes from satellites in orbit, leveraging deep learning to improve sensor readings and Federated Learning to share knowledge in a satellite constellation; the second example, we explore autonomous drones that sail the ocean to open new possibilities for scientific research and commercial uses.
Together, we would use these two examples show how do design and deploy AI applications for unlocking the potential of extreme environments.
Uri Rosenberg
Specialist Technical Manager, AI/ML
Amazon Web Services
Uri Rosenberg is the Specialist Technical Manager of AI & ML services within enterprise support at Amazon Web Services (AWS) EMEA. Uri works to empower enterprise customers on all things ML: from underwater computer vision models that monitor fish to training models on satellite images in space; from optimizing costs to strategic discussions on deep learning and ethics. Uri brings his extensive experience to drive success of customers at all stages of ML adoption.
Before AWS, Uri led the ML projects at AT&T innovation center in Israel, working on deep learning models with extreme security and privacy constraints.
Uri is also an AWS certified Lead Machine learning subject matter expert and holds an MsC in Computer Science from Tel-Aviv Academic College, where his research focused on large scale deep learning models.
Becky Soltanian
VP, Research & Development
Sanborn
Dr. Soltanian’s career in the field of AI has been extensive. With a global reach, her endeavors in AI, engineering, and academia span over 20 years. Her background includes a considerable amount of hands-on experience in a variety of roles in automation, AI, robotics, and computer vision. Most recently, Dr. Soltanian worked as a principal artificial intelligence and machine learning engineer, developing algorithms that improved perception and localization. She has also held leadership and management positions where she successfully directed teams in developing and applying advanced technologies in the use of lidar and other data types.
Dr. Soltanian holds a PhD in Electrical, Electronics and Communications Engineering; a Master of Technology in Digital Signal Processing; and a Bachelor of Science in Electrical Engineering. She’s worked for a variety of different companies such as Byton, Daqri and Velodyne Lidar, and has six (6) patents in the field of Autonomous Driving and automation.
Becky Soltanian
VP, Research & Development
Sanborn
Dr. Soltanian’s career in the field of AI has been extensive. With a global reach, her endeavors in AI, engineering, and academia span over 20 years. Her background includes a considerable amount of hands-on experience in a variety of roles in automation, AI, robotics, and computer vision. Most recently, Dr. Soltanian worked as a principal artificial intelligence and machine learning engineer, developing algorithms that improved perception and localization. She has also held leadership and management positions where she successfully directed teams in developing and applying advanced technologies in the use of lidar and other data types.
Dr. Soltanian holds a PhD in Electrical, Electronics and Communications Engineering; a Master of Technology in Digital Signal Processing; and a Bachelor of Science in Electrical Engineering. She’s worked for a variety of different companies such as Byton, Daqri and Velodyne Lidar, and has six (6) patents in the field of Autonomous Driving and automation.
Eugenio Zuccarrelli
Manager, Data Science
CVS Health
Eugenio is a Business-Focused Data Science Leader, leading the innovation efforts for several Fortune 500 companies across multiple industries, including Healthcare (CVS Health), Automotive (BMW) and Finance (Morningstar).
He is a Forbes 30 Under 30, a Fulbright Scholarship recipient and studied across MIT, Harvard and Imperial College London. Currently, he leads the innovation efforts for complex chronic care at CVS Health, the #1 Healthcare company in the world and a Fortune 5 firm.
In addition, he has been working in the Task Force using analytics to fight COVID-19 and develop policy recommendations for The White House and overall finding solutions to fight the COVID-19 pandemic. You can find Eugenio's work across Forbes, The Washington Post, Bloomberg and Financial Times as well as multiple journals and in the App Store.
When he is not working, Eugenio enjoys contemporary art as well as playing Tennis with friends and traveling.
Model Compression is paramount in the world of Edge AI, as it is key to enhancing the performance and efficiency of AI models on edge devices. This talk will highlight the key drivers behind the increasing necessity for model compression, the essential evaluation metrics, and a range of vital techniques involved in the compression process. We will then delve into notable innovations in the field, illustrated by a case study on the Jabra Panacast20, to demonstrate the real-world applications and benefits of these techniques. The session will wrap up with a summary and a Q&A segment, equipping attendees with the knowledge and tools needed to optimize AI models for edge deployment.
Anuj Dutt
Senior Software Engineer, AI Systems
Jabra
Anuj Dutt
Senior Software Engineer, AI Systems
Jabra
Sutanay Choudhury
Chief Scientist, Data Science
Pacific Northwest National Laboratory
Sutanay Choudhury is Chief Scientist, Data Sciences in Advanced Computing, Mathematics and Data division at Pacific Northwest National Laboratory, and the co-director of the Computational and Theoretical Chemistry Institute. His current research focuses on scalable graph representation learning and neural-symbolic reasoning, with applications to chemistry, medical informatics and power grid. Sutanay has more than a decade's experience in developing artificial intelligence and data analytics systems that extract, learn and search for patterns from the "complex web of things" - webs that emerge from atomistic interaction in molecular networks, to interaction between diseases, drugs and genes, or the web of human knowledge captured in knowledge bases such as Wikipedia, PubChem and SNOMED. His research has been supported by US Department of Energy, US Department of Homeland Security, DARPA and US Department of Veterans Affairs.