Carnegie Mellon University is pleased to present the fourth in a series of Capitol Hill briefings on Artificial Intelligence (A.I.).
This briefing will highlight the expanding range of AI applications to societal problems to effect positive change. They include health, environmental sustainability, and many other areas.
Please join us for a discussion of how AI innovation in academia and the private sector is having transformative impact, as well as the potential policy implications of these innovations.
This will be a widely attended event in accordance with House Ethics rules.
Jason Hong is an associate professor in the Human Computer Interaction Institute, part of the School of Computer Science at Carnegie Mellon University. He works in the areas of usability, mobility, privacy, and security, and his research has been featured in the New York Times, MIT Tech Review, CBS, CNN, Slate, the World Economic Forum, and more. Jason is an associate editor for IEEE Pervasive Computing and ACM Transactions on Human Computer Interaction, and is on the editorial board for Communications of the ACM. He is also an author of the book The Design of Sites, a popular book on web design using web design patterns. Jason is also a co-founder of Wombat Security Technologies, which focuses on the human side of computer security. Jason received his PhD from Berkeley and his undergraduate degrees from Georgia Institute of Technology. Jason has participated on DARPA's Computer Science Study Panel (CS2P), is an Alfred P. Sloan Research Fellow, a Kavli Fellow, a PopTech Science fellow, a New America National Cybersecurity Fellow, and currently holds the HCII Career Development fellowship.
Anna is a deep learning data scientist at Intel’s Artificial Intelligence Product Group where she the head of their AI4Good efforts. She is currently investigating how AIPG and Intel could contribute to a number of potential social good projects. One of these projects is the use the AI in crop growth, determining how algorithms can aid greenhouse operators achieve the highest crop yields while minimizing the use of resources. Her team recently won a hackathon, where they obtained the highest profits in a simulated cucumber growing season.
Prior to leading the AI4Good efforts, she was researching deep learning algorithms for natural language processing. This included investigating problems such as text summarization, sentiment analysis, and question-answer systems. This work is included in Intel’s NLP Architect which is an open-source Python library.
Anna has an M.S. and B.S. in Aerospace Engineering from MIT. Prior to Intel, she was a senior data scientist at In-Q-Tel Lab41 and a geo-spatial data analyst at MIT Lincoln Laboratories. She is passionate about finding the most reliable and understandable way of letting an end user learn more about their data. Outside of work, she is a volunteer data lead with Delta Analytics, which pairs non-profit organizations with technical volunteers who provide them free data consulting and data services.
Fei Fang is an Assistant Professor at the Institute for Software Research at Carnegie Mellon University. Before joining CMU, she was a Postdoctoral Fellow at the Center for Research on Computation and Society (CRCS) at Harvard University. She received her Ph.D. from the Department of Computer Science at the University of Southern California in June 2016. She received her bachelor degree from the Department of Electronic Engineering, Tsinghua University in July 2011.
Her research lies in the field of artificial intelligence and multi-agent systems, focusing on data-aware game theory and mechanism design with applications to security, sustainability, and mobility domains. Her dissertation is selected as the runner-up for IFAAMAS-16 Victor Lesser Distinguished Dissertation Award, and is selected to be the winner of the William F. Ballhaus, Jr. Prize for Excellence in Graduate Engineering Research as well as the Best Dissertation Award in Computer Science at the University of Southern California. Her work has won the Innovative Application Award at Innovative Applications of Artificial Intelligence (IAAI’16), the Outstanding Paper Award in Computational Sustainability Track at the International Joint Conferences on Artificial Intelligence (IJCAI’15). Her work has been deployed by the US Coast Guard for protecting the Staten Island Ferry in New York City since April 2013. Her work has led to the deployment of PAWS (Protection Assistant for Wildlife Security) in multiple conservation areas around the world, which provides predictive and prescriptive analysis for anti-poaching effort.
Jay Qi is a Data Science Technical Lead at Uptake, an industrial A.I. software company headquartered in Chicago. Uptake combines data analytics and machine learning with deep industry knowledge to unlock the power of AI for the global industrial sector.
In addition to his primary work predicting locomotive and heavy equipment failures using machine learning, Jay is closely involved with Uptake.org, the company's philanthropic and civic innovation arm. As a mentor for the Uptake.org Data Fellows Program, he has advised social sector data scientists since the program's founding, including those from the City of Chicago, the New York City Department of Education, and a technology platform for non-profits in Melbourne, Australia.
Jay has a M.S. in Mechanical Engineering from Caltech and a B.S.E. in Mechanical and Aerospace Engineering from Princeton. In his past life, he has worked on computational fluid dynamics, robotics, and aerospace engineering.
