Panel Session: Perspectives on Machine learning

Machine learning and artificial intelligence can be found in everyday applications ranging from autonomous navigation, to extracting information from 'Big Data'. The application of machine learning raises a number of interesting and diverse questions. For example, how have aspects of machine learning positively and/or adversely impacted our everyday lives (e.g., smart phones), and is it someday possible for machine learning to provide a comprehensive framework for knowledge representation and reasoning? An expert panel made up of program managers and researchers from multiple government agencies will discuss these topics and more, as well as where future investments may lead.

Thursday, December 8, 13:00 - 13:45

Brian M. Sadler
Army Research Laboratory

Brian Sadler, ARL

Brian M. Sadler is the Army Senior Scientist for Intelligent Systems, and General Co-Chair of GlobalSIP’16. He is a Fellow of IEEE, and a Fellow of the Army Research Laboratory. He is an IEEE Signal Processing Society Distinguished Lecturer for 2017-2018, and his lecture topics include distributed collaborative intelligent systems, human-autonomy querying and interaction, and autonomous networking.


David Aha

Dr. David W. Aha (UCI, 1990) leads the Adaptive Systems Section within theU.S. Naval Research Laboratory’s Navy Center for Applied Research in Artificial Intelligence. His research interests include goal reasoning, case-based reasoning, mixed-initiative interaction, machine learning, planning, text analysis, and related topics pertaining to intelligent decision aids. He was a AAAI Councilor, founded the UCI Repository of Machine Learning Databases, co-founded the AI Video Competitions, and has received three Best Paper awards. David has (co)organized 24 international research events, (co)edited three special journal issues on AI topics, participated on 14 dissertation committees, serves on the editorial boards for three journals, and serves annually on the PCs for several conferences, workshops, and doctoral symposiums.

Charles Clancy

Dr. Charles Clancy is an Associate Professor of Electrical and Computer Engineering at Virginia Tech and directs of the Hume Center for National Security and Technology. Prior to joining Virginia Tech in 2010, he served as a senior researcher at the Laboratory for Telecommunications Sciences, a defense research lab at the University of Maryland, where he led research programs in software-defined and cognitive radio. Dr. Clancy received his B.S. in Computer Engineering from the Rose-Hulman Institute of Technology, M.S. in Electrical Engineering from the University of Illinois, and his Ph.D. in Computer Science from the University of Maryland. He is a Senior Member of the IEEE and has over 150 peer-reviewed technical publications. His current research interests include cognitive communications and spectrum security.

Jill Crisman

From December 2010-September 2016, Dr. Jill Crisman was a Program Manager at Intelligence Advanced Research Projects Activity (IARPA) in the Incisive Analysis Office. She created and directed the Finder Program which developed technologies to geolocate where a query image or video was taken based on the query’s content alone. She also directed the Aladdin Video program which developed technologies that can quickly search massive video collections for a user’s events-of-interest. She is currently Chief Scientist at Next Century Corporation.

Dr. Jill Crisman came to IARPA after over 20 years in academia and industry. Dr. Crisman participated in both DARPA Grand and Urban Challenges and developed algorithms for 3D reconstruction while at SAIC. She was a founding faculty member of the Franklin W. Olin College of Engineering where she created project courses to help reinforce learning in co-taught physics and mathematics courses. Dr. Crisman was Director of the Robotics and Vision Systems Laboratory at Northeastern University where she collaborated with colleagues on many projects including development of a robot hand, wheelchair, and lobster. She received her Electrical and Computer Engineering from Carnegie Mellon University and has authored over 50 academic publications.

Tom Rondeau

Dr. Tom Rondeau joined DARPA as a program manager in the Microsystems Technology Office in May 2016. His research interests include adaptive and reconfigurable radios, improving the development cycle for new signal-processing techniques, and creating general purpose electromagnetic systems.

Prior to joining DARPA, Dr. Rondeau was the maintainer and lead developer of the GNU Radio project and a consultant on signal processing and wireless communications. He worked as a visiting researcher with the University of Pennsylvania and as an Adjunct with the IDA Center for Communications Research in Princeton, NJ. In these roles, he helped push forward architectures and algorithms in signal processing for communications, signal analysis, and spectrum monitoring and usage.

Dr. Rondeau is active in many conferences and workshops around the world to help further research and technology in these areas, and he has consulted with many companies and government organizations on new techniques in wireless signal processing. He has published widely in the fields of wireless communications, software radio, and cognitive radio. Dr. Rondeau holds a Ph.D. in electrical engineering from Virginia Tech and won the 2007 Outstanding Dissertation Award in math, science, and engineering from the Council of Graduate Schools for his work in artificial intelligence in wireless communications.

Paul Tilghman

Mr. Paul Tilghman joined DARPA in December 2014 as a Program Manager in the Microsystems Technology Office. His research interests include intelligent and adaptive RF systems, digital signal processing, machine learning, wireless communications and electronic warfare. Prior to joining DARPA, Mr. Tilghman was a senior research engineer at Lockheed Martin’s Advanced Technology Laboratories where he led programs in adaptive electronic warfare, signals intelligence and non-cooperative geolocation. While at Lockheed Martin, Tilghman led the development of a real-time cognitive electronic warfare system, which used machine learning techniques to characterize and counter previously unknown radio emitters on the battlefield. He is a recipient of Lockheed Martin’s highest award, the NOVA award, and was also previously honored as the company’s Engineer of the Year. Mr. Tilghman received a bachelor of science in computer engineering from the Rochester Institute of Technology and a master of science in electrical engineering from Drexel University.

GlobalSIP 2016 thanks the following for their support.