MERL’s Virtual Open House 2020

December 9, 2020

Join us for MERL's virtual open house on December 9. Live sessions will be held from 1-5pm EST, including an overview of recent activities by our research groups and a featured guest speaker. Registered attendees will also be able to browse our virtual booths at their convenience and connect with our research staff on engagement opportunities including internship/post-doc openings as well as visiting faculty positions.


  • Date: Wednesday, December 9, 2020
  • Time: 1:00 - 5:00 PM EST

Live Session Schedule

1:00 - 1:40 EST Opening / MERL Overview
Dick Waters and Elizabeth Phillips
1:40 - 2:20 EST Computer Vision
Alan Sullivan
Controls for Autonomy
Stefano Di Cairano
2:20 - 3:00 EST Speech & Audio
Jonathan Le Roux
Multi-physics & Dynamics
Jay Thornton
3:00 - 3:40 EST Data Analytics
Daniel Nikovski
Kieran Parsons
3:40 - 4:20 EST Computational Sensing
Petros Boufounos
Multi-Physical Systems
Chris Laughman
4:20 - 5:00 EST Closing / Featured Talk
"Adversarial Machine Learning"
Prof. Pierre Moulin, University of Illinois at Urbana-Champaign


Virtual Exhibit Booths

The event will feature more than 20 virtual exhibit booths in key research areas. Attendees can visit these virtual booths at their convenience to learn more about MERL's research activities and internship opportunities. These virtual spaces will provide:

  • Material that provides a more in-depth view of our latest research results
  • Links to relevant internship and post-doc opportunities
  • Message or request meeting with research contacts

  • Artificial Intelligence
    • Multimodal AI
    • End-to-End Speech & Audio Processing
    • Machine Learning & Optimization for Robot Control
    • Robotic Perception
    • Visual Representations & Analysis
    • Human Monitoring
    • Learning & Inference
    • Power Systems Analytics
  • Signal Processing
    • Networking & Communications
    • Signal Modeling & Inverse Problems
    • Optical Sensing & Devices
    • Array Processing & Radar Imaging
    • Intelligent & Digital Radio
  • Optimization & Control
    • Autonomous Vehicle Systems
    • Cyberphysical Systems Control, Learning & Verification
    • Control & Dynamics for Mobility and Airflow
  • Multi-Physical Modeling & Simulation
    • Multiphysical Systems Modeling, Control & Learning
    • Advanced Motor Technologies


    Featured Guest Speaker

    Prof. Pierre Moulin, University of Illinois at Urbana-Champaign Prof. Pierre Moulin

    Adversarial Machine Learning

    Abstract: Deep neural networks achieve state-of-the-art performance for several image classification and automatic speech recognition problems but have been shown to be easily fooled by adversarial perturbations which slightly modify a legitimate input in a specific direction and are perceptually indistinguishable from the original. This presents a security risk for applications such as autonomous driving systems. This talk will present a systematic approach to detect adversarial inputs and is based on work done at MERL in 2019 and 2020.

    Pierre Moulin received his doctoral degree in 1990, after which he joined at Bell Communications Research as a Research Scientist. In 1996, he joined the University of Illinois at Urbana-Champaign, where he is currently Professor in the Department of Electrical and Computer Engineering, Research Professor at the Coordinated Science Laboratory and the Beckman Institute and the Coordinated Science Laboratory, and affiliate professor in the Department of Statistics.

    His fields of professional interest include statistical decision theory, statistical signal processing and modeling, machine learning, information security, and Shannon theory. Dr. Moulin has served on the editorial boards of the IEEE Transactions on Information Theory, the IEEE Transactions on Image Processing, and the Proceedings of IEEE. He was co-founding Editor-in-Chief of the IEEE Transactions on Information Forensics and Security (2005-2008), member of the IEEE Signal Processing Society Board of Governors (2005-2007), member of the IEEE Information Theory Society Board of Governors (2016-2018) and has served IEEE in various other capacities. He is co-recipient of two best paper awards from the IEEE Signal processing Society and was plenary speaker for ICASSP, ICIP, and several other conferences. He is an IEEE Fellow (2003) and was Distinguished Lecturer of the IEEE Signal Processing Society for 2012-2013 and co-chair of the technical program for ISIT 2015. He was UIUC Sony Faculty Scholar and is the recipient of the 2018 Ronald W. Pratt Faculty Outstanding Teaching Award.


    Contact Us

    If you are experiencing any issues with registration or accessing the event site, or would like further information about this event, please contact us at merl-voh2020[at]merl[dot]com .