Faculty Candidate Seminars

Cross-Layering in Future Wireless Networks: From Compact Full-duplex Radios to City-Scale Experimentation

Small-Data Learning in Big Cyber Physical Systems

Large-Scale Optimization and Nonconvexity: From Deep Learning to Energy Markets

Learning from Societal Data: Theory and Practice

Canceled: Scalability and Methods of Deep Learning from an Optimization Viewpoint

Towards Scalable Algorithms for Distributed Optimization and Learning

Learning Low-complexity Models from the Data – Geometry, Optimization, and Applications

Sight and Sound

Information Theoretic Limits in Learning: Applications to Privacy and Security

Delay, memory, and messaging tradeoffs in distributed service systems

Modelling and Analysis of Brain Network Dynamics via Systems and Control Theory

System Architecture Directions for Post-SoC/32-bit Networked Sensors

Indoor Human Information Acquisition from Physical Vibrations

Deep Learning for Medical Imaging: Mapping Sensor Data to Decisions

Learn Policy Optimally via Efficiently Utilizing Data

Rethinking the role of optimization in learning

Seeing the Unseen: Data-Driven 3D Scene Understanding for Robot Vision

Sequential Learning, Optimization and Control for Cyber-Physical Systems

Exploiting Geometry for High-Resolution Source Localization

Decision Making Under Uncertainty in Networks of Strategic Agents

Efficient scalable algorithms for adaptive data collection

Tackling the size and complexity of large-scale neural datasets

Integrated Magnetics and Multiferroics for Compact and Power Efficient Sensing, Power, RF, Microwave and mm-Wave Electronics

Towards a Theory of Safe and Interactive Autonomy

Growth, Characterization and the Impact of Wide-Bandgap Materials on Electronic Devices

Next-Generation Computing using Spin-Based and 2D Materials