The PhD forum at SEC 2021 provides an opportunity for PhD students to present their ongoing research, explore their research interests and career objectives with other PhD students and senior researchers in person in San Jose, CA. The presenters at the forum are expected to be PhD students who have a concrete dissertation proposal outlining the key challenges they plan to solve as well as the strategies and methodologies that are applicable. Domain experts from industry will be invited to provide their valuable suggestions, and the forum will also be an excellent opportunity for developing person-to-person networks to the benefit of the PhD students in their future careers. PhD forum presenters will have the priority to be considered for the student travel grant opportunity.

PhD Forum Presntation

PhD Forum Session, Dec. 16
  1 Understanding Time Variations in DNN Inference for Autonomous Driving. 
Liangkai Liu (Wayne State University)
  2 Untangling the Cloud from Edge Computing for IoT. 
Nabeel Nasir (University of Virginia)
  3 Extended Abstract on Federated Learning on Heterogeneous Clients. 
Yiyue Chen (University of Texas at Austin)
  4 Mechanisms Supporting Compute/Data Orchestration Policies for Geo-Distributed Situation Awareness Applications. 
Harshit Gupta (Georgia Institute of Technology)
  5 TrustZone Enhanced Plausibly Deniable Encryption System for Mobile Devices. 
Jinghui Liao (Wayne State University)
  6 Scheduling with Performance, Accuracy and Cost Trade-offs for Edge-based Applications. 
Sohaib Ahmad (University of Massachusetts, Amherst)
  7 Self-Adjusting Video Analytics Pipeline (VAP). 
Sibendu Paul (Purdue University)
  8 Efficient Meta Continual Learning on the Edge. 
Young D. Kwon (University of Cambridge)
  9 Design and Implementation of Fully Autonomous Aerial Systems. 
Jayson Boubin (Ohio State University)
  10 Adaptive Activation-based Structured Pruning. 
Kaiqi Zhao (Arizona State University)
  11 SecureFL: Privacy Preserving Federated Learning with SGX and TrustZone. 
Yitao Chen (Arizona State University)
  12 Reinforcement Learning for Adaptive Video Compressive Sensing. 
Sidi Lu (Wayne State University)


Please send email to for questions.