Hello, I am Athindran. I am currently a machine learning engineer in Behavior Planning at Aurora Innovation in Pittsburgh, PA. I was a sixth-year PhD student in the Department of Electrical and Computer Engineering at Princeton University. I was fortunate to be advised by Prof. Peter Ramadge.

Resume / Google Scholar / Github

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Research

My research was focused on designing safety fallback mechanisms for autonomous systems with provable guarantees. I utilize various tools, ranging from classical control to model-based optimization, to enable these filters to satisfy desirable properties such as smooth handover and robustness to imperfect models. My general research focus over the past few years has been on applying optimization and learning methods to control applications.

Publications

  1. A. R. Kumar, K. -C. Hsu, P. J. Ramadge and J. F. Fisac, “Fast, Smooth, and Safe: Implicit Control Barrier Functions through Reach-Avoid Differential Dynamic Programming,” in IEEE Control Systems Letters, doi: 10.1109/LCSYS.2023.3292132 Link to paper
  2. Liang Heng, Athindran Ramesh Kumar and Grace Xingxin Gao, Location Hash: Private Proximity Detection Using Partial GPS Information, IEEE Transactions on Aerospace and Electronic Systems. Dec. 2016. Link to paper
  3. Ting-Han Fan, Athindran Ramesh Kumar, Peter J. Ramadge. “Safety Control for Prime Focus Spectrograph.” In 2022 56th Annual Conference on Information Sciences and Systems (CISS) (pp. 269-274). IEEE Link to paper
  4. Athindran Ramesh Kumar*, Sulin Liu*, Jaime F. Fisac, Ryan P. Adams, Peter J. Ramadge. “ProBF: Probabilistic Safety Certificates with Barrier Functions.” Presented at SafeRL workshop at NeurIPS 2021. Link to paper
  5. Athindran Ramesh Kumar, Balaraman Ravindran, and Anand Raghunathan. “Pack and detect: Fast object detection in videos using region-of-interest packing.” Proceedings of the ACM India Joint International Conference on Data Science and Management of Data. 2019. Link Featured in TechXplore

For a complete list, please visit Google Scholar

Projects with Code

Fast, smooth, and safe   Probabilistic Safety with GP

Talks and Presentations

Control theory and practice Deep learning
ECE General Exam ORFE Deep Learning Theory Seminar
ACC 2021 CSML Reading Group GNN part 1
CISS 2021 CSML Reading Group GNN part 2

Work Experience

  • ML Software Engineer, Behavior Planning at Aurora Innovation. Present
  • Software Intern, Control at Aurora Innovation. May - Aug 2022
  • Research Intern, Nokia Bell Labs. June - Aug 2021
  • Research Engineer, Center of Excellence in Wireless Technology. April 2016 - June 2018
  • Tech Intern, Google StreetView. May - August 2014

Reviewer Services

NeurIPS (2022-2024), ICML (2023-2025), ICLR (2021, 2023, 2024), CISS 2022, IJCAI 2024, IEEE RA-L, IEEE TCST.

Teaching Assistant

  • UIUC ECE 456 - Introduction to GNSS systems/GPS - Organized and led the lab sessions as a single TA for the course.
  • UIUC ECE 210 - Introduction to Analog and Digital Signal Processing
  • PU ELE 364 - Machine Learning for Predictive Data Analytics
  • PU ELE 456 - Machine Learning and Pattern Recognition
  • PU SML 201 - Introduction to Data Science
  • PU EGR 153 - Foundations of Engineering Physics
  • PU ELE 203 - Introduction to Circuits
  • PU ELE 368 - Introduction to Wireless Communication Systems

Outside Work

Back in my undergraduate days, I played quite a bit of tennis as a serious extra-curricular and represented the institute at the inter-IIT sports meet and the inter-collegiate sports fest. I was also involved in app development during my undergraduate years. I helped build Android apps for the institute’s technical and cultural festivals, Shaastra and Saarang.

Contact

You can reach me through email at r[dot]athindran[at]gmail[dot]com