Note

I am on the job market for postdocs, research scientist roles, and other similar roles.

The sidebar contains my one-page resume and my CV with my longer list of academic achievements (both updated March 2025).

About Me

I am a Computer Science PhD candidate at the University of Southern California. I am part of the CPS-VIDA group, and my advisor is Prof. Jyotirmoy Deshmukh. My research interests lie in the design and verification of controllers for cyber-physical systems.

My research involves:

• Incorporating formal methods in the design of controllers for autonomous systems. This includes:
  • Design of reward functions for reinforcement learning agents, given temporal logic task specifications.
  • Controller synthesis for time-sensitive and safety-critical tasks.
  • Marrying automata theory with array programming and gradient-based optimization pipelines.
• Fault detection and verification of perception-based control systems, especially in the context of autonomous vehicles.
  • Use of runtime monitors to detect malfunction in perception systems, especially in the context of multi-object detection and tracking.

Before this, I received my B.S. in Computer Engineering from the University at Buffalo in 2018, where I also worked with Prof. Karthik Dantu at the Distributed Robotics and Networked Embedded Systems Lab.

Selected Publications

• Monitoring Spatially Distributed Cyber-Physical Systems with Alternating Finite Automata

  Anand Balakrishnan, Sheryl Paul, Simone Silvetti, Laura Nenzi, and Jyotirmoy V. Deshmukh.

  In 29nd ACM International Conference on Hybrid Systems: Computation and Control (HSCC), May 2025. (Accepted)

• Motion Planning for Automata-based Objectives using Efficient Gradient-based Methods

  Anand Balakrishnan, Merve Atasever, and Jyotirmoy V. Deshmukh.

  In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2024.

  arxiv

• Differentiable Weighted Automata

  Anand Balakrishnan, and Jyotirmoy V. Deshmukh.

  In ICML 2024 Workshop on Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators, June 2024.

• Model-Free Reinforcement Learning for Spatiotemporal Tasks Using Symbolic Automata

  Anand Balakrishnan, Stefan Jakšić, Edgar A. Aguilar, Dejan Ničković, and Jyotirmoy V. Deshmukh.

  In 2023 62nd IEEE Conference on Decision and Control (CDC), December 2023.

  PDF arxiv Poster

• PerceMon: Online Monitoring for Perception Systems

  Anand Balakrishnan, Jyotirmoy Deshmukh, Bardh Hoxha, Tomoya Yamaguchi, and Georgios Fainekos.

  In Runtime Verification, October 2021.

  arxiv

• Augmenting Visual SLAM with Wi-Fi Sensing for Indoor Applications

  Zakieh S. Hashemifar, Charuvahan Adhivarahan, Anand Balakrishnan, and Karthik Dantu.

  In Autonomous Robots, December 2019.

• Structured Reward Shaping Using Signal Temporal Logic Specifications

  Anand Balakrishnan, and Jyotirmoy V. Deshmukh.

  In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019.

  PDF Poster

• Specifying and Evaluating Quality Metrics for Vision-based Perception Systems

  Anand Balakrishnan, Aniruddh G. Puranic, Xin Qin, Adel Dokhanchi, Jyotirmoy V. Deshmukh, Heni Ben Amor, and Georgios Fainekos.

  In 2019 Design, Automation Test in Europe Conference Exhibition (DATE), March 2019.

  PDF

For most up-to-date publication information, check out my DBLP or Google Scholar pages.