Scholar
Anand Balakrishnan
Google Scholar ID: egagNkwAAAAJ
Postdoctoral Fellow, University of Texas at Austin
Citations & Impact
Citations
226
H-index
6
i10-index
6
Publications
16
Co-authors
20
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Selected publications: 'Monitoring Spatially Distributed Cyber-Physical Systems with Alternating Finite Automata' (HSCC 2025, Best Paper Award), 'Motion Planning for Automata-based Objectives using Efficient Gradient-based Methods' (IROS 2024), 'Differentiable Weighted Automata' (ICML 2024 Workshop), 'Model-Free Reinforcement Learning for Spatiotemporal Tasks Using Symbolic Automata' (CDC 2023), 'PerceMon: Online Monitoring for Perception Systems' (Runtime Verification 2021), 'Augmenting Visual SLAM with Wi-Fi Sensing for Indoor Applications' (Autonomous Robots 2019), 'Structured Reward Shaping Using Signal Temporal Logic Specifications' (IROS 2019), 'Specifying and Evaluating Quality Metrics for Vision-based Perception Systems' (DATE 2019).
Research Experience
- Focused on the design and verification of controllers for learning-enabled cyber-physical systems during PhD, including: Incorporating formal methods in the design of controllers for autonomous systems, designing 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 autonomous vehicles), using runtime monitors to detect malfunction in perception systems (especially in multi-object detection and tracking).
Education
- PhD: Computer Science, University of Southern California, Summer 2025, advised by Jyotirmoy Deshmukh, part of CPS-VIDA group; B.S.: Computer Engineering, University at Buffalo, 2018, worked with Prof. Karthik Dantu at the Distributed Robotics and Networked Embedded Systems Lab.
Background
- Research interests: Intersection of formal methods and modern AI/ML, specifically in the design and verification of neurosymbolic systems. Brief introduction: Postdoctoral Fellow at the University of Texas at Austin.
