Summary
Anand Balakrishnan is a Computer Science PhD candidate at USC specializing in designing and verifying controllers for cyber-physical systems, with a focus on integrating formal methods into reinforcement learning and time-sensitive, safety-critical controller synthesis. He combines academic research with hands-on industry experience—developing runtime monitors for perception-based control at TRI, prototyping Level 2 autonomy at INDI EV, and building sensor-consistency monitoring frameworks at Siemens. His work emphasis on using temporal logic to shape RL reward design and runtime monitors for fault detection reflects a practical bridge between theory and deployable autonomy. With an 11-year engineering background that began in embedded robotics and Wi‑Fi‑augmented SLAM during his undergrad, he brings both low-latency perception experience and systems-level thinking to autonomy safety. Based in Los Angeles, Anand’s projects consistently aim to make learning-enabled systems auditable and certifiable for real-world deployment.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Southern California
High School, Science with Economics, 94.4%, High School, Science with Economics, 94.4% at The Lawrence School, Lovedale
Bachelor’s Degree, Computer Engineering, 3.724 GPA, Bachelor’s Degree, Computer Engineering, 3.724 GPA at University at Buffalo
Hindi, Tamil, English