Summary
Shreyas Sekhar is a research engineer based in California with nine years at Salesforce and over two decades in technology, specializing in robotics, distributed systems, and embodied AI. He has led real-world robotics deployments—integrating VLMs, LLM reasoning, ROS 2, and control stacks—to cut grasp failures and manual inspection effort by roughly a quarter to four-fifths while achieving sub-centimeter end-effector accuracy on humanoids. His work blends PyTorch/CUDA RL (PPO, SAC), TensorFlow pipelines, LangChain/RAG integrations, and trajectory optimization to deliver robust sim-to-real generalization across hundreds of hardware trials. Earlier roles accelerated edge perception and detection (MobileNetV3, YOLOv5/8 with TensorRT) for fast, accurate robotics perception in smart-city and drone use cases. He pairs deep hands-on systems engineering with academic training in mechatronics and robotics, and maintains an active interest in AI-driven manipulation and humanoid control that bridges research prototypes to production-ready robot systems.
9 years of coding experience
17 years of employment as a software developer
Nano Degree Gen AI, Nano Degree Gen AI at Udacity
Bachelor's degree Electrical and Electronics Engineering, Bachelor's degree Electrical and Electronics Engineering at University of Madras
Adarsh
Master's degree Mechatronics Robotics and Artificial Intelenge, Master's degree Mechatronics Robotics and Artificial Intelenge at Worcester Polytechnic Institute
Kendriya Vidyalaya Sangathan
English