Abhinav Sai Tummapudi
Core Member @Global Ai Hub
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WORK HISTORY
Core Member @Global Ai Hub
Collaboration with people across the world and learn core topics and new technologies-) Presenting seminar on the topics related to AI.
EDUCATION
George Mason University
Master of Science - MS, Computer Science - Machine Learning Concentration
Narayana Junior College
Intermediate Board Of Education, 12th Class
Sree Vidyanikethan Engineering College
Bachelor of Technology - BTech, Computer Science
CVR Memorial English Medium High School
Seconday State Board, 10th Class
George Mason University
Doctor of Philosophy - PhD, Mechatronics, Robotics, and Automation Engineering
CodePath
Intermediate Technical Interview Prep - TIP02, Computer Science
ABOUT ABHINAV SAI TUMMAPUDI
I am a PhD student in Robotics at George Mason University, focused on autonomous systems, artificial intelligence, computer vision, and human–robot interaction. My doctoral research emphasizes developing intelligent robotic systems that integrate perception, decision-making, and control, with a strong balance of theoretical rigor and real-world experimentation.In parallel with my PhD research, I serve as a Graduate Research Assistant with the Office of Research Computing (ORC), where I support Slurm-managed GPU and high-performance computing infrastructure used across the university. My work centers on GPU monitoring, systems automation, and performance observability, ensuring reliability and efficiency in shared research environments.I am the creator of GPU-Watch, a production-grade GPU monitoring framework built using Prometheus, Grafana, and NVIDIA DCGM, which I presented at SC25 (Supercomputing 2025) and am currently extending into a full paper submission to ACM PEARC 2026.Previously, I worked as a Technical Lead at Tata Consultancy Services (TCS), an experience that strengthened my approach to building robust, scalable, and production-ready systems.My interests lie in robotics and autonomous systems, supported by AI/ML and HPC infrastructure, with a focus on translating research ideas into reliable, real-world deployments.
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