Summary
Shlok Agarwal is a Deep Learning Engineer with nine years of multidisciplinary experience building perception, control, and autonomy systems for robotics and large-scale ML at NVIDIA and in academic labs. He combines hands-on deep learning and computer vision work (PyTorch, TensorFlow, OpenCV) with robotics control and embedded systems expertise developed at Virginia Tech, Ghost Robotics, and in NASA-focused student projects. His background spans industry internships at Apple, USC ISI, and NVIDIA to graduate research at the University of Michigan, giving him a rare bridge between production ML engineering and research-driven robotic autonomy. He led a 40-person team to prototype an autonomous ice-drilling robot for NASA competitions, illustrating both technical depth and program leadership. Based in Sunnyvale, he focuses on turning perception models into reliable, low-level control behaviors—often integrating multimodal sensors (LiDAR, motion, force) to close the loop between learning and real-world robot actions.
9 years of coding experience
4 years of employment as a software developer
Master of Science - MS Electrical Engineering and Computer Science, Master of Science - MS Electrical Engineering and Computer Science at University of Michigan College of Engineering
Bachelors Electrical and Computer Engineering, Bachelors Electrical and Computer Engineering at Virginia Tech College of Engineering