Summary
Shashank Marpally is a PhD candidate at NUS's CLeaR Lab researching robot learning, human-robot interaction, and classical planning under Dr. Harold Soh, with a focus on safety and trust in collaborative systems. With nine years of experience spanning research labs, industry internships, and competitive robotics, he blends strong theoretical skills in reinforcement learning and planning with hands-on systems work in ROS/ROS2, Gazebo, and CoppeliaSim. He has delivered practical robot solutions—from merging multi-laser scans for an autonomous forklift to data-driven inverse kinematics modeling—and has published his drive to “impart intelligence to robots” through code on GitHub. Comfortable across Python, C++, Matlab and robotics CAD tools, Shashank pairs rigorous academic training with prototyping and fabrication experience rooted in competitive robotics and interdisciplinary teams. Notably, he has repeatedly converted simulation insights into real-world robot behaviors, a thread that runs through internships at Toyota and research stints at ASU, IIT Bombay and IIT Kanpur.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Technology (BTech), Mechanical Engineering, 8.88 CGPA, Bachelor of Technology (BTech), Mechanical Engineering, 8.88 CGPA at National Institute of Technology Karnataka
Robotics and Autonomous Systems, Artificial Intelligence, 4.0, Robotics and Autonomous Systems, Artificial Intelligence, 4.0 at Arizona State University
Secondary Education, 95.6%, Secondary Education, 95.6% at National Public School , Rajajinagar
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at National University of Singapore
English, Telugu, Hindi, Kannada