Lasitha holds a Ph.D.(2023) and an M.S.(2022) in Mechanical Engineering from University of Maryland and a B.Sc.(Hons.) in Engineering (2016) specializing Mechanical Engineering from University of Peradeniya. Lasitha has won the Rising Star 2022 award from the American Society of Mechanical Engineers (ASME) Dynamic Systems and Control Division (DSCD), 2022-2023 Maryland Robotics Center Graduate Research Assistantship (MRC-GRA) award and, several awards at the general convocation at the University of Peradeniya in 2016 including C.A.Hewavitharana Prize for the Best Performance in Engineering and Channa Lalith Maddumage Prize for the Best Performance in Mechanical Engineering. 

He has recent  experience working as a Graduate Teaching Assistant and a Graduate Research Assistant at the University of Maryland. He also served as a temporary Lecturer at the Dept of Mechanical Engineering at University of Peradeniya in 2017-2018.

Lasitha Weerakoon has experience working in projects involved in a complex interconnection of robotics, control theory, machine learning, and computer vision and delivering tangible results with quick progress. He is a responsible team player who is enthusiastic about what he is doing and motivated to continuously learn to keep his knowledge up to date.

• His Ph.D. dissertation was on dynamic control of dexterous soft robotic systems. (6+ years experience on soft robotics, controls, dynamics, LSTM, OptiTrack motion capture, soft robot fabrication)

- used controls concepts such as passivity-based adaptive and robust control, and energy based control and tailored them for soft robots.

• During his Ph.D. studies, he was also a graduate research assistant for a multidisciplinary research project on autonomous navigation. (3+ experience on SLAM, ROS, TensorFlow, LiDAR)

- developed an algorithm to detect and map transparent objects (e.g. glass walls) using 2D LiDAR data and packaged it as a SLAM algorithm leveraging Google Cartographer.

- designed a pipeline for data collection and training using deep neural networks for navigation among dynamic obstacles.

• Lasitha has 12+ years experience on MATLAB, Simulink, Arduino, 5+ years experience on Python and 2+ years experience on UR3e robotic manipulator arms.