I am a Robotics Engineer, currently working at Berkshire Grey Inc, that has some of the best and brightest roboticists in the world. I work at the intersection of Robotics, Computer Vision and Machine Learning.

2022 — NowBerkshire GreyPrincipal Robotics Software Engineer (Perception / Manipulation)

2022 — Now

United States

2019 — 2022Berkshire GreySenior Robotics Software Engineer (Perception/Autonomy)

2019 — 2022

Greater Boston Area

At Berkshire Grey, we believe it’s time to radically change the essential way we do

business. Our game-changing solutions combine AI and Robotics to automate omnichannel

fulfillment for enterprises serving today’s connected consumers. By

transforming pick, pack and sort operations, our technology is a fundamental engine of

change that moves you forward. Berkshire Grey customers include Global 100 retailers

and logistics service providers.

2017 — 2019Berkshire GreyRobotics Engineer

2017 — 2019

Greater Boston

2017 — 2017Robotics Realization Laboratory, University of Maryland College ParkGraduate Assistant

2017 — 2017

College Park, MD

Managed robots such as Baxter, Turtle Bot(2 & 3), Kuka Robotic Arms, Crazyflie and provided technical support to users

Created interactive demos, using ROS and C++, for various events that were held at University of Maryland

* Worked under the supervision of Prof. Sarah Bergbreiter

2016 — 2017Autonomy Robotics Cognition Lab, University of MarylandResearch Assistant

2016 — 2017

College Park, Maryland

Collected 60 GB of data of Crazy Flie Nano UAV being manually controlled to imitate the homing behavior of bees , in OptiTrack mocap environment.

Created the hardware and simulation test bed for the drone to perform deep-learning tests using NVIDIA Jetson TX1

Implemented Q Learning, Deep Q Network and Deep Deterministic Policy Gradient algorithms for position control of Crazyflie and proved that they can perform better than classical controllers, like PID, without modeling the dynamics

*Calibrated the cameras and rectified the images

Derived Odometry of the drone using Optical Flow Technique

Utilized libraries such as ROS, OpenCV, Keras, Tensorflow & Theano and Programmed using C++ & Python

* Worked under the supervision of Prof. Yiannis Aloimonos