Rahul Choudhary

Researcher in Robotics and Deep Reinforcement Learning


About Me

Researcher in Robotics and Deep Reinforcement Learning

I focus on the intersection between control in Robotics and Reinforcement Learning. My aim is to develop algorithms and techniques with the help of which machines can autonomously acquire the skills for executing complex tasks.

Name: Rahul Choudhary
Experience: 1.5 Years
Birthday: 1 December 2000
Permanent Phone: +91 9079102623
Email: rcstark3614@gmail.com


[Google Scholar]

[Research Gate]


Education & Expericence

My Education

B.Tech in Aerospace Engineering and M.Tech in Artificial Intelligence Machine Learning and Applications

Indian Institute Of Technology Kharagpur | 2019 - Present


Class XII

MDS SCHOOL | 2016 - 2018


Class X



My Experience

Mitacs Research Intern

Mila - Quebec AI Institute | May 2022 - August 2022

  • Work focuses on Optimisation and Reinforcement learning

  • Carried out an empirical study to understand the effects of different optimizers and their critical gradient versions on Atari/Atari100k using Rainbow DQN Algorithm.

Reinforcement Learning Research Intern

Symbiosis Centre for Applied Artificial Intelligence | September 2020 - January 2023

  • Work focuses on Robotics, Reinforcement learning and Allied areas.

  • Created a sample efficient state representation learning framework (ShivNet) from the observations

  • Incorporated Reinforcement Learning with ShivNet for Self-Supervised Robotic Manipulation tasks like lifting, grasping of objects, opening and closing drawer.


DeepLearning.AI | August 2021 - September 2022

Resolving doubts and issues of students who take courses on Deeplearning.ai/Coursera

Software Development Intern |

Jan Elaaj Healthcare (P) Ltd. | 2021 - Present

Work focus on using image/signal processing techniques from computer vision to develop health care product.


My Publications

Spatial And Temporal Features Unified Self Supervised Representation Learning Networks

September 2022

Rahul Choudhary, Rahee Walambe, Ketan Kotecha




My Projects

Deep Reinforcement Learning Notebook Series

06 2020 - 04 2021

  • Implemented basic Deep Reinforcement Learning algorithms like REINFORCE, SARSA, DQN, A2C to advanced algorithms like DQN with Prioritised Experience Replay and target networks, PPO extending Actor- Critic Algorithm, SAC,A3C, Noisy Nets,Rainbow in various easy and medium level difficult gym environments.

  • Codes were written from scratch in tensorflow framework in python.Reproduced approximately 70-80 of the level of accuracy provided in the research papers that introduced the algorithms.


Robot Manipulation Task using IRL and SAC (Learning from Human Demonstration

10 2020 - 11 2020

  • Implemented Time-Contrastive Networks and Soft-Actor Critic to form a pipeline of inverse reinforcement learning to perform robotic grasping.

  • The robot is able to learn to pick up objects similar in shape but different in size from only one video demonstration of human picking up the block.


Robotic Car Path Planning

06 2021 - 06 2021

  • Utilized the Twiddle algorithm to optimise parameters for a PD Controller and combined with a Smoother to make a robotic car reach its goal on a smooth path without colliding.

  • Implemented a particle filter for localisation of the car and A* Algorithm to find optimal path.