Arijit Mallick

Papers

Total Citations

H-Index

About

Arijit Mallick is a robotics researcher whose work focuses on the intersection of deep learning and robotic manipulation, particularly for autonomous object recognition and grasping in unstructured environments. His most impactful contribution, "Deep Learning based Object Recognition for Robot picking task" (2018, 19 citations), addresses a critical challenge in industrial automation: enabling robots like the BAXTER to accurately identify and pick specific objects from cluttered scenes. By demonstrating that deep learning-based recognition outperforms traditional feature-matching algorithms in complex, real-world settings, Mallick provided a practical pathway for deploying more intelligent and reliable robotic pick-and-place systems. He further showcased his expertise in applied robotics as a key member of the UJI RobInLab team at the Amazon Robotics Challenge 2017 (8 citations), where the goal was to automate shelf picking—a notoriously difficult task requiring robust perception and dexterous manipulation. This competition work highlights his ability to translate research into high-stakes, real-world applications. With a total of 27 citations from these two pivotal papers, Mallick’s research is a valuable resource for students and engineers seeking to integrate deep learning into robotic grasping, offering a clear bridge between algorithmic innovation and tangible robotic performance.