Hire Top 3.5% Robotics Engineers - Shortlisted by AI

Professional experience of 8 years with a strong background in Python, Machine learning, Deep learning, data analytics and NLP. With experience in developing predictive models and working on various data science tools, I am eager to explore data sets to solve complex business problems. Strong communication skills with the ability to effectively translate complex technical concepts to non-technical stakeholders. Having knowledge in all stages of the data science lifecycle, from data collection and preprocessing to model deployment and visualization.

Research Area: Robotic Grasping, Machine Learning and Adaptive ControlPublications :Hirakjyoti Basumatary, and Shyamanta M. Hazarika."Design optimization of an underactuated tendon-driven anthropomorphic hand based on grasp quality measures." Robotica (2022): 1-20.Hirakjyoti Basumatary, and Shyamanta M. Hazarika." State of the Art in Bionic Hands." IEEE Transactions on Human-Machine Systems, 50, no. 2 (2020): 116-130.Dey, Abhijit, Basumatary, Hirakjyoti, and Shyamanta M.Hazarika. "A Decade of Haptic Feedback for Upper-Limb Prostheses ." IEEE Transactions on Medical Robotics and Bionics (2023)Hirakjyoti Basumatary, Daksh Adhar, Atharva Shrawge, Prathamesh Kanbaskar and Shyamanta Moni Hazarika "A Reinforcement Learning Approach for Bionic Reflex Control in Anthropomorphic Hands Exploiting Domain Randomization," Robotics and Autonomous Systems, Elsevier, 2024. (Revision Submitted)Hirakjyoti Basumatary, Tamen Thapa Sarkar and Shyamanta Moni Hazarika "Robustifying a ReinforcementLearning based Grasped Object Slippage Prevention Controller through Adaptive Sliding Mode Control," 28th International Conference on Methods and Models in Automation and Robotics (MMAR) 2024. (Submitted)Hirakjyoti Basumatary, Tamen Thapa Sarkar and Shyamanta Moni Hazarika "Robustifying a ReinforcementLearning Agent based Bionic Reflex Controller through an Adaptive Sliding Mode Control," Robotica 2024.(Submitted)Hirakjyoti Basumatary, Atharva Shrawge, Prathamesh Kanbaskar and Shyamanta Moni Hazarika "Low-Level Grasp Controller for Slippage and Deformation Prevention exploiting Deep Reinforcement Learning" In Advances in Robotics-6th International Conference of The Robotics Society, 2023Hirakjyoti Basumatary, Daksh Adhar, Riddhiman Shaw, and Shyamanta Moni Hazarika "Grasp Force Optimization as a Bilinear Matrix Inequality Problem: A Deep Learning Approach" 6th National Conference on Multidisciplinary Design, Analysis and Optimization (NCMDAO 2023)Key courses taken: Machine Learning: Pattern Recognition and Machine Learning, Reinforcement Learning, Deep Learning, Meta Learning, Transfer Learning, Deep Unsupervised Learning, Recommender Systems, MLOps Bootcamp (Udemy)Natural Language Processing: Introduction to Natural Language Processing, Natural Language Processing in Python, Natural Language Processing with Transformers, CS224N NLP with Deep LearningRobotics: Robotics and Robot Applications, Mechanics and Control of Robot Manipulators, Robotics Operating System (ROS 1 and ROS 2), Mechatronics, Signal Processing, Wheeled Mobile RoboticsControl: Control Systems, Nonlinear Adaptive Control, Sliding Mode Control, Digital ControlComputer Vision: Deep Learning for Computer Vision, Computer Vision Basics, Modern Computer VisionMiscellaneous: Object Oriented Programming in Python, Search Methods in Artificial Intelligence, Fundamentals of Artificial Intelligence, Data Structures and Algorithms, Finite Element Analysis

Bringing 3 years of hands-on experience in the robotics domain, I specialize in creating efficient, reliable software systems with ROS1, C++, Python, Qt, and QML. My work in deploying scalable solutions on AWS and optimizing databases with MongoDB has allowed me to contribute significantly to the success of cross-functional teams. I am dedicated to designing robust product architectures that align with both technical and business goals.

I’m an Electronics and Communication Engineering student at the National Institute of Technology Warangal with a strong interest in robotics, autonomous systems, and computer vision. Through multiple robotics internships, I’ve worked on areas such as sensor fusion, SLAM, stereo vision algorithms, and robot navigation using tools like ROS, Gazebo, and Nvidia Jetson. I’ve contributed to projects ranging from shopping robots to flapping-wing micro aerial vehicles for artificial pollination, focusing on building intelligent systems that can perceive and interact with their environments. I enjoy solving complex robotics problems by combining embedded systems, control theory, and machine learning concepts.

Verification & Validation Engineer with over 6 years of experience across the embedded systems development lifecycle. Skilled in designing, developing, and implementing comprehensive test strategies. Possesses a strong background in both hardware and software quality assurance, with hands-on expertise in system-level testing, defect tracking, and process improvement. Proven ability to ensure product reliability and compliance with industry standards.

I hold an MSc in Cyber Security and a B.E. in Mechatronics. My expertise spans networking protocols and infrastructure, including BGP, OSPF, TCP, Frame Relay, DNS, and OAuth, along with strong experience in IP networks, LAN, WAN, ISP environments, AWS, SD-WAN, VXLAN, and next-generation firewalls. I work across operating systems such as Cisco IOS, Junos OS, Unix, and Linux, and have experience with management solutions like HPE Service Manager and Cisco ISE. My knowledge also includes security policies and frameworks such as PKI and OIDC. Additionally, I am proficient in tools and technologies including SAML, Microsoft Excel, Microsoft Visio, Azure, Python, and SQL, with a strong foundation in cryptography and encryption.