Contact Details

Professional Experience

Machine learning engineer at squark ai

September 2025 - Present

• Designed and maintained the Automodeler pipeline integrating H2O AutoML and AutoGluon, ensuring consistent metadata tracking of top-performing models and algorithms.

• Implemented enhancements to Automodeler_Stats.json, standardizing outputs across frameworks (H2O and AutoGluon) to capture key metrics (best model, algorithm type, feature importance).

Teaching Assistant for INST490 : Capstone for Information Systems

August 2024 - May 2025

College of Information - iConsultancy , University of Maryland, College Park, USA

• Led Capstone Development: Guided 200+ undergraduate students through the design and implementation of AI, ML, NLP, and full-stack web/app projects, providing technical mentorship and milestone-based progress evaluations.

• Enabled Real-World Skills: Facilitated hands-on learning of industry-standard tools and workflows (e.g., Git, Flask, React, Hugging Face) to ensure students could translate theoretical knowledge into deployable solutions.

• Enhanced NLP Application Proficiency: Advised multiple teams on NLP techniques such as text classification and sentiment analysis, supporting their integration into user-facing applications.

• Fostered Innovation: Oversaw research-driven solution development including market analysis, encouraging teams to align technical feasibility with user and industry needs.

Research Assistant 

August 2024 - January 2025

Tubaldi Lab, University of Maryland, College Park, USA

• Optimized Robotic Efficiency: Designed computational models that improved soft robotic geometry and control systems, resulting in a 5% gain in speed and movement efficiency.

• Applied Wasserstein Barycenter Techniques: Utilized Wasserstein barycenter to interpolate between bio-inspired base shapes, enhancing the stability and energy efficiency of underwater soft robots .

• Differentiable Design Optimization: Leveraged differentiable physics-based simulation and backpropagation through soft-body dynamics to perform gradient-based optimization of soft robot geometries and control inputs, significantly reducing the number of required simulation iterations.

Teaching Assistant for ENES221: Engineering Dynamics

May 2024 - July 2024

A. James Clark School of Engineering, University of Maryland, College Park, USA

• Delivered Conceptual Clarity: Guided students through core principles of Newtonian mechanics, planar motion, and energy methods using hybrid instruction and one-on-one mentoring sessions.

• Ensured Academic Rigor: Managed grading of problem sets, proctored exams, and provided individualized feedback to help students strengthen their understanding and performance.

• Enhanced Engagement: Designed interactive learning aids—including animations and real-world problem examples—to deepen conceptual grasp and promote active learning.

Mechanical Engineer at Brahm Works Pvt. Ltd.

December 2022 - March 2023

• Programmed and Integrated Control Systems: Developed and integrated PLC-based control systems using Siemens hardware to automate an accelerated bitumen testing setup.

• Product Development : Designed automated systems and indoor farming setups in Autodesk Fusion 360 and Solidworks, managed fabrication, and led final product assembly.

• Machine Learning for Smart Agriculture Automation: Engineered a sensor-driven hydroponic farming system using Raspberry Pi, LoRa modules, DHT22 (temperature/humidity), EC and pH sensors, and relay-controlled actuators; implemented time-series ML models to optimize irrigation, nutrient delivery, and lighting—boosting crop yield by 25%.

• Advanced Infrastructure Testing: Built a custom accelerated testing rig to simulate extreme weather conditions and analyze bitumen compositions, enabling data-backed recommendations for road construction in harsh environments.

Software Engineer (GET) at Tata Technologies

June 2021 - March 2022

• PLM Data Migration & Integration: Led data migration efforts for Magneti Marelli’s PLM systems, managing over 50+ TB of legacy and SAP-integrated data with custom parsing logic to ensure accuracy and minimal downtime.

• C++ Automation for Teamcenter: Wrote production-ready C++ scripts for Siemens Teamcenter to automate data validation and reduce manual QA tasks, decreasing processing time by 85%.

• Post-Go-Live Software Support: Delivered Tier-2 support during and after go-live phases, resolving critical defects, patching configuration issues, and ensuring stable production rollout.

• Lean-Based QA & Documentation: Applied Lean Six Sigma methods to identify bottlenecks in QA workflows, leading to faster test cycles and maintaining clean documentation using internal knowledge bases.

• Excel-Based Project Monitoring Tools: Built interactive Excel dashboards with macros and pivot tables to track task completion and surface metrics for weekly reporting to senior stakeholders.

• Cloud Migration Collaboration: Supported the PMO team during a multi-phase software upgrade for a global agribusiness client, including environment readiness checks and sprint-level status tracking.

Technical Skills and Expertise

Robot Opertating System(ROS) 

Experienced in both ROS1 and ROS2 for developing and integrating robotic applications using rclcpp (C++) and rospy (Python). Proficient in designing autonomous navigation stacks, including sensor integration (LiDAR, cameras, IMU), localization (AMCL, SLAM), path planning (Nav2, MoveBase), and behavior coordination for mobile and aerial robots in both simulation and real-world environments.

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Computer Vision

• • • Experienced in applying computer vision techniques to enhance robotic perception and autonomy across mobile and industrial platforms. Worked extensively on real-time tasks such as lane detection, stop sign recognition, obstacle tracking, and semantic/instance segmentation for scene understanding and navigation, using OpenCV and deep learning models. Skilled in object detection using point cloud data (via PCL/Open3D) and depth estimation from stereo and RGB-D cameras for accurate 3D spatial understanding.

    • Proficient in camera calibration, LiDAR-camera fusion, AprilTag tracking, and image correction methods to improve localization and manipulation accuracy. Integrated these pipelines into ROS2 for tasks like visual SLAM and vision-based control of robotic arms. Additionally, developed structure-from-motion (SfM) workflows for 3D scene reconstruction, and worked on surround view stitching and wide-FOV correction to enhance environmental awareness in autonomous robotic systems. 

    • Currently developing 3D reconstruction pipelines for drone-captured monocular RGB imagery by leveraging tools like COLMAP and MASt3R.

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AI and Deep Learning

• • • Experienced in applying deep learning techniques to robotic perception and control using PyTorch, TensorFlow, and Keras. 

    • Skilled in developing and deploying CNN, LSTM, and Transformer models for tasks such as object detection, scene understanding, and sequence classification. 

    • Familiar with reinforcement learning(RL), model optimization, and integration of AI/ML pipelines into ROS2 for robotic applications.

    • Adept in fine-tuning and transfer learning of large language models (LLMs) for domain-specific tasks, with experience in model deployment and performance optimization.

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Motion Planning & Autonomous Navigation

• Skilled in implementing classical and sampling-based path planning algorithms including DFS, BFS, Dijkstra, A*, Bi-directional A*, RRT, RRT*, RRT*-Smart, Real-Time RRT*, and Potential Fields. 

• Proficient in designing and deploying SLAM-based autonomous navigation strategies for both simulated and real-world robotic systems, with an emphasis on robustness and real-time performance. 

• Additionally, experienced in using MoveIt for motion planning, collision avoidance, and trajectory generation in industrial robotic arms, including inverse kinematics and CNC tending workflows in factory cell simulations.

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Control Systems 

• Proficient in designing and implementing a range of controllers for robotic applications, including PID, LQR, LQG, feedback linearization, and adaptive sliding mode control. Experienced in modeling, simulation, and validation of control strategies using MATLAB and Simulink.

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Software Development

• Programming Languages: Python, C++ (14/17), C, MATLAB, Bash, Shell Scripting, Java, C# (.NET), CUDA

• Version Control :  Proficient in Git with hands-on experience using GitHub and GitLab. Skilled in CI/CD integration and applying branching strategies including feature, release, and hotfix workflows. Contributed to open-source projects, collaborating through pull requests and issue tracking.

• Containerisation and Deployment : Skilled in Docker for application packaging and deployment. Experienced in packaging and delivering Over-the-Air (OTA) software updates, for remote deployment of applications and system updates. 

• Operating Systems :  Strong command of Linux systems, particularly Ubuntu and ROS-based setups, with working knowledge of Windows for development and debugging.

Other Technical Skills

• Design and Development :   Extensive experience in designing and developing mechanical components and systems using CAD tools such as AutoCAD, SolidWorks, CATIA, and Fusion 360. Skilled in interpreting technical drawings, tolerance analysis, and design for manufacturability (DFM).

• Fabrication & Simulation : Skilled in hands-on fabrication, including sheet metal work, prototyping, and assembly. Experienced in additive manufacturing (3D printing using FDM and SLA), as well as utilizing Finite Element Analysis (FEA) tools for structural validation and optimization.

• Manufacturing Tools & Processes: Familiar with CNC machining workflows, rapid prototyping techniques, and integration of mechanical designs into robotic and embedded platforms.

• PLM & Engineering Data Systems: Experienced with Siemens Teamcenter for product lifecycle management (PLM), including data migration, version control, and workflow automation. Proficient in analyzing and validating large-scale engineering datasets and applying Computer-Aided Engineering (CAE) tools to support simulation-driven design and quality assurance

Master of Engineering in Robotics, University of Maryland College Park

August 2023 - May 2025 

Coursework : 

• ENPM662, Introduction to Robot Modeling : A+

• ENPM667, Control of Robotic Systems : A-

• ENPM809Y, Introduction to Robot Programming : A

• ENPM661, Planning for Autonomous Robots : A+

• ENPM673, Perception for Autonomous Robots : A

• ENPM690, Robot Learning (Reinforcement Learning) : A+

• ENPM645, Human Robot Interaction : A+

• ENPM700, Software Development for Robotics : A+

• ENPM703, Fundamentals of AI and Deep Learning : B

• ENAM788M, Hands On Autonomous Aerial Robotics: A+

• ENPM818N, Cloud Computing : A

Final GPA : 3.881 / 4.0

Through my graduate studies, I have developed a comprehensive understanding of computer vision (CV), artificial intelligence (AI), and machine learning (ML) as applied to robotics. My practical experience includes deploying deep learning models for perception, implementing vision-based navigation, and applying reinforcement learning for autonomous decision-making. I have also built strong expertise in robot kinematics and dynamics, control theory, and path planning algorithms, enabling the development of robust autonomous systems.

I’ve gained hands-on experience in motion planning, SLAM, and perception pipelines using tools like ROS, OpenCV, and Gazebo, along with integrating LiDAR and RGB-D camera data for environment understanding. My background includes designing human-robot interaction systems, writing production-grade robotic software in C++, Python, and ROS2, and exploring scalable cloud architectures for deploying robotics and AI workloads. Currently, I am working with autonomous aerial platforms, focusing on real-time control, onboard perception, and 3D reconstruction from monocular imagery.

Bachelor of Engineering in Mechanical Engineering, Ramaiah Institute of Technology

Coursework : 

Mechanical and Robotics 

• Robotics 

• Electronics

• Control Systems

• Vibrations

• Kinematics 

• Mechanics

• Electrical 

Mathematics and Programming :

• Engineering Mathematics 

• Computing and Programming (C++, Python, C)

Design and Manufacturing 

• CAD/CAM

• Machine Design

• Finite Element Analysis (FEA)

• Machining (Traditional and Non-Traditional)

My undergraduate studies in Mechanical Engineering at Ramaiah Institute of Technology provided a solid foundation in system dynamics, mechanical design, and simulation. I gained hands-on experience with CAD/CAM, FEA, and core engineering tools, while developing programming skills in C++, Python, and C that supported my growing interest in automation and robotics. This blend of mechanical and computational training prepared me to transition into robotics, enabling me to work effectively across both hardware and software domains.

Projects

Checkout my projects here : Projects 

Hobbies AND INTERESTS

Passionate about travel and outdoor exploration, especially trail hiking and adventure biking. Currently training regularly at the gym with a focus on fitness and endurance. Aspiring to travel the world on a motorcycle.

University of Maryland – Maryland Day Showcase

Represented the Drone Lab and Robotics and Automation Lab (RAL) during the Maryland Day event. Demonstrated research projects, answered public queries, and promoted STEM engagement through hands-on robotics and drone exhibits.

FIRST Robotics Competition

Volunteered as a scorer at the FIRST Robotics Competition, ensuring accurate match scoring and assisting with event logistics. Supported the smooth operation of matches and contributed to creating an engaging and fair experience for all participating teams.