Robotics Controls Engineer

Building controls-first robotics systems.

I work across system identification, robot dynamics, state estimation, planning, trajectory optimization, and learning-aware robotics software for collaborative and humanoid platforms.

Research-to-deployment robotics engineering.

I build real-time robotics software and control algorithms with a bias toward methods that remain interpretable, benchmarkable, and deployable.

Professional Summary

Robotics Controls Engineer with 4+ years of research and industry experience developing real-time robotics software and control algorithms for collaborative and humanoid robots. My work spans numerical optimization, task-space control, system identification, state estimation, trajectory optimization, and motion planning.

I also bring working exposure to optimal control, reinforcement learning, classical machine learning, and generative AI research, with a strong preference for turning theory into reusable software and moving algorithms from simulation toward physical systems.

From mechatronic prototyping to modern robotics control stacks.

My recent work combines model-based methods, simulation platforms, and software infrastructure for high-performance robotics.

Sept 2024 - Present

Robotics Controls Engineer

Neura Robotics GmbH, Metzingen, Germany

  • Contributing to system identification, robot kinematics and dynamics, planning, controls, and trajectory optimization for fixed-base and floating-base robots.
  • Building exposure across Newton, MuJoCo, Isaac Sim, and adjacent simulation stacks for locomotion and manipulation workflows.
  • Working around the stack needed for whole-body planning, controllers, state estimation, and tracking for complex robot systems.

Nov 2021 - Aug 2024

Student Research Assistant

WZL, RWTH Aachen, Germany

  • Built expertise in inertial-parameter and friction-model identification for industrial robot dynamics.
  • Worked on structured learning pipelines that combine model-based methods with machine learning for torque prediction.
  • Supported interpretable ML workflows and deployed research notebooks with Docker and RWTH JupyterHub infrastructure.

Oct 2022 - Mar 2024

Student Assistant, Optimal Control and Informatics

Chair of Intelligent Control Systems, RWTH Aachen, Germany

  • Guided students implementing PI, PID, and MPC controllers on the FloatShield apparatus using Arduino.
  • Prepared lecture notes on the Pontryagin Maximum Principle and graded coursework for more than 50 students.
  • Supported laboratory sessions on Kalman filters, Model Predictive Control, and Receding Horizon Control.

Aug 2018 - Aug 2019

Product R&D Engineer, Mechatronic Systems

Carnot Technologies, Mumbai, India

  • Conceptualized and prototyped automation systems for product development workflows.
  • Developed functional prototypes aligned with ISO and IEC standards and generated bills of materials for sourcing.

A controls-heavy profile with ML and full-stack tooling when needed.

My strongest work sits at the boundary between mathematical modeling, practical software, and robotics deployment constraints.

Languages

C++, Python, TypeScript

Primary implementation languages for robotics libraries, experimentation, developer tooling, and browser-based interfaces.

Robotics and Optimization

Dynamics, control, planning

System identification, state estimation, realtime model-based controller design, trajectory optimization, and motion planning.

ML and RL

Physics-aware learning

PyTorch, JAX, diffusion models, actor-critic reinforcement learning, and Lagrangian neural networks for robotics research.

Simulation and Modeling

Robot-centric simulation stack

Pinocchio, Newton, MuJoCo, Isaac Sim, Gymnasium, and URDF-based systems for modeling and evaluation.

Software and Tooling

Research-to-product workflow

Docker, Linux, Git, CMake, nanobind, FastAPI, React, and Three.js for reliable development and delivery.

Working Style

Independent and direct

Independent learner, critical thinker, problem-solver, and clear communicator with a strong bias toward ownership.

Thesis and seminar work that shaped the current profile.

These projects capture the control, optimization, learning, and robotics themes that continue to define my day-to-day engineering work.

Thesis

Regularization in Differential Dynamic Programming

May 2023 - Jan 2024

Developed improved regularization methods for DDP, benchmarked them on pendubot, acrobot, and cartpole systems, and extended the analysis to autonomous-driving trajectory planning.

Implementation lives inside a dedicated trajectory optimization library.

Research Project

Condition Number Optimization

Mar 2022 - Mar 2023

Optimized excitation trajectories to reduce regressor condition number and improve inertial parameter identifiability in robot system identification.

View project

Seminar

Advanced Methods in Control and Optimization

Apr 2022 - Jul 2022

Reviewed online trajectory optimization for complex behaviors and wrote a concise report on DDP, with emphasis on regularization and line-search behavior.

View seminar repo

Seminar

Learning-based Control

Oct 2021 - Feb 2022

Analyzed AlphaGo, Monte Carlo Tree Search, and deep reinforcement learning, then summarized the architecture and training logic in a written review.

View seminar repo

Seminar

Ethics in AI and Robotics

Apr 2021 - Sept 2021

Evaluated safety, accountability, transparency, and human impact in AI-driven robotics systems and published the seminar work at Machine Ethics.

View seminar repo

Reusable libraries and research platforms.

Most of my side projects are shaped as compact libraries or focused tooling platforms rather than one-off experiments.

Optimal Control

Trajectory Optimization Library

On request

Compact C++ and Python framework for unconstrained optimal control with DDP, iLQR, and iLQG solvers for robotics problems.

C++ Python DDP iLQR

Trajectory Generation

Motion Generation Library

On request

Reusable trajectory-generation library with linear, polynomial, trapezoidal, jerk-limited double-S, and waypoint spline profiles for robotics and CNC workflows.

C++ Python Motion Profiles

Planning

Planning Algorithms Library

On request

Unified implementations of RRT, RRT*, RRT-Connect, PRM, PRM*, FMT*, BIT*, and RABIT* with obstacle handling, tests, and optional Python bindings.

C++ Python Motion Planning

Estimation

State Estimation Library

On request

Robotics-oriented estimation framework covering Bayes filter recursion, Kalman variants, particle filtering, and Gauss-Hermite Gaussian filtering.

C++ Bayes Filters Kalman Methods

Generative AI

Diffusion Models Platform

GitHub

PyTorch DDPM research platform with configurable U-Net diffusion models, Gaussian diffusion utilities, AMP plus EMA training, and sampling workflows.

Python PyTorch DDPM

Reinforcement Learning

RL Projects Platform

GitHub

Single experimentation suite for dynamic programming, Monte Carlo methods, temporal-difference learning, DQN variants, policy gradients, actor-critic, and model-based reinforcement learning.

Python RL Experimentation

Learned Dynamics

Lagrangian Neural Network Platform

GitHub

Research platform for LNN, DeLaN, and FeLaN dynamics modeling with reproducible training workflows, double-pendulum baselines, and Pinocchio-based dataset generation.

Python JAX PyTorch

Visualization

Robot Viewer

GitHub

Full-stack robot visualization tool with a FastAPI backend and React plus TypeScript frontend for URDF, MJCF, and USD inspection in the browser.

FastAPI React Three.js

Kinematics

Inverse Kinematics for 7-DoF Robot

GitHub

Redundancy-resolving inverse kinematics solver with pseudo-inverse Jacobians, null-space projection, and secondary objectives for robust motion execution.

C++ Jacobian Methods IK

Mechanical engineering foundation, then robotics and control specialization.

My academic path moved from classical engineering analysis into robotics, optimal control, reinforcement learning, and numerical optimization.

Graduate Study

RWTH Aachen University

M.Sc. in Robotic Systems Engineering

Oct 2020 - May 2024

Coursework included advanced robot kinematics and dynamics, optimal control, reinforcement learning, numerical optimization, machine learning, computer vision, and self-driving vehicles.

Undergraduate Study

Veermata Jijabai Technological Institute

B.Tech. in Mechanical Engineering

Aug 2014 - May 2018

Built a base in mechatronics, automotive engineering, electrical drives, computational fluid dynamics, finite element methods, and broader engineering analysis.

Open to any research-engineering conversations.

If you want to talk about research-engineering problems that intersect with mathematics and its applications whether it is controls, neuroscience, biology, etc., I would love to connect. I am also open to conversations about potential collaborations, or just sharing ideas in the robotics and controls space.