Nidhin Ninan

Entrepreneurial AI & Controls Engineer | Passionate and Forever-Learning Self-Starter | Eagerly seeking roles in AI, Robotics, and Controls! Ready to contribute expertise, energy, and determination to make an impact!

I am an AI and Aerospace engineer with over three years of experience specialized in bridging aerospace control systems with Deep Reinforcement Learning (DRL), developing AI Agents over the past 2 years, and modern Vision-Language-Action (VLA) models.

I’ve spent the last few years getting my hands dirty in the full LLM lifecycle, moving far beyond basic API calls to manage the "guts" of these models, everything from dataset reformatting and loss masking to mixed-precision training and supervised fine-tuning (SFT). Whether it's pushing the reasoning limits of models like InternLM2-Math on complex STEM datasets or architecting multi-agent solver systems using LangGraph and n8n, I’m driven by the challenge of making AI actually work in the real world. I don’t just build "wrappers"; I build intelligent workflows that include cost-optimized model routing and verifiable reasoning to tackle the very real problems of performance trade-offs and hallucinations. 

My expertise spans the full development lifecycle of embodied intelligence, from engineering 6-DOF mathematical models and non-linear controllers in MATLAB to architecting imitation learning-based foundation models for multi-drone collaboration. I have a proven track record of delivering high-impact results, such as extending UAV target tracking from seconds to over six minutes using PyTorch-based Soft Actor-Critic (SAC) controllers and optimized auto-landing LQR control.

I am deeply committed to pushing the boundaries of autonomous systems through hands-on experimentation with bleeding-edge tools like NVIDIA IsaacSim, and Hugging Face’s LeRobot. My technical rigor is matched by my leadership experience; I have founded and coordinated research teams to success, recently securing a top 10% finish in a worldwide robotics hackathon by developing cost-effective teleoperation and data collection pipelines. Whether I am fine-tuning specialized LLMs for verifiable reasoning or designing bidirectional sim-to-real workflows, I focus on synthesizing NLP, computer vision, and control theory to create robust, intelligent robotic systems.

University of Central Missouri, Lee’s Summit, MO {May 2024 - December 2025}
Master of Science in Data Science and AI

Texas A&M, College Station, TX {August 2020 - December 2022}
Masters of Eng. in Aerospace Engineering

• Received Texas A&M Graduate Research Fellowship and worked as a Graduate Research Assistant at the Vehicle Systems and Control Laboratory.
• Graduated with certification in 'Business Immersion for Engineers' from Mays Business School, Texas A&M

University of Kansas, Lawrence, KS {August 2016 - May 2020}
Bachelor of Science in Aerospace Engineering (Hons.)

• Graduated with honors, receiving KU-IIE Scholarship, Vincent Muireheed Leadership Award and KU Undergraduate Research Award