Hi There,
I'm Nitish John Rawat
Bridging
See What I Build
I design and build intelligent systems at the intersection of machine learning, robotics, and software engineering. My work focuses on turning research ideas into practical, scalable solutions from robotic manipulation in simulation to ML models for real-world medical and educational applications.
My work focuses on what truly matters: reliable systems, clean and secure design, and intelligent automation — building technology that scales, adapts, and delivers real-world impact.
Education: Master’s in Computer Science (Completed) : Clark University
Seeking: Full-time opportunities in AI, robotics, or software engineering (Web/Mobile)
where I can build intelligent systems and continue growing as a lifelong learner.
email : nitishjohnrawat@gmail.com
place : Boston, US
Education is not the learning of facts, but the training of the mind to think.
Clark University, Worcester, MA
Worcester Polytechnic Institute, Worcester, MA
SRM Institute of Science and Technology, Chennai, India
AI-powered tutoring platform with voice-guided lessons using Whisper STT and Coqui TTS. Designed a deterministic LLM pipeline with adaptive learning analysis and a full-stack architecture deployed on AWS.
Code
Designed a secure, cloud-based healthcare application architecture for MyBILH Chart (Epic EHR). The project evaluated Azure deployment strategy, HIPAA compliance, security risks, disaster recovery, and enterprise-scale data storage.
Academic project exploring the Presorting technique as an instance of the Transform-and-Conquer paradigm in algorithm design. Analyzed classical problems including element uniqueness, closest pair, convex hull, and meeting scheduling with formal time and space complexity evaluation.
Implemented analytical and SGD-based linear regression models and MLPs to predict UR10 end-effector pose from joint angles. Focused on feature engineering and model comparison.
Modeled object push dynamics using physics-based equations, neural networks, and hybrid models. Compared accuracy, loss curves, and trajectory predictions.
Implemented DDPG and A3C from scratch to train a Kuka robot in PyBullet. Analyzed policy learning, stability, and continuous control performance.
Built an Action Chunking Transformer (ACT) for peg insertion using MuJoCo. Trained on multi-view RGB demonstrations and evaluated closed-loop performance.
Conducted advanced research projects under non-disclosure agreements spanning healthcare machine learning and human-centered AI. Work included predictive modeling for Renal Cell Carcinoma (RCC) and the development of multi–large language model systems for empathic, emotionally-aware communication.
Responsibilities covered data analysis, model design, evaluation strategies, and ethical considerations in sensitive, real-world environments. Due to NDA restrictions, code, datasets, and detailed results cannot be publicly shared.
Focus Areas: Medical AI, Multi-LLM Systems, Empathic Communication, Healthcare Data, Responsible AI
Sep 2025 – Present | Worcester, MA
Designed and developed a mobile EdTech application using Flutter/Dart, integrating RESTful APIs and backend services to deliver responsive, voice-guided learning experiences. Improved application performance through testing, debugging, and optimization prior to deployment.
May 2025 – Present | Worcester, MA
Led financial planning and research coordination for the IEEE student chapter. Developed and evaluated machine learning models (ANN, DNN, XGBoost) for renal cell carcinoma tumor size prediction, achieving 76% accuracy, and contributed to drafting an IEEE-style research paper.
Aug 2025 – Dec 2025
Led a multi-member team to architect and build an AI-powered tutoring platform integrating Whisper STT and Coqui TTS for adaptive, voice-based learning. Designed the full stack across Flutter, Django REST, PostgreSQL, Docker, and AWS EC2.
