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nirav sawant

ESC
Mechatronics & Robotics

Engineering Intelligent
Autonomous Systems.

Embedded Systems • Control Theory • Machine Learning • GPU Computing

Mechatronics engineering student building real-time perception pipelines and control systems for robotics applications. Passionate about bridging hardware and software through embedded systems, CUDA acceleration, and safety-critical software design.

me

about me

I'm a Mechatronics and Robotics Engineering student focused on building reliable, production-minded autonomous and embedded systems. My interests span robotics integration, perception pipelines, and software that has to work under real-world constraints, not just in controlled environments.

I approach projects and internships from a systems perspective, overseeing interactions between components, defining and maintaining interfaces, managing version control history, and actively reducing regression risk as systems evolve. I care as much about how parts fit together and scale as I do about individual algorithms or features.

I've applied this mindset through hands-on robotics development in coursework, as well as contributions to open-source autonomous driving software, where code quality, review standards, and long-term maintainability matter the most. I enjoy working in environments that treat engineering as an end to end discipline, from testing and design to deployment and iteration.

Long term, I'm aiming to work on real-world autonomous systems where performance, safety, and reliability are non-negotiable.

experience

June 2024 - August 2024

junior AI content strategist

legacy+

championed communication with marketing/analyst teams
created ai tools to streamline development of educational content for partnering organizations

react node.js aws
May 2025 - August 2025

software engineer intern

cibc

Championed concept of SDLC
Contributed to multiple production level projects within the bank
Championed communication with analyst teams, and gained a thorough understanding of the commercial banking industry

react node.js aws

projects

StudentIO-v2

StudentIO is an adaptive learning system that treats instruction as a closed loop perception action problem. It infers learner state from interaction signals and adjusts explanation strategies over time for robust, personalized learning.

Python Machine Learning Adaptive Systems Education Tech

Invariant

Invariant explores a missing layer in modern robotics: the governance of complex systems using machine learning informed by control theory. Its purpose is to treat workflows themselves as dynamic systems in order to make robotics development more predictable, reproducible, and trustworthy.

Python Control Theory ML Governance Robotics

motion-aware-perception-model

CUDA accelerated machine learning perception model for robotics applications. Leverages GPU parallelism for real-time sensor fusion and object detection in dynamic environments.

CUDA C++ PyTorch Robotics Perception

Contact Me

my thoughts

Adaptive Learning Through Closed-Loop Perception

January 2025

Exploring how StudentIO reimagines instruction as a perception-action problem, using machine learning to infer learner state and adapt explanation strategies in real-time.

Machine Learning Education Tech Adaptive Systems

GPU-Accelerated Computing in Modern AI

January 2025

A deep dive into CUDA programming, the GPU computing paradigm, and how parallel processing enables real-time perception in robotics applications.

CUDA GPU Computing Deep Learning

Reach Out

Email

please feel free to reach out to talk about your projects!

niravsawant22@gmail.com

LinkedIn

let's connect!

Nirav Sawant
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GitHub

Check out my code

GitHub NiravTech22
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