
AI Fellow @ PI School '24 | Bioinformatics Intern '24 @ Regeneron | ML Engineer Intern '23 @ Fusic.co, Japan | GSoC '22 @ TensorFlow | IITM '25
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Indian Institute of Technology
Data Scientist
June 19, 2026 – Present
Quark_Formers
July 4, 2025 – July 4, 2025
The goal of this project is to build a 100-200M parameter model, I'm going to pre-train, finetune and post-train models. Let's see if we can beat the big models in intelligence, speed and efficiency!
View ProjectSarvam_ResearchFellow_Assgn
April 5, 2025 – April 8, 2025
This repo contains my submission to the Sarvam RF assign
View ProjectAccelerating_TransferLearning_for_MotorImagery
February 18, 2025 – April 15, 2025
This is the accompanying codebase to the paper: "Riemannian Transfer Learning in Motor Imagery decoding: Reproducibility and Standardized Benchmarks"
View Projectinterp-project
September 28, 2024 – September 30, 2024
interp-project — GitHub repository
View ProjectTinyML_OV7670
July 30, 2022 – September 13, 2022
This repo contains all the necessary files to build a MNIST TinyML application, that works with an OV7670 camera module and TFT LCD module.
View Project3D-Unity-game-using-MPU6050-and-TinyML
June 22, 2022 – August 28, 2022
This repo contains all the necessary files to build a 3D Unity Game integrated with an TinyML controller
View ProjectSmartwatch_From_Scratch
December 1, 2021 – April 9, 2022
This is a project to build a smartwatch from scratch. The Progress will be updated in this repository as needed.
View ProjectSummer-School-2021
July 11, 2021 – October 9, 2021
The repository for Summer School organised by Electronics club in July 2021.
View ProjectCultural Fit Analysis
The candidate shows a strong inclination towards personal projects, particularly in the TinyML and embedded systems domain. This indicates a proactive and hands-on approach, which can be a positive cultural fit for innovation-driven teams. However, the projects are predominantly personal and academic, with limited information on collaborative efforts or real-world business impact. The breadth of technologies used (C++, Jupyter Notebook, Verilog, Coq, Ruby, HTML, CSS, JavaScript) suggests a curious and adaptable individual, but also a potential lack of deep specialization in core data science tools beyond TinyML. The target role is 'Data Scientist', but the projects lean heavily into embedded ML, which might require a specific type of data science role or further development in traditional data science areas.
Soft Skills & Operational Fit
The provided data is insufficient to assess soft skills or operational fit. No psychometric test results or interview feedback are available.