Sajal Tyagi

Product Manager

Delhi, India2 yrs 3 mos experience
Most Likely To Switch

Key Highlights

  • Dual degree candidate at IIT Delhi in Mathematics and Computing.
  • Experience in developing innovative AI models and algorithms.
  • Strong foundation in data analysis and machine learning techniques.
Stackforce AI infers this person is a skilled candidate in AI and machine learning development.

Contact

LinkedIn

Skills

Other Skills

Data AnalysisMachine LearningPython (Programming Language)

About

I am a dual degree candidate at IIT Delhi majoring in Mathematics and Computing. I’m interested in Graph ML, Continual Learning and Multi-Modal Generative AI. Feel free to ping me if you need to reach out for a potential opportunity or just to chat in general.

Experience

Sony | technology

Research Engineer

Oct 2024 – Present · 1 yr 5 mos · Tokyo, Japan · On-site

Indian institute of technology, delhi

Teaching Assistant

Jul 2023 – May 2024 · 10 mos · Delhi, India · On-site

  • Teaching Assistant for the courses -
  • MTL100: Calculus, Fall 2023
  • MTL108 : Statistics, Spring 2024

Sonyai

DL Research Intern

May 2023 – Jul 2023 · 2 mos · Tokyo, Japan · On-site

  • Developed a Novel Text-to-2.5D model for 3D asset creation at Foundation Models lab

Ripik.ai

ML Intern

Jun 2022 – Aug 2022 · 2 mos · Delhi, India · Remote

  • Worked closely with Godrej Interio team to model Production constraints for their factories and also leveraged data analysis techniques to look for production trends
  • Created data-driven Job-Shop scheduling and sequencing algorithms to automate production planning and improve Productivity and OTIF for the steel production plants
  • The Code contributed is still being actively used at the plant and was one of the first module of the Ripik Optimus Toolkit
  • Received a return offer for exceptional performance

Indian institute of technology, delhi

Undergraduate Researcher

Dec 2021 – Apr 2022 · 4 mos

  • Worked on Developing a Novel feature-based Graph Coarsening Approach for robust and scalable GNN training using PyTorch and open-Source large Graph Datasets
  • Achieved Significant performance retention for high coarsening ratios
  • Code + PPT can be found here - https://github.com/STK101/GraphCoarsener

Education

Indian Institute of Technology, Delhi

Bachelor of Technology - BTech — Mathematics and Computing

Jan 2019 – Jan 2024

AECS, Narora

Class 10

SR Public School, Kota

12 Class

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