Deepening my knowledge on the theoretical frameworks of fast-evolving field of Machine Learning with a fundamental approach (Learning from the scratch / first principles).
Learning to navigate an academic researcher's life.
Leveraged end-to-end ML solutions for:
Revenue Prime™ (revenue management for CPG industries)
Optimized promotions cost for improved Promotion RoI by 15%. Price optimization to tackle inflationary pressures. Increase in revenue by 2-5% through insights on key growth levers.
Envirozone™ (sustainability as a service)
Built carbon footprint forcasting models for Scope 1, 2, and 3 emissions across the value chain to meet the greenhouse gas (GHG) emission protocol requirements and Science-based Targets initiative (SBTi) and Carbon Disclosure Project (CDP).
GPT 3.5 came in November 2022, and it changed course of my journey. Over the next 1.5 years I realised that I was just doing the surface works like writing ML pipelines, or integrating GenAI features to some platform, etc majorily by relying on LLMs code generation capabilities, instead of self-thinking. So I decided to pursue a theoretical research career in ML in order to learn the fundamentals of the field.
My focus was on understanding Machine Learning concepts. I managed this along with my primary undergraduate (EE) studies initially and with my full-time work later.
Hybrid mode taught me to choose good but limited resources, prioritize quality education over quantity, time management and importance of being consistent in a particular field of study.
I also got the pleasure to serve as the founder secretary of the Gir House and hence a member of the first Upper House Council in the student community. Also served some committee roles in the office of IIT Madras.
| Year | Engineering Rank | University Rank |
|---|---|---|
| 2017 | 9 | 5 |
| 2023 | 10 | 4 |
Institute ranks under 10 in the country around my graduation.
CGPA: 8.4/10
Gained quality education in the field of Electrical Engineering and statistical foundations which later on became framework for my career as ML researcher. Electives included Advanced Instrumentation (Measurements), Analysis of Measurement Data, and Artificial Intelligence which developed my keen interest in the field of Machine Learning.
Developed a systems-thinking approach. The transition from physical electrical circuits to computational neural networks was my most significant takeaway.
It was during this journey that I realized the importance of having a good guide to learn from and the option of choosing a great one was waiting for me in the future.
Percentage: 89.3/100. DPS, Mandla Road
Science Stream (Mathematics, Physics, Chemistry, Biology).
CGPA: 9.4/10. CCBSSS, South Civil Line
Foundational years that built my curiosity for how systems work—from mathematical equations to biological organisms.