Hey! I am

Mrinal

I'm a

About

About Me

Welcome to the chronicle of a techie, a researcher, and an AI/ML aficionado.

If I had to capture my journey in a few words, I'd say I'm a curious fella shaped by the illustrious halls of IIT. I'm IIT Gandhinagar (B.Tech) alumnus majoring in Computer Science and Engineering. Machine Learning isn't just a discipline for me; it's a canvas where I paint with algorithms, data, and imagination. Over the years, my curiosity has led me to dive into extensive research, resulting in several published papers that mirror both my passion for ML.

Research interest: Adversarial robustness and Explainable AI (XAI) systems. During my undergrad, I was fortunate to work on multiple sub-domains of machine learning: Computer Vision, NLP & RL. Some of the problems that I have explored includes study of adversarial robustness, self-supervised learning, program synthesis, entity extraction, HDR imaging & temporal coherency in videos. Please find my papers here. However, two areas that constantly beckon me are adversarial robustness and Explainable AI. There's a unique allure in ensuring the systems we design can stand their ground and, simultaneously, be transparent in their operations.

Professional Experience: I have 2.5+ years of experience in building scalable ML systems. As of today, I am an AI/ML Consultant with the expertise in NLP, CV and backend development. I am currently consulting for two organizations ARTPark and ARMMAN. My work is dedicated to transforming the landscape of healthcare in India, where I actively contribute to innovations and solutions aimed at improving health outcomes across the nation. Pastly I have worked at OrbitShift.ai as ML Engineer focusing mainly on LLMs & NLP. At Enphase I used to work on time-series forecasting & optimization related problems.

Education

2017-2021

Bachelors in Computer Science and Engineering

Indian Institute of Technology, Gandhinagar

Experience

Sept 2023 - Present

ML/AI Consultant, ARTPark IISC Bangalore

  • Currently building ML systems for project ARMMAN.
May 2023 - Sept 2023

Machine Learning Engineer(NLP), OrbitShift.ai

  • Build people (stakeholders) recommendation model using semantic matching corresponding to each business opportunity. Implemented contrastive learning losses to further boost the model accuracy by 4%.
  • Optimization: Optimized the response time of the search apis using Elastic search framework for efficient text searches. Reduced the API response time within 2 sec as compared to 9 sec (without Elastic search).
  • Automation: Build ChatGPT APIs to automate the process of complex data extraction & tagging from text, pdfsummarization, and sentence paraphrasing using OpenAI chat completion apis.
July 2021 - April 2023

Machine Learning Engineer, Enphase Energy

  • Architected and developed a predictive solar energy forecast API for the Enphase App.Leveraging historical energy data and system configuration information, we innovated to forecast the energy output of the Enphase System for future days. Devised algorithm achieves 𝑅2 greater than 0.9 for first three days.
  • Optimization: Benchmarked the deep learning model performance using light‐weight auto‐regressive models. Drastically reduced the API response time (within 3000ms) as compared to the previous baseline (10s).
  • Developed crucial features like support history, app tutorial, and custom data visualization tool for Enlighten Homeowner app.The app empowers the user to track their systems analytics and performance data. App has 100k+ downloads.

App Store Play Store

Dec 2020 - Present

Co-Founder

SZone

SZone is a B2B Augmented Reality based platform for salon and beauty franchises.

Pitch Deck

Aug 2020 - April 2021

Teaching Assitant, IIT Gandhinagar

ES 654: Machine Learning (Spring 2021) and CS 614: NLP (Fall 2020)

Faculty Advisor - Dr. Nipun Batra (ML) and Dr. Mayank Singh (NLP)

I throughly enjoyed teaching students about machine learning algorithms. Most of work involved designing the course syllabus, delivering practical sessions on Deep learning, developing open‑source code for student assignments and reference notebooks, weekly project discussion sessions. I mentored a total of 8 student projects in both the courses. Topics ranging from Reinforcement learning, AI Safety, Program Synthesis etc.

May - July 2019

Research Intern, IIT Kharagpur

Inpainting through natural language expressions

Faculty Advisor - Dr. Abir Das

A lot of research has been done in the field of image inpainting, however most of the research work requires drawing the object that needs to be inpainted. My task was to inpaint the object using a corresponding natural language expression. The proposed method is a two-stage architecture where segmentation mask is generated using Text-Image Architecture and inpainting is done using Wasserstein GAN.

Dec 2018 - Jan 2019

Data Analyst Intern, Ernst & Young

Identifying major skill gaps

Majorly, In South Asian countries there is a skill gap between a job seeker (15-24 yr old) and an industrial employee. And a large amount of money is spent by the government and private sector for vocational training. My job was to find major factors that leads to this skill gap and hence reduce the total amount of money spend on vocational and industrial training.

May - June 2018

Deep Learning Intern, Infostretch Corporation

Object Detection and Image Captioning

I worked on Faster RCNN model object detection model for the detection of total number of medicine strip present in a picture.



Projects

Sept 2019 - March 2020

Autocoder

Faculty Advisor - Dr. Mayank Singh

In the recent past, we witness massive progress on the development of code generation systems for domain-specific languages (DSLs) employing sequence-to-sequence deep learning techniques. In this project we specifically experiment with AlgoLisp DSL-based generative models and showcase their extreme dataset bias through the different classes of adversarial examples. We also present a simple transformer based encoder-decoder model that outperforms the all of Algo-Lisp DSL-based baselines. However, consistent with the previous baselines, the proposed model achieves poor performance under adversarial settings.

Dec 2019 - Present

AI for monsoon rainfall prediction

Faculty Advisor - Dr. Udit Bhatiya

Currently, people are using deterministic mathematical models to predict rainfall and for the other related task. Since machine learning have proven to given state-of-the-art results for many different task. My task is to tackle the predictability of monsoon through machine learning algorithms.

Awards

May-2021

Professor Nitish Thakor Scholarship

IIT Gandhinagar

Grant of 1500 USD for overall academic excellence.

April-2021

LaunchPad Fellowship‑21

IIT Gandhinagar

Grant of 2500 USD as pre‑seed funding for startup.

June-2020

Best Research Proposal Award

Virtual, Europe

Won best research proposal award at Eastern European Machine Learning Summer School(EEML-2020).

April-2020

Awarded Financial Grant (EEML‑2020)

Virtual, Europe

Waived registration fees and selection process for EEML‑2021.

Dec-2018

Medalist, 7th Inter IIT Tech Meet

IIT Bombay

Implemented Satellite image segmentation model and came 3rd among all 23 participating IITs.

Feb 2018

Runner Up, Hackathon

Infostretch Corporation

Build Custom Chatbot for the company website. The chatbot give the details about the company's services.



Publications

Blog

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