Machine Learning Engineer

• Jun 2023 - Present

Computer Vision Intern

• Jun 2022 - Sep 2022

Optimized MaSS, a data transformation technique using a generative model, to suppress a selected set of attributes while simultaneously preserving the rest, for downstream machine learning tasks. Submitted at ICML 23. Implemented batch processing and data parallelism, resulting in a 250x increase in computation speed Optimized MaSS, a data transformation technique using a generative model, to suppress a selected set of attributes while simultaneously preserving the rest, for downstream machine learning tasks. Submitted at ICML 23. Implemented batch processing and data parallelism, resulting in a 250x increase in computation speed

Computer Vision Analyst

• Jan 2022 - Jun 2022

Implemented Self-supervised learning on Pre-Clinical Tissue slides to compensate for lack of labelled data in Digital Pathology. Reduced the need for annotated data by 90% in downstream tasks using this pre-trained network. Implemented Self-supervised learning on Pre-Clinical Tissue slides to compensate for lack of labelled data in Digital Pathology. Reduced the need for annotated data by 90% in downstream tasks using this pre-trained network.

CS Research Mentorship Program Fellow

• Sep 2021 - Dec 2021

Successfully completed 2021B class of Google's Computer Science Research Mentorship Program (CSRMP), where I had the opportunity to brainstorm on cutting-edge research to improve Google Meet video quality under the guidance of experienced mentors from Google. Successfully completed 2021B class of Google's Computer Science Research Mentorship Program (CSRMP), where I had the opportunity to brainstorm on cutting-edge research to improve Google Meet video quality under the guidance of experienced mentors from Google.

Research Fellow

• Feb 2021 - Oct 2021

Advised by Professor Sarah Ostadabbas. Identified a domain gap in facial detection algorithms for infants and laid the groundwork in the early prediction of developmental disorders. Our work was recognized with Best Scientific Paper Award at ICPR 22 Advised by Professor Sarah Ostadabbas. Identified a domain gap in facial detection algorithms for infants and laid the groundwork in the early prediction of developmental disorders. Our work was recognized with Best Scientific Paper Award at ICPR 22

Teaching Assistant

• May 2021 - Aug 2021

Served as TA to professor Drew van der Poel for Algorithms course for a class of 80+ students. Conducted one-on-one tutoring during Office Hours. Prepared and delivered coding question on HackerRank. Served as TA to professor Drew van der Poel for Algorithms course for a class of 80+ students. Conducted one-on-one tutoring during Office Hours. Prepared and delivered coding question on HackerRank.

Software Engineer II

• Aug 2019 - Dec 2020

Spearheaded development and design of BOT Onboarding Platform - a Platform-As-A-Service for chatbots at an enterprise level; Sustaining over 40 chatbots supporting 1000+ users in various segments at Dell across the globe.Consulted 60+ teams to adopt on-premise chatbot solutions.Collaborated with SMEs to address problems in Digital Supply Chain using NLP and ML techniques.Recognized with first-ever GameChanger Award.

Software Engineer I

• Jul 2017 - Aug 2019

Built an app assistant for global inventory of Dell's Supply Chain that helps in resolution of all issues within this space. Intent and entities are extracted from user query using NLU engine and an action is triggered. This was the first chatbot to be integrated with Skype for Business within Dell.Part of IT Patent Committee FY19, Quality Engineering Org ML/AI InitiativeGLOVIA Inventory

Research Intern

• Jan 2017 - Jun 2017

Worked on Automatic Grading of Computer Programs: A Machine Learning Approach (published ICMLA 2013) and extended the research to multiple languages. This involved parsing code, extracting informative features and determining closeness of logic using machine learning based algorithms. Further implemented a parse tree based approach to extract features from uncompilable code snippets. Worked on Automatic Grading of Computer Programs: A Machine Learning Approach (published ICMLA 2013) and extended the research to multiple languages. This involved parsing code, extracting informative features and determining closeness of logic using machine learning based algorithms. Further implemented a parse tree based approach to extract features from uncompilable code snippets.

Founding Member

• Nov 2014 - Jul 2016

Founding Member of Shiv Nadar University's ACM Chapter. Organized trainings to motivate students to participate in ACM ICPC(International Collegiate Programming Contest) and GSoC(Google Summer of Code) Organized various events to encourage students towards programming Organized and mentored Hackthon, Movie Screenings Founding Member of Shiv Nadar University's ACM Chapter. Organized trainings to motivate students to participate in ACM ICPC(International Collegiate Programming Contest) and GSoC(Google Summer of Code) Organized various events to encourage students towards programming Organized and mentored Hackthon, Movie Screenings

Intern

• Jun 2015 - Jul 2015

Project: Television Recommendation System Used Machine Learning techniques, to improve user experience for their customers. Applied Collaborative filter using similarity based on user and content Dataset used: Movielens Technologies Used: Python, numpy, scikit for various calculations, and wxpython for gui Project: Television Recommendation System Used Machine Learning techniques, to improve user experience for their customers. Applied Collaborative filter using similarity based on user and content Dataset used: Movielens Technologies Used: Python, numpy, scikit for various calculations, and wxpython for gui