Hello, I’m Aditya!

Thank you for visiting my home page on the internet! My name is Aditya Lahiri, and I am a Masters student at UC San Diego, majoring in Computer Science. Prior to this, I worked at American Express, AI Labs for two years as a Research Engineer. My work revolved around core machine learning(Explainable ML and Ensemble algorithms) and software development(Here is my CodeSignal Assessment score!). I completed my undergraduate studies in Computer Science from BITS Pilani in the beautiful state of Goa.

Research Interests

  • Explainable ML
  • Causal Inference
  • Machine Learning
  • Inductive Logic Programming
  • Ensemble Algorithms
  • Computational Biology

Publications

  • "Accurate and Intuitive Contextual Explanations using Linear Model Trees" - pdf

    at the KDD 2020 Workshop on Machine Learning in Finance

    Aditya Lahiri, N.U.Edakunni

  • "Pitfalls of Explainable ML: An Industry Perspective" - pdf

    at the JOURNE Workshop At MLSys 2021

    Sahil Verma,Aditya Lahiri, John P.Dickerson, Su-In Lee

Projects

  • GRE Visualizer
    Built an interactive graph based tool to visualize synonyms and commonly confused words. The open source tool allows users to try it out on their browser directly using Binder. The tool has been starred and forked by over 50 users.

  • Contributor to Atlan Data Wiki
    Contributed to an online wiki repository on topics related to Data Science and Machine Learning. Amongst other topics, primarily contributed by providing bite sized explanations of the most popular machine learning algorithms.

  • Dealing With Imbalanced Datasets In Machine Learning
    Selected to give a technical talk on handling imbalanced datasets at the PyData conference 2019 held at Microsoft in Times Square, New York.

Experience

September 2021 - Present

Teaching Assistant/Student Researcher

•Building an autograding framework for SQL query evalution as a Teaching Assistant for the Intro to Database Management Course.
•Researching at the intersection of causality and game theory for explainable Machine Learning, under Prof. Babak Salimi.

August 2019 - August 2021

Research Engineer

• Involved in Research and Development of novel methods for Machine Learning Explainability.
• Contributed to a modification of the open source XGBoost algorithm which was being customized for the organisation’s needs.
• Using State Of The Art NLP techniques to automate important business actions efficiently.

May 2019 - July 2019

Data Science Intern

• Data munging,analysis and creation of machine learning and deep learning models to provide valuable insights into the Indian demography by analysing consumer persona and ethnicity at high granularity..

Jan 2019 - May 2019

Student Researcher

• Using Inductive Logic Programming and Meta Interpretive Learning to perform one shot learning. Project in collaboration with TCS Innovation Labs.

Supervisor: Dr. Ashwin Srinivsan
Jan 2018 - May 2018

Undergraduate Researcher

•Developed methodologies to combine Graph theory and Machine learning to understand critical bio-molecular interaction in living organisms.

Supervisor: Dr. Raviprasad Aduri

Education

2021- Present

University of California, San Diego

Masters in Computer Science
2016 - 2019

BITS Pilani, Goa Campus

• B.E. in Computer Science (8.88/10)