Experience

  • Autonomous System Research Intern

    • Organization: Nokia Bell Labs

    • Location: Murray Hill, NJ
    • Duration: June 2024 - Present
    • Leveraged LangChain and Prompt Engineering techniques to substantiate LLM planning and reasoning power.
    • Visualized and deployed the multi-agent system using streamlit to interact and demonstrate their capabilities.
    • Engineered test cases and executed experiments on different SOTA LLMs, ensuring high-quality optimization.
    • Skills: Large Language Models (LLMs), LangChain, Prompt Engineering, streamlit, NLP, Git
    • Manager: Dr. Thomas Woo, Research Group Leader - Autonomous Systems Research Department

  • Master's Research

    • Organization: University of Wisconsin-Madison

    • Location: Madison, WI
    • Duration: September 2023 - May 2024 (8 Mos)
    • Ran comprehensive benchmark tests on various LLMs with different configurations on platforms with varying levels of hardware capability.
    • Formulated an RNN-based approach for trajectory prediction using Wifi signal data and historical user data.
    • Skills: Large Language Models, Recurrent Neural Networks, PyTorch, NumPy, pandas, Git
    • Advisor: Dr. Suman Banerjee, David J. DeWitt Professor

  • Associate Engineer - AI/ML

    • Organization: Qualcomm

    • Location: Hyderabad, India
    • Duration: July 2022 - July 2023 (1 Yr)
    • Introduced evaluation frameworks and metrics for ML models to enhance efficiency and accuracy by 10.26%.
    • Ran inference and benchmark tests using SnapDragon Neural Processing Engine, based on OEM requests.
    • Skills: NLP, Python, NumPy, pandas, Docker
    • Manager: Mrs. Archana Patil, Engineer - Staff / Manager

  • Machine Learning Intern

    • Organization: Mad Street Den (Vue.ai)

    • Location: Chennai, India
    • Duration: March 2021 - June 2022 (1 Yr 4 Mos)
    • Developed OCR/NLP-based document processing tool to convert unstructured data for workflow automation.
    • Our efforts reduced document processing time by 37% and achieved an accuracy of 85%.
    • Skills: NLP, CV, Python, PyTorch, Tensorflow, NumPy, pandas, scikit-learn, NLTK, spaCy, OpenCV, AWS
    • Manager: Mr. Anand Chandrasekaran, Founder and CTO

  • Part-Time Undergraduate Research & Teaching Assistant

    • Organization: Bright Academy (Previously Solarillion Foundation)

    • Location: Chennai, India
    • Duration: February 2020 - June 2022 (2 Yrs 5 Mos)
    • Lead the NLP group that worked to translate the video input of a German sign language translator depicting the weather, into cohesive and accurate German sentences.
    • We achieved 98.19% score retention in the ROUGE-L score and 86.65% in the BLEU-4 score, while simultaneously achieving a 30.88% reduction in model parameters when compared to the state-of-the-art model.
    • Collaborated on an NLP project to classify unfair Terms of Service clauses using a two-stage knowledge distillation approach with BERT.
    • Guided 5+ students in research, evaluated assignments and projects in Python and Machine Learning.
    • Oversaw the website development and managed the server for our research group.
    • Wrote bots for posting office hours and creating polls.
    • Skills: Research, NLP, CV, PyTorch, Tensorflow, NumPy, pandas, scikit-learn, NLTK, spaCy, OpenCV
    • Advisor: Mr. Vineeth Vijayaraghavan, Director - Research and Outreach

  • Student Researcher

    • Organization: Sri Sivasubramaniya Nadar College Of Engineering

    • Location: Chennai, India
    • Duration: December 2020 - April 2022 (1 Yr 5 Mos)
    • Posited a novel architecture for Fake News Detection based on Transformer architecture, which considers the title and content of a news article to determine its integrity.
    • Our work performed with an accuracy of 74.0% on a subset of the NELA-GT 2020 dataset. To our knowledge, FakeNews Transformer is the first published work considering both title and content for evaluating a news article.
    • Proposed a robust and cost-effective automatic speech recognition model for the Tamil language leveraging Baidu's Deep Speech architecture. Our work was compared against Google's speech-to-text API, outperforming it by 20%.
    • Skills: Research, NLP, Speech Signal Processing, PyTorch, Tensorflow, NumPy, pandas, scikit-learn, NLTK, spaCy
    • Advisor: Dr. Shahina A - Professor and Dr. Gayathri K S - Assistant Professor, Department of IT