About me

I’m Aditya Kulkarni, a passionate Computer Science graduate student at the University of Texas at Dallas, where I blend my deep love for machine learning and artificial intelligence with real-world applications in robotics and big data.

Current Focus:

  • Machine Learning Intern at UT System, working on exciting projects involving LLMs, RAG systems and NLP
  • Application of ML in computer vision systems for robotics
  • Delving into the realm of cloud computing, with a particular focus on AWS

Projects

Current Research: Application of computer vision and ML based object detection and tracking in robotics


  • 2D Deterministic Path-based Dynamic Object Grasping

    Grasping of Linearly Moving Objects Using a Robotic Manipulator Computer vision-based robotic system utilizing OpenCV and ROS for real-time detection, tracking, and grasping of moving objects.

    Python, PyBullet, ROS, Gazebo, OpenCV

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  • News Bias Analysis on Realtime Reddit Posts

    Real-time news classification and sentiment analysis pipeline using Apache Kafka, Spark Structured Streaming, and DistilBERT, processing 50 articles/minute with 83% bias classification accuracy.

    Spark Streaming, Pyspark, Kafka, Kibana

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  • InvestAid: An AI-powered Investment Dashboard

    NLP-driven investment advisory system leveraging Spacy, PyTorch, and TensorFlow for sentiment analysis and topic modeling of financial data with 85% classification accuracy.

    NLP, Topic Modelling, Sentiment Analysis

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  • Language Translation Using RNN using BPTT algorithm

    NumPy-only implementation of a sequence-to-sequence RNN model for language translation, featuring custom BPTT algorithm and optimizers for competitive accuracy.

    Python, Encoder-Decoders, Numpy

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  • Vehicle Survelliance System using Licence Plate Recognition

    YOLOv3-based license plate recognition system with OCR, achieving 95% capture rate and 3-second feedback time for unauthorized vehicle detection.


    Object Detection and Tracking, OCR, YOLO

    Learn More

Work Experience

Machine Learning Intern

The University of Texas System, University Lands

June 2025 - Current
  • Developing a RAG System for queries documents
Data Science Co-op

Boehringer Ingelheim

Janaury 2025 - May 2025
  • Developing a GPT-4-based framework to classify vendors into nine service categories, including retail and mail-order pharmacies.
  • Developed a Streamlit-based web application to automate the scraping and analysis of medical entity websites, enabling efficient content extraction and structured data processing.
  • Compared various prompting methods like chain-of-thought and observed behavior of LLMs on different structures of prompts like JSON, Markdown etc., and improved the accuracy by up to 8%.
  • Designed and implemented an evaluation framework leveraging the LLM-as-a-judge method with deepeval, ensuring robust assessment of classification accuracy and model performance.
  • Created a comprehensive dashboard to track and visualize evaluation history, providing actionable insights and supporting continuous improvement of the classification system.
  • Contributed to MLOps initiatives, including deployment and management of machine learning models on OpenShift, ensuring scalable and reliable model serving.
Graduate Research Assistant

HBS Lab, UTD

August 2024 - December 2024
  • Engineering a ResNet50-based object detection system for aquatic animals, aiming to develop a autonomous tracking system in challenging underwater conditions.
  • Conducted in-depth literature review of 25+ articles on state-of-the-art underwater robotics and vision tracking systems.
  • Collaborated with HBS Lab researchers to advance ML vision capabilities for underwater robot navigation.
SDET-1

Pubmatic Inc

April 2021 - June 2023
  • Implemented Python-based automation for functional test cases, slashing execution time by 80%.
  • Pioneered integration of generative AI tools like ChatGPT, optimizing code writing and reducing development time by 10%.
  • Spearheaded test plan design for Adserver product, maintaining a post-release defect rate below 2%.
  • Led end-to-end testing for high-priority, high-revenue projects serving 500+ global clients.
  • Actively participated in feature design processes, enhancing code stability and reliability.
  • Conducted rigorous code reviews to maintain quality and ensure adherence to best practices.
R&D Intern

PTC India

September 2020 - March 2021
  • Automated 100+ UI test cases using Java and Selenium, earning recognition through a special efforts award.
  • Maintained and executed a robust suite of 1000+ test cases daily using Jenkins, improving overall stability.
  • Developed a Flask-based dashboard for real-time tracking and monitoring of the testing process.
  • Collaborated with cross-functional teams to optimize test automation and quality assurance processes.
  • Gained hands-on experience in test automation and process optimization within a dynamic R&D environment.
  • Demonstrated commitment to efficiency and quality assurance through innovative automation solutions.

Education

MS Computer Science

University of Texas at Dallas

GPA: 3.74

August 2023 - December 2025(Expected)

  • Independent researh at HBS Lab: ML based object tracking system for underwater robots
  • Data Structures and Algorithms
  • Design and Analysis of Algorithms
  • Database Design
  • Artificial Intelligence
  • Machine Learning
  • Recent Advances in Computer Science- Software Engineering for ML Systems
  • Big Data Management and Analytics
  • Introduction to Robot Manipulation and Navigation
  • Natural Language Processing

BE Computer Science

Savitribai Phule Pune University

GPA: 3.70

August 2017 - May 2021

Skills and Interests


  • Python

  • ML

  • NLP

  • Data Engineering

  • Computer Vision

  • Machine Learning & AI

    Machine Learning Algorithms
    Large Language Models (LLMs)
    RAG development
    PyTorch
    Hugging Face
    Scikit-learn
    NLTK
    Keras
    TensorFlow
    Deep Learning
    Computer Vision
    Natural Language Processing (NLP)
    Object Detection and Tracking

    Domain-Specific Knowledge

    Data Science Methodology
    Data-Driven Insights
    ETL and ELT Design
    Software Engineering

  • Big Data & Data Engineering

    Apache Spark
    Apache Kafka
    Databricks
    Apache Hive
    Apache Airflow
    HDFS
    Spark SQL
    Structured Streaming

    Data Analysis & Visualization

    Pandas
    Kibana
    Matplotlib
    Plotly
    Seaborn
    Logstash

    Testing & Quality Assurance

    Selenium
    Test Automation
    PyTest
    API Testing

  • Programming Languages

    Python (proficient)
    PySpark (proficient)
    C++

    Databases

    MongoDB
    MySQL
    Elasticsearch

    DevOps & Cloud

    Docker
    Jenkins
    Git
    Kubernetes
    Linux
    LXC (Linux Containers)

    Other Technical Skills

    OCR (Optical Character Recognition)
    Time Series Analysis

Certifications


  • IBM Data Science Professional Certificate

    Earned the IBM Data Science Professional Certificate, a rigorous 10-course program covering essential skills in Python, SQL, data analysis, visualization, and machine learning, culminating in hands-on projects using industry-standard tools like Jupyter Notebooks and IBM Watson Studio.

    Learn More

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