Home
Hello, I'm Adith
Ph.D. Student | Machine Learning & Cloud Systems
I am a Ph.D. student in Computer and Information Technology at Purdue University, specializing in Natural Language Understanding (NLU). My research explores bias, fairness, and explainability in large language models, along with practical applications of machine learning in cloud-scale and IoT systems. I completed my M.Sc. in Computer Science at New York University with a 3.97/4.0 GPA, where I conducted research in applied machine learning for wind energy simulations and served as a Teaching Assistant for graduate and undergraduate Machine Learning courses.
In industry, I have worked as a Cloud ML Engineer Intern at Rheem Manufacturing, where I architected large-scale data pipelines (AWS S3 → Logstash → Elasticsearch) handling 100M+ daily records, built predictive models for IoT-driven energy optimization, and reduced processing latency by 30%. At Unique World Robotics, I designed precision agriculture ML models with 97% accuracy and deployed cost-efficient real-time APIs on AWS. My work bridges research and engineering, with the goal of creating scalable, transparent, and impactful AI systems.
Education
Purdue University
PhD in NLP
Specializing in Natural Language Processing (NLP) with a focus on bias, fairness, and explainability in large language models. My research aims to develop more transparent, reliable, and trustworthy AI systems, exploring how advanced language models can be evaluated, fine-tuned, and applied responsibly across real-world domains.
New York University
Masters in Computer Science
Completed advanced coursework in Machine Learning, Deep Learning, Computer Vision, Operating Systems, and Java Programming, complemented by a Marketing elective at NYU Stern that broadened my perspective on the intersection of technology and business. Alongside my studies, I gained industry experience as a Cloud Engineer Intern, where I worked on deploying APIs, optimizing infrastructure, and building scalable, data-driven solutions.
National Institute Of Technology,Warangal
Bachelor Of Technology-Computer Science
Studied at the National Institute of Technology Warangal—one of India’s highly competitive engineering institutions—where I completed rigorous coursework in Cloud Computing, Data Science, Data Mining, Distributed Systems, and Database Management Systems (DBMS). My bachelor’s thesis centered on developing a review-based group recommender system using deep learning techniques, aiming to enhance user recommendations through advanced AI methodologies.
Professional Highlights
ML Engineer
Rheem Manufacturing May 2024-May 2025
At Rheem Manufacturing, I developed Python-based RESTful APIs with FastAPI handling 10,000+ daily requests and deployed a self-managed Elasticsearch stack, improving data retrieval speed by 40%. I engineered real-time analytics pipelines integrating AWS S3 for large-scale data ingestion and built ML models for predictive maintenance and energy optimization, improving anomaly detection accuracy for connected devices. These contributions streamlined large-scale data workflows and supported production deployment of intelligent analytics solutions.
Software Engineer Intern
Alpha Data Dubai,UAE May 2022-Aug 2022
At Alpha Data, I automated manual workflows by developing RPA bots, reducing operational effort by 80%. Using Python and UIPath, I streamlined repetitive tasks, enhancing productivity by 30%.
ML Engineer
Unique World Robotics May 2021-Aug 2023
Built an ML algorithm for crop pattern prediction with 97% accuracy, leveraging PyTorch and TensorFlow with DHT11 sensor data. Deployed the solution on AWS EC2 and S3, reducing infrastructure costs by 30%.* Created RESTful APIs to streamline IoT data flow to cloud storage, increasing solution adaptability.
Academic Experience
Research Assistant
Sep 2024- May 2025
I am contributing to the OpenFAST software development on the computer science side, focusing on enhancing simulation capabilities for offshore wind energy systems. My role involves optimizing and integrating computational models to improve the performance of wind turbines in dynamic ocean environments. By working with complex codebases and simulations, I’m helping drive innovations in renewable energy through advanced software solutions.
Course Assistant(ML)
Sep 2024-May 2025
As a course assistant for both graduate (CS-GY 6923) and undergraduate (CS-UY 4563) Machine Learning courses, I assist in preparing course materials, grading assignments, and providing support to students during office hours. I collaborate with professors to ensure students grasp key concepts in machine learning, deep learning, and algorithmic problem-solving. Additionally, I help facilitate discussions, explain complex topics, and guide students through hands-on coding exercises and projects.
Undergraduate Research Assistant
Aug 2022-Aug 2023
As a research assistant, I developed a review-based group recommender system using deep learning techniques, including CNN and attention mechanisms. My research aimed to improve recommendation accuracy by leveraging user reviews, focusing on group decision-making dynamics. This work involved extensive experimentation with neural networks, data preprocessing, and model optimization, contributing to advancements in personalized recommendation systems.
If you're interested in collaborating on cutting-edge technology, or if you just want to say hello, feel free to reach out!