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Master of Computational Data Science

Carnegie Mellon University

• Select Courses
  • Large Language Models
  • Multimodal Machine Learning
  • Deep Reinforcement Learning
  • Introdution to Deep Learning
  • Introduction to Machine Learning (PhD)
  • Cloud Computing
  • Foundations of Computational Data Science
• Academic Services
  • Reviewer for EMNLP 2023
  • Core Committee Member, LTI Computing Insfrastructure

Bachelor of Computer Science and Engineering

Vellore Institute of Technology, Vellore

• Select Courses
  • Machine Learning
  • Artificial Intelligence
  • Image Processing
  • Neural Networks and Fuzzy Logic
  • Parallel and Distributed Computing
  • Virualization
  • Data Structures and Algorithms
  • Operating Systems
  • Databases
  • Networks and Communications
  • Calculus
  • Linear Algebra
  • Statics and Probability
  • Discrete Mathematics and Graph Theory
  • Theory of Computation and Compiler Design
• Extracurricular Experiences
  • Researcher at ACM-VIT
  • Core Committee Member, SEDS-VIT
  • Founding Member at Team Qubits
• Achievements
  • G. D. Naidu Young Scientist Award, 2020
  • Sir. M. Visvesaraya Award, 2019
  • Secured 1st position in 7 national hackathons
  • Ranked in Top 3 teams at 3 national hackathons
  • Secured 2 patents

Research Scientist Intern

Abacus.AI

• Conceptualized and led research on exploring linear properties of LLM adapters (soft prompts, LoRAs)
• Invented a novel learning algorithm to approximate a linear combination of pre-trained LoRAs to enhance generalization and multi-task performance
• Collaborated with researchers and developed new metrics for debunking staleness in popular NLP benchmarks due to memorization in LLMs

Graduate Research Assistant

Robotics Institute, Carnegie Mellon University

• Led and mentored a team of 6 research assistants for increasing generalization and robustness of computer vision tasks (segmentation, classification and tracking) for robotic e-waste disassembly at Biorobotics lab
• Devised a multimodal deep neural network architecture for semantic segmentation
• Developed a new loss function robust to label noise, improve baseline performance by 15% IoU and generalization 20% IoU
• Implemented an out-of-distribution detection algorithm achieving 98.6% accuracy

Research Intern

SketchX Lab, University of Surrey

• Invented a novel active learning algorithm for fine-grained cross-modal instance-level retrieval tasks,
• Increased mean top1 accuracy by 5% over state-of-the-art technique, published a first-authored paper to a top-tier conference (BMVC).

Senior Technology Associate

Morgan Stanley

• Developed a distributed deep learning framework for real-time failure prediction (time-series forecasting) and detection;
• Led to 5000x reduction in failure detection time, enabled prediction of batch job failures with 94% accuracy, awarded best contributor to global firm resiliency out of 5000+ nominees.
• Pioneered graph database as a service to enable 100x faster search and data lineage applications
• Rsearched and developed a domain-agnostic recommendation engine (using large-scale and distributed training of deep learning models) powered by graph databases, recognized as most innovative firmwide project.

Data Scientist Intern

Locale.AI

• Developed a novel clustering algorithm for human activity discovery from raw geo-spatial ping data using semi-supervised representation learning, enabled automated discovery of 18% new business areas from previously unused data.
• Productionized and scaled a timeseries anomaly detection framework using temporal convolutional networks (TCN), increased requests throughput by 6x, helped 10 companies in reliably predicting vehicle vandalism and trip delays.

Machine Learning and Web Development Intern (Part-Time)

S4S Technologies

• Worked on creating the entire internal operations dashboard for the team as well as a computer vision solution to solve food quality assurance problem.

Summer Intern

Sigmaways Inc

• Worked on AI based portfolio recommendation engine using LSTM based predictor and Meta-Heuristic Optimiser. Also, built a chatbot interface to the service.

Software Engineering Intern

Nova (P & D)

• Modernized the existing software capabilities and introduce a new method for speedy billing.
• Worked on Data Analytics and Software Development to create a new Edge-Billing system which allowed multiple working staffs to finalise a bill on their smartphones itself.
• Allowed multiple simultaneous billing, hence speeding up the process and developed software features which allowed better insights into sale and purchase.

AI on the Beach

• Developed a data visualization library that can render over 10 GB of data into a single animated scatter plot under minutes.

• G. D. Naidu Young Scientist Award

• Sir. M. Visvesaraya Award