Experience
May 2025 – August 2025
Machine Learning Engineer Intern
Pervaziv AI, Pittsburgh, PA
August 2023 – May 2024
Software Developer (Cloud Ops)
Hewlett Packard Enterprise, Bangalore, India
January 2023 – July 2023
Software Development Intern
Hewlett Packard Enterprise, Bangalore, India
July 2022 – December 2022
Machine Learning Intern
PESU Venture Lab, Bangalore, India
Education

Carnegie Mellon University

Master of Science in Artificial Intelligence Engineering
GPA: 3.73/4.0 | August 2024 – December 2025

PES University

Bachelor of Technology in Computer Science Engineering
GPA: 8.51/10 | August 2019 – May 2023
Projects

Multimodal Document Question-Answering on Research Papers

Enhanced performance of multimodal document QA on scholarly articles by fine-tuning Qwen-VL-7B for +15% QA accuracy, fine-tuned CLIP to boost image retrieval accuracy by 12%.

Qwen-VL-7B CLIP Multimodal AI Document QA

Reward Model guided Slide Generation

Trained SmolVLM-500M as a reward model with self-refinement and inference-time scaling leading to a 28% performance gain on AutoPresent.

SmolVLM-500M Reward Models Self-Refinement AutoPresent

Exploring Impact of Code in Pre-training

Implemented continuous pretraining of GPT-medium on code data, demonstrating a ~5-7% improvement across popular LLM benchmarks available on Eleuther AI's lm-eval-harness.

GPT-medium Code Generation Pre-training LLM Benchmarks
Publications & Patents

Attention Based Evolutionary Approach for Image Classification

Achieved SOTA accuracy on CIFAR-10 with 50% fewer generations than baseline NAS (Neural Architecture Search).

Neural Architecture Search CIFAR-10 Evolutionary Algorithm Image Classification
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System And Method for Clustering and Categorizing Large Datasets

Patented system combining text embeddings with dimensionality reduction and clustering techniques; facilitated efficient document retrieval and categorization for deriving business insights.

Patent Text Embeddings Clustering Document Retrieval

Automated Workflow for Deepfake Detection

Deployed bi-directional LSTM API with 98% accuracy; slashed parameters by 100x for efficient deepfake detection.

Deepfake Detection LSTM API Deployment Computer Vision
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