Master's in Computer Vision and 5+ years of computer vision industry experience.
Expertise in MLLMs, training, finetuning LLMs, stable diffusion models, LoRA
Expertise in object detection, image segmentation, and facial recognition using OpenCV and YOLO.
Proficient in CNN and RNN architectures with TensorFlow and PyTorch for real-world applications.
During my master's, I gained hands-on experience applying research methodologies, exploring novel ideas, and leveraging HPC resources to train/eval large-scale models.
Skilled in classical techniques for enhancement, restoration, and feature extraction.
Experience deploying ML models and APIs using Azure AI and Cognitive Services.
Use Multi-Modal Large Language Models for generating DSG, zero-shot as well as finetuning
Distilled DINO models to smaller efficientnets and VITs for efficient inference.
Built a real-time customer behavior analysis system using YOLO and OpenCV, preventing self checkout theft.
EEG research is my passion. I'm resrarching how we can interpret our brain singals that can read our thoughts and visulize our dreams. I have developed algorithms to convert EEG signals into visual representations for brain-computer interfaces.
Implemented a drunk and drowsiness alert system for long route drivers for monitoring and safety purposes.
Center for research in computer vision @UCF | May 2024 - Jan 2025
Neurosymbolic AI based approach to generate Dynamic Scene Graph from videos using Off-the-shelf MLLMS(Multi-Modal Large Language Models)
UCF College of Medicine | Dec 2023 - Apr 2024
Designed CV algorithm to perform angle measurement of MRI data(DICOMs) for the bone alignment using Segment Anything Model(SAM) + Image Classifier Heads
Tata Consultancy Services(TCS) | June 2018 - June 2023
Over my five years at TCS, I had the opportunity to take on diverse roles and contribute to various projects, including leading a team of two in developing computer vision solutions. This experience laid a strong foundation in software engineering and corporate best practices, while also exposing me to real-world challenges in computer vision.
University of Central Florida | August 2023 - May 2025
Focused on advanced computer vision techniques and emerging research, bridging theory with real-world applications.
Proposed a novel approach for dynamic scene graph generation using off-the-shelf multi-modal large language models (MLLMs), outperforming state-of-the-art methods at Top-1, Top-5, and Top-10 accuracy while effectively balancing the precision-recall tradeoff.
Developing novel algorithms to transform brain activity into actionable visual data, with applications in neuroscience and human-computer interaction.
I'm open to opportunities and collaborations in computer vision and AI. Reach out to discuss ideas or projects!