About

I am a PhD candidate in Electrical and Computer Engineering at Purdue University and a member of the Robot Vision Lab, under the guidance of Dr. Avi Kak. My research lies at the intersection of Natural Language Processing (NLP) and Computer Vision (CV), focusing on machine learning solutions for multimodal data analysis, with expertise in LLM evaluation, knowledge graph generation, inference, and anomaly detection [NeurIPS’24]. Proficient in Python, PyTorch, and Deep Learning, I also bring strong skills in scientific communication, public speaking, and presentations, enabling me to effectively bridge research and impactful real-world applications.

I have a strong foundation in both theoretical and applied machine learning and am passionate about exploring how AI can unlock insights across diverse domains.

Previously, I contributed to research at the intersection of Computational Neuroscience and AI with Dr. Joe Makin. My work involved applying machine learning and deep learning techniques to decode speech and motion from neural data captured from both human and primate subjects.

In an earlier phase of my career, I explored the fascinating field of Nanophotonics and Electrodynamics, where I combined computational modeling with experimental research. My projects focused on simulating nanoscale systems in solid-state and biological contexts, as well as designing and fabricating nanostructures for applications in sensing and imaging. I am deeply grateful to have been mentored by the remarkable Dr. Naresh Emani, Dr. Jinal Tapar and Dr. Zubin Jacob whose guidance has profoundly shaped my academic and professional journey. Their expertise and support have inspired my passion for research and continue to influence my approach to problem-solving and innovation.

For a detailed overview of my academic and professional journey, you can view my full CV or my condensed resume.

Let’s connect and explore how technology can transform the way we perceive and solve problems!