I am a PhD candidate at the Ohio State University working as a research associate at the Photogrammetric Computer Vision Lab (PCVLab). I am advised by dr. Alper Yilmaz. My research interest includes Generative AI and Computer Vision. I am currently doing an internship at Path Robotics Inc as a computer vision researcher.
Research Journey: I have devoted my research to exploring advanced methods for the interpretation and generation of complex visual data. I began by investigating 3D image understanding, focusing on segmentation and classification techniques that capture nuanced spatio-temporal relationships in volumetric data. Leveraging insights gained in representation learning, I then turned my attention to diffusion-based generative models, demonstrating how even simple sketches can be transformed into high-fidelity images. More recently, I have extended these generative approaches to incorporate 3D data, developing ways to condition the diffusion process on geometric information for faithful 2D renderings of 3D objects. While these efforts address distinct challenges, they converge on a shared goal: pushing the boundaries of deep learning for richer, more versatile visual representations.
I am actively looking for ML/AI full-time research positions. I am immediately available after May 5th and will graduate by the end of summer 2025.
KnobGen: Controlling The Sophistication Of Artwork In Sketch-Based Diffusion Models
SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation
A Probabilistic-based Drift Correction Module for Visual Inertial SLAMs