Ava Kouhana

Ava Kouhana

MS Student @ Stanford ICME (Computational and Mathematical Engineering)


I am an ICME master's degree student at Stanford University. Prior to Stanford, I spent six months conducting research at Harvard under the supervision of Dr. Mengyu Wang, focusing primarily on Computer Vision tasks like Image Segmentation and Vision-Language Models. Before joining ICME, I had the opportunity to work for six months supervised by Stanford Professor Dr. Craig Levin, researching the application of Diffusion Models for image super-resolution.
My research interests primarily revolve around computer vision, deep learning, and generative AI, with a growing interest for 3D modeling and video generation.

Pinned GitHub Projects


Publications



FairSeg

FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling

Yu Tian*, Min Shi*, Yan Luo*, Ava Kouhana, Tobias Elze, Mengyu Wang

International Conference on Learning Representations (ICLR), 2024



FairCLIP

FairCLIP: Harnessing Fairness in Vision-Language Learning

Yan Luo*, Min Shi*, Muhammad Osama Khan*, Muhammad Muneeb Afzal, Hao Huang, Shuaihang Yuan, Yu Tian, Luo Song, Ava Kouhana, Tobias Elze, Yi Fang, Mengyu Wang

Conference on Computer Vision and Pattern Recognition (CVPR), 2024



PET Attenuation

Direct Generation of Attenuation and Scatter Correction of Brain PET Data Using a Conditional Latent Diffusion Model

Ava Kouhana, M. Jafaritadi, G. Chinn, C.S. Levin

IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS MIC), 2024



Super-Resolution Reconstruction

Super-Resolution Tomographic Image Reconstruction Using Latent Diffusion Models

Ava Kouhana, M. Jafaritadi, G. Chinn, C.S. Levin

IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS MIC), 2024

Grants & Awards