Hi, Iām Hani Alomari š
I'm a Ph.D. candidate in Computer Science at Virginia Tech, advised by Dr. Chris Thomas, and a recipient of the Amazon Fellowship. My research sits at the intersection of computer vision and natural language processing: I study how vision–language models understand, evaluate, and retrieve images that admit more than one valid interpretation, with the goal of building systems that judge visual content from diverse human perspectives and give interpretable, actionable feedback. I also build agents that map rooms from echoes alone, without cameras or lidar. My work has appeared at CVPR, ACL, EMNLP, ECCV, and NeurIPS.
Research Interests
News
Oct '26Submitted papers to ICLR 2027 and ACL Rolling Review
Aug '263 papers accepted to EMNLP 2026 (Main), one receiving a SAC Highlights Award
Aug '26Received the Amazon Fellowship (Amazon–Virginia Tech Initiative, 2026–2027)
Aug '26Wrapped up my ML Engineer internship at Adobe in San Jose, working on image-quality evaluation
Jun '26Part-level visual grounding paper accepted to ECCV 2026
May '25MaxMatch accepted to ACL 2025 (Main)
Selected Publications

Maximal Matching Matters: Preventing Representation Collapse for Robust Cross-Modal Retrieval

JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images

ENTER: Event-Based Interpretable Reasoning for VideoQA

