Welcome!
I am a scientist focused on building AI systems that not only see and understand the world, but remain reliable, understandable, and useful across the diverse ways people actually use them.
My main areas of interest are in machine learning, with a focus on computer vision, natural language processing, robustness, and human-centered AI.
I hold a Ph.D. in Intelligent Systems from the University of Pittsburgh and currently work as a data scientist at PNC Financial Services, where I develop AI/ML solutions for financial applications.
Previously, I worked in the computer vision group with Dr. Adriana Kovashka at the University of Pittsburgh.
Specific research areas include:
- Vision-language modeling
- Training and adaptation strategies for improving representational robustness (e.g., regularization, data augmentation, and contrastive sampling)
- Foundation models
- Data-efficient and parameter-efficient learning
- Object recognition, detection, and image-text retrieval
- AI in multilingual and cross-cultural settings
Recent News
08-2025 I successfully defended my dissertation and completed my Ph.D. Thanks to everyone for the support!
04-2025 I have started working as a Data Scientist at PNC.
09-2024 One paper has been accepted to the International Joint Conference on Natural Language Processing and the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL) 2025.
09-2024 One paper has been accepted to the Empirical Methods in Natural Language Processing (EMNLP) (Short) 2024.
06-2024 I am working this summer as an Applied Scientist Intern at Amazon.
04-2024 One paper has been accepted to the What is Next in Multimodal Foundation Models? Workshop (MMFM) at CVPR 2024.
02-2024 One paper has been accepted to the IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) 2024.
10-2023 One paper has been accepted to the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2024.
04-2023 One extended abstract has been accepted to the CVPR Workshop on Open-Domain Reasoning Under Multi-Modal Settings 2023.
11-2022 One paper has been accepted to the AAAI Workshop on Practical Deep Learning in the Wild 2023.
05-2022 I am working this summer as a machine learning intern at GatherAI.