Zhiqiang Tao - Featured Faculty 2024

Dr. Tao leads his research group to study cutting-edge AI techniques in vision-language (VL) domains, with a particular interest in large language/multimodal models (LLMs/LMMs), and has applied their research across biomedical, healthcare, computational imaging, and AI education. Recent projects from his group include: 1) reliable large vision-language understanding that explores visual reasoning in developing LLMs/LMMs to mitigate object hallucination and manage over-long contexts; 2) uncertainty quantification in hybrid models, bridging the gap between lab simulation and real-world measurements; and 3) robust sparse network training – advancing methods for higher inference efficiency through optimization on bit, weight, and model levels. In 2024, Dr. Tao mentored PhD students and collaborated on more than 15 publications in top-tier AI conferences and journals, such as NeurIPS, CVPR, ECCV, KDD, WWW, EMNLP, NAACL, IEEE TPAMI, IEEE TKDE, and Briefings in Bioinformatics.

Dr. Tao earned his Ph.D. degree from Northeastern University in 2020. He was a former research intern with Adobe, CA, and Alibaba’s DAMO academy, WA. He has published over 60 papers in peer-reviewed journals and conferences, including IEEE TPAMI, TNNLS, TIP, TCYB, TKDD, NeurIPS, ICLR, CVPR, ICCV, ECCV, KDD, SIGIR, WWW, EMNLP, NAACL, AAAI, IJCAI, etc. He currently serves as Associate Editor of IEEE TCSVT and Neurocomputing and has served as reviewers and (senior) PC members for prestigious journals and international conferences. He won the 3rd place award in KDD Cup AutoML track in 2019 and received the Ciocca Center Research Award from Santa Clara University in 2021. His research interests lie in pursuing reliable and efficient AI by interweaving machine learning, deep learning, and computer vision.

Zhiqiang Tao
Assistant Professor
School of Information
Golisano College of Computing and Information Sciences