People
(Faculty) Members of the UCSD NLP Group
Prithviraj Ammanabrolu
CSE 4134
Lianhui Qin
CSE 4124
Ndapa Nakashole
CSE 4108
Zhiting Hu
HDSI 442
Julian McAuley
CSE 4102
Jingbo Shang
CSE 4104 / SDSC 211E
Hao Zhang
HDSI
CSE 4134
Prithviraj (or Prithvi or Raj) Ammanabrolu is an Assistant Professor in CSE and directs the PEARLS Lab. His research group lives at the intersection of NLP, Reinforcement Learning, and Embodied AI: focusing on how humans and machines can collaborate more efficiently with machines by having them learn from feedback, human or environmental. He is currently recruiting Phd Students in the 2023-24 application cycle!
CSE 4124
Lianhui Qin is an Assistant Professor in CSE. Her research interests lie in natural language processing and machine learning, especially commonsense reasoning in text and conversation generation. She is currently recruiting Phd Students in the 2023-24 application cycle!
CSE 4108
Ndapa Nakashole is an Associate Professor of Computer Science focused on Artificial Intelligence and NLP. Before UCSD, she was a postdoctoral fellow in the Machine Learning department at Carnegie Mellon University. She obtained her PhD from the Max Planck Institute for Informatics, and Saarland University. Her dissertation was awarded the Otto Hahn Medal by the Max Planck Society. Her proposed work for 2022-2027 has been awarded an NSF CAREER award. She is the founder of Okalai, an educational and outreach project that introduces Artificial Intelligence to young people in Namibia, and other African countries. She is not currently accepting new students.
HDSI 442
Zhiting Hu is an Assistant Professor in Halicioglu Data Science Institute at UC San Diego. He received his Bachelor’s degree in Computer Science from Peking University in 2014, and his Ph.D. in Machine Learning from Carnegie Mellon University in 2020. His research interests lie in the broad area of machine learning, artificial intelligence, natural language processing, and ML systems. In particular, he is interested in principles, methodologies, and systems of training AI agents with all types of experience (data, symbolic knowledge, rewards, adversaries, lifelong interplay, etc), and their applications in controllable text generation, healthcare, and other application domains. His research was recognized with best demo nomination at ACL2019 and outstanding paper award at ACL2016. He is currently accepting PhD students!
CSE 4102
Julian McAuley is a Professor at UC San Diego, where he works on applications of machine learning to problems involving personalization, and teaches classes on personalized recommendation. He likes bicycling and baroque keyboard. You can find out more about his group here. He is currently accepting students!
CSE
Taylor Berg-Kirkpatrick is an Associate Professor in the Department of Computer Science and Engineering at the University of California, San Diego. His research group (the BergLab) works on natural language processing and machine learning, focusing on unsupervised methods for deciphering hidden structure. They develop techniques for analyzing various kinds of human data, including natural language – but also diverse sources like early modern books, handwritten text, historical ciphers, and music. He is not currently accepting new students.
CSE 4104 / SDSC 211E
Jingbo Shang is an Assistant Professor at the Computer Science and Engineering Department and Halicioglu Data Science Institute at the University of California, San Diego. His research focuses on data mining, natural language processing, and machine learning methods with minimum human effort and their applications. He obtained his Ph.D. from the University of Illinois at Urbana-Champaign in 2019 and his B.E. from Shanghai Jiao Tong University in 2014. His research has been recognized by many prestigious awards, including SIGKDD Dissertation Award Runner-up in 2020, Google Research Scholar in 2021, and NSF CAREER award in 2023. He is currently accepting students!
HDSI
Hao Zhang studies the intersection area of machine learning and systems. He is equally interested in designing strong, efficient, and secure machine learning models and algorithms, and in building scalable, practical distributed systems that can support real-world machine learning workloads. Recently, he has developed open models and systems to democratize the access of Large Language Models (LLMs). He also co-founded LMSYS Org.