Paul Liang, CMU

Paul Pu Liang

Email: pliang(at)cs.cmu.edu
Office: Gates and Hillman Center 8011
5000 Forbes Avenue, Pittsburgh, PA 15213
Machine Learning Department and Language Technologies Institute, School of Computer Science, Carnegie Mellon University

[CV] @pliang279 @pliang279 @lpwinniethepu

I am a fifth-year Ph.D. student in the Machine Learning Department at Carnegie Mellon University, advised by Louis-Philippe Morency and Ruslan Salakhutdinov. I also collaborate closely with Manuel Blum, Lenore Blum, and Daniel Rubin at Berkeley and Stanford. My research lies in the foundations of multimodal machine learning with applications in socially intelligent AI, understanding human and machine intelligence, natural language processing, healthcare, and education. As steps towards this goal, I work on:

  • Foundations of multimodal machine learning: representation, translation, fusion, and alignment of heterogeneous data [foundations, interactions, MultiViz, HighMMT, Brainish, MultiBench, factorized, translation, alignment].
  • Social intelligence: AI that can perceive human behaviors and engage in multimodal interactions in embodied environments [CMU-MOSEI, Social-IQ, sentiment, emotions].
  • Human-centered AI applications in language, vision, speech, robotics, healthcare, and education [mobile health, education].
  • Real-world representation learning: learning fair, robust, interpretable, efficient, and generalizable representations [fairness in language models, fairness in sentence representations, federated learning, robustness, efficiency].

  • My research is generously supported by a Waibel Presidential Fellowship, Facebook PhD Fellowship, and Center for Machine Learning and Health Fellowship, and has been recognized by 3 best-paper awards at NeurIPS workshops and ICMI 2017. I love teaching and advising, and was honored to receive the Alan J. Perlis Graduate Student Teaching Award for co-instructing courses (CMU 11-877, CMU 11-866, CMU 11-777), and organizing workshops (ICCV, NAACL, NeurIPS, ACL) and tutorials (ICML, CVPR, NAACL) on multimodal machine learning. Previously, I received an M.S. in Machine Learning and a B.S. with University Honors in Computer Science and Neural Computation from CMU, where I am grateful for the mentorship of Louis-Philippe Morency, Ruslan Salakhutdinov, Tai Sing Lee, Roni Rosenfeld, and Ryan Tibshirani. I have also been fortunate to spend time at DeepMind, Facebook AI Research, Nvidia AI, Google Research, and RIKEN Artificial Intelligence Project.

    Research opportunities: I am happy to collaborate and answer questions about my research and CMU academic programs. If you are interested, please send me an email. I especially encourage students from underrepresented groups to reach out.

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    (* denotes joint first-authors, see full list here)

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    Some amazing students I've had the pleasure of advising:

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    I have an Erdős number of 3 (Paul Erdős → Giuseppe Melfi → Erik Cambria → Paul Pu Liang).
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