Pengtao Xie

I am looking for highly-motivated PhD and master students to join my group. I am also looking for research interns for  summer.

News

• 2023/9. Two papers are accepted by NeurIPS 2023. 

• 2023/6. Course evaluations are released. ECE269-Winter2022, ECE285-Winter2022, ECE285-Spring2023, ECE175B-Spring2023, ECE269-Winter2021, ECE285-Winter2021

• 2023/5. A recent project. ProteinChat: Towards Enabling ChatGPT-Like Capabilities on Protein 3D Structures

• 2023/5. A recent project. DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

• 2023/5. A recent project. XrayChat: Towards Enabling ChatGPT-Like Capabilities on Chest X-ray Images

• 2023/4. Three papers are accepted by ICML 2023.

• 2023/1. Two papers are accepted by ICLR 2023, including one Notable-Top-5% paper.

• 2023/1. I received the Best Graduate Teacher Award (presented by ECE at UCSD).

• 2022/4. Course evaluations are released. ECE269-Winter2022, ECE285-Winter2022, ECE269-Winter2021, ECE285-Winter2021

• 2020/8. My PhD thesis was selected as a finalist (top 5) for the AMIA Doctoral Dissertation Award.

Current Students

PhD Students and Postdocs

• Caitlin Aamodt (PhD from UCLA)

• Han Guo (from CS at Rice U.)

• Ramtin Hosseini (from ME at UC Berkeley)

• Mingjia Huo (from CS at Peking U.）

• Amirhosein Javadi (from EE at Sharif U. of Tech.)

• Youwei Liang (from CS at SCAU)

• Xinshuang Liu (from CS at Tsinghua U.)

• Sai Somayajula (from EE at IIT Hyderabad)

• Li Zhang (from CSE at Zhejiang U.)

• Ruiyi Zhang (from CS at Peking U.)

Collaborative PhD Students

• Ding Bai (MBZUAI)

• Sang Choe (CMU)

• Nicholas Ho (CMU)

• Blair Jia (UCSD)

• Yingtao Luo (CMU)

• Sazan Mahbub (CMU)

• Shentong Mo (MBZUAI)

• Duy Nguyen (University of Stuttgart)

• Ning Sun (MBZUAI)

• Jiayou Zhang (MBZUAI)

• Shuxian Zou (MBZUAI)

Master Students

• Hongchao Fang

• Yiheng He

• Onkar Litake

• Preyaa Patel

• Shreya Saha

• Abhishek Singh

• Zeyuan Yin

Undergraduate Students

• Shuhang Lin

• Ritvik Gupta

• Yuchen Shen

• Zihan Wang

Past Students

Undergraduate Students

• Ruisi Zhang (2020 --> PhD student at UCSD ECE)

• Matt Hong (2020 --> PhD student at UCSD CSE)

• Jiayuan Huang (2020 --> Master student at CMU CS)

• Jiaqi Zeng (2020 --> Master student at CMU CS)

• Meng Zhou (2020 --> Master student at CMU CS)

• Yuhong Chen (2020 --> Master student at CMU INI)

• Yue Yang (2020 --> Master student at Georgia Tech CS)

Master Students

• Jiachen Li (2020 --> PhD student at UCSB)

• Xuehai He (2020 --> PhD student at UCSC)

Teaching

• ECE285 Deep Generative Models.  Course Evaluations: ECE285-Winter2022, ECE285-Winter2023, ECE285-Winter2021

• ECE269 Linear Algebra and Applications. Course Evaluations: ECE269-Winter2022, ECE269-Winter2021

• ECE175B Probabilistic Reasoning and Graphical Models. Course Evaluations: ECE175B-Spring2023

Publications Since 2020

Google Scholar

Publications Before 2020

• Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, Eric Xing. Generalized Zero-shot ICD Coding. International Joint Conference on Artificial Intelligence (IJCAI 2020).

• Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric P Xing. Adversarial Domain Adaptation Being Aware of Class Relationships. European Conference on Artificial Intelligence (ECAI 2020).

• B. Huang, K. Zhang, P. Xie, M. Gong, E. P. Xing. Specific and Shared Causal Relation Modeling and Mechanism-based Clustering. Advances in Neural Information Processing Systems (NeurIPS 2019).

• K. Xu, M. Lam, J. Pang, X. Gao, C. Band, P. Mathur, F. Papay, A. K. Khanna, J. B. Cywinski, K. Maheshwari, P. Xie, E. P. Xing. Multimodal Machine Learning for Automated ICD Coding. Conference on Machine Learning for Healthcare (MLHC 2019).

• Z.Wang, N.Dong, S.Rosario, M.Xu, P.Xie, and E.P.Xing. Ellipse Detection of Optic Disc-and-Cup Boundary in Fundus Image with Unsupervised Domain Adaption. The IEEE International Symposium on Biomedical Imaging (ISBI 2019).

• P.Xie, W.Wu, Y.Zhu and E.P.Xing. Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis. The 35th International Conference on Machine Learning (ICML 2018) (Long Oral Presentation).

• P.Xie, H.Zhang, Y.Zhu and E.P.Xing. Nonoverlap-Promoting Variable Selection. The 35th International Conference on Machine Learning (ICML 2018) (Short Oral Presentation).

• P.Xie, H.Shi, M.Zhang and E.P.Xing. A Neural Architecture for Automated ICD Coding. The 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018) (Oral Presentation)

• B.Jing, P.Xie and E.P.Xing. On the Automatic Generation of Medical Imaging Reports. The 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018).

• P.Xie, J.Kim, Q.Ho, Y.Yu and E.P.Xing. Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design. Symposium of Cloud Computing (SoCC 2018).

• D.Sachan, P.Xie and E.P.Xing. Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition. Conference on Machine Learning for Healthcare (MLHC 2018).

• X.Liu, K.Xu, P.Xie and E.P.Xing. Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records. NIPS ML for Healthcare Workshop, 2018 (Spotlight Presentation).

• P.Xie, R.Salakhutdinov, L.Mou and E.P.Xing. Deep Conditional Determinantal Point Process for Large-Scale Multi-Label Classification. International Conference on Computer Vision (ICCV 2017).

• P.Xie, B.Poczos and E.P.Xing. Near-Orthogonality Regularization in Kernel Methods. Conference on Uncertainty in Artificial Intelligence (UAI 2017) (Plenary Presentation).

• H.Zhang, Z.Zheng, S.Xu, X.Liang, W.Dai, Q.Ho, Z.Hu, J.Wei, P.Xie, and E.P.Xing. Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters. 2017 USENIX Annual Technical Conference (ATC 2017) (Oral Presentation).

• P.Xie, A.Singh and E.P.Xing. Uncorrelation and Evenness: A New Diversity-Promoting Regularizer. The 34th International Conference on Machine Learning (ICML 2017) (Oral Presentation).

• P.Xie, Y.Deng, Y.Zhou, A.Kumar, Y.Yu, J.Zou and E.P.Xing. Learning Latent Space Models with Angular Constraints. The 34th International Conference on Machine Learning (ICML 2017) (Oral Presentation).

• H.Zhou, J.Li, P.Xie and Y.Zhang. Improving the Generalization Performance of Multi-class SVM via Angular Regularization. The 26th International Joint Conference on Artificial Intelligence (IJCAI 2017).

• P.Xie and E.P.Xing. A Constituent-Centric Neural Architecture for Reading Comprehension. The 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017).

• Y.Zhou, K.Yuan, Y.Yu, X.Ni, P.Xie, E.P.Xing and S.Xu. Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with polynomial functions. Heredity, 2017.

• E.P.Xing, Q.Ho, P.Xie and W.Dai. Strategies and Principles of Distributed Machine Learning on Big Data. Engineering, Transactions of Chinese Academy of Engineering (Engineering 2016).

• P.Xie, J.Kim, Y.Zhou, Q.Ho, A.Kumar, Y.Yu and E.P.Xing. Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting. The 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016). 

• P.Xie, J.Zhu and E.P.Xing. Diversity-Promoting Bayesian Learning of Latent Variable Models. The 33rd International Conference on Machine Learning (ICML 2016) (Oral Presentation).

• E.P.Xing, Q.Ho, W.Dai, J.Kim, J.Wei, S.Lee, X.Zheng, P.Xie, A.Kumar and Y.Yu. Petuum: A New Platform for Distributed Machine Learning on Big Data. IEEE Transactions on Big Data (IEEE BigData 2015).

• P.Xie. Learning Compact and Effective Distance Metrics with Diversity Regularization. European Conference on Machine Learning (ECML 2015) (Oral Presentation).

• P.Xie, Y.Deng and E.P.Xing. Diversifying Restricted Boltzmann Machine for Document Modeling. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015) (Oral Presentation).

• E.P.Xing, Q.Ho, W.Dai, J.Kim, J.Wei, S.Lee, X.Zheng, P.Xie, A.Kumar and Y.Yu. Petuum: A New Platform for Distributed Machine Learning on Big Data. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015) (Oral Presentation).

• P.Xie, D.Yang and E.P.Xing. Incorporating Word Correlation Knowledge into Topic Modeling. The 2015 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2015).

• P.Xie, Y.Pei, Y.Xie and E.P.Xing. Mining User Interests from Personal Photos. The 29th AAAI Conference on Artificial Intelligence (AAAI 2015).

• P.Xie and E.P.Xing. Integrating Image Clustering and Codebook Learning. The 29th AAAI Conference on Artificial Intelligence (AAAI 2015) (Oral Presentation).

• P.Xie and E.P.Xing. Multi-Modal Distance Metric Learning. The 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013) (Oral Presentation).

• P.Xie and E.P.Xing. Integrating Document Clustering and Topic Modeling. Proceedings of the 29th International Conference on Uncertainty in Artificial Intelligence (UAI 2013).

Professional Activities

Area Chairs for:

• ICML 2021, NeurIPS 2021, CVPR 2021, NAACL 2021, ICCV 2021, AAAI 2021, IJCAI 2021

Co-organizer for:

• NeurIPS 2020 workshop "Self-Supervised Learning -- Theory and Practice".

• AAAI 2021 workshop "Trustworthy AI for Healthcare".

• ICLR 2021 workshop “Machine Learning for Preventing and Combating Pandemics”.

Member for:

• Machine Learning for Signal Processing Technical Committee

• ACM, IEEE, AMIA

Program Committee Members or Reviewers for:

• Conferences: ICML (2014, 2018-2019), NIPS (2016, 2018), AISTATS (2017-2019), UAI (2018), ICLR (2019), AAAI (2019), CVPR (2016-2019), ICCV (2015, 2017), ECCV (2016, 2018), ACL (2015-2018), EMNLP (2015), KDD (2015), ECML (2016-2017), ACCV (2016), BMVC (2017)  

• Journals: TPAMI (2018), TKDE (2015-2018), TMM (2016-2017), PLOS ONE (2017-2018), TNNLS (2015-2016, 2018), JASA (2015)  

Selected Awards and Honors

• Finalist (top 5) for AMIA Doctoral Dissertation Award.

• Amazon AWS Research Award. 

• Tencent AI-Lab Faculty Award. 

• Tencent Faculty Award. 

• Innovator Award, 2018 (presented by the Pittsburgh Business Times).

• Google Cloud research credits.

• 1st Place (out of 400+ participating teams) in both Defenses and Targeted Attacks, 3rd Place in Untargeted Attacks, in NIPS Adversarial Vision Challenge, 2018.

• Siebel Scholarship, 2014 (85 graduate students from around the world).

• National Scholarship of China, 2009.

• National First Prize in China Undergraduate Mathematical Contest of Modeling, 2008.

• Goldman Sachs Global Leader Scholarship, 2008 (150 undergraduate students from around the world).

Recent Invited Talks

• Machine Learning for Medical Decision Support

  • Nov 2019, Department of Biomedical Informatics, University of Pittsburgh

  • Oct 2019, AI NEXTCon Developer Conference

  • Apr 2019, New York University

  • Apr 2019, University of Massachusetts Amherst

  • Mar 2019,  University of California San Diego

  • Feb 2019, Columbia University

  • Feb 2019, Johns Hopkins University

  • Feb 2019, University of California Los Angeles

  • Jan 2019, University of Wisconsin-Madison