Chuan–Sheng (CS) Foo

I lead a research group at the Institute for Infocomm Research (I2R), A*STAR, focusing on data-efficient deep learning. Our work is inspired by applications in healthcare and manufacturing where collecting large, well-annotated datasets is often time and cost-prohibitive due to the need for careful expert labelling.

I earned a BS ('08), MS ('12) and PhD ('17) in Computer Science from Stanford, where I had the privilege to work with Professors Anshul Kundaje, Daphne Koller, Andrew Ng and Serafim Batzoglou on machine learning and deep learning for biology. I took a year off during my PhD to work for Counsyl, where I developed software (variant calling and LIMS integration) for clinically validated sequencing-based genetic tests.

• Semi-supervised Audio Classification with Consistency-Based Regularization

  INTERSPEECH (2019)

  Kangkang Lu, Chuan-Sheng Foo, Kah Kuan Teh, Tran Huy Dat, Vijay Ramaseshan Chandrasekhar

  [paper (coming soon)]
  

• TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks

  ACM/IEEE International Symposium on Low Power Electronics and Design (2019)

  Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar and Mohamed M. Sabry

  [paper (coming soon)]
  

• MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors

  IEEE Conference on Computer Vision and Pattern Recognition (2019)

  Lile Cai, Bin Zhao, Zhe Wang, Jie Lin, Chuan Sheng Foo, Mohamed Sabry Aly, Vijay Chandrasekhar

  [paper]
  

• Encoding Knowledge Graph with Graph CNN for Question Answering

  International Conference on Learning Representations Workshop on Representation Learning on Graphs and Manifolds (2019)

  Leo Laugier*, Anran Wang*, Chuan-Sheng Foo, Theo Guenais and Vijay Chandrasekhar

  (* equal contribution)

  [paper]
  

• Optimistic mirror descent in saddle-point problems: Going the extra(-gradient) mile

  International Conference on Learning Representations (2019)

  Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

  [paper, code (coming soon)]
  

• The Unusual Effectiveness of Averaging in GAN Training

  International Conference on Learning Representations (2019)

  Yasin Yazıcı, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar

  [paper, code]
  

• Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images

  NeurIPS Workshop on Machine Learning for Health (2018)

  Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Pavitra Krishnaswamy and Jayashree Kalpathy-Cramer

  [paper, code (coming soon)]
  

• Predicting thermoelectric properties from crystal graphs and material descriptors – first application for functional materials

  NeurIPS Workshop on Machine Learning for Molecules and Materials (2018)

  Leo Laugier, Daniil Bash, Jose Recatala, Hong Kuan Ng, Savitha Ramasamy, Chuan-Sheng Foo, Vijay R. Chandrasekhar, Kedar Hippalgaonkar

  [paper]
  

• Adversarially Learned Anomaly Detection

  IEEE International Conference on Data Mining (2018)

  Houssam Zenati*, Manon Romain*, Chuan-Sheng Foo*, Bruno Lecouat, Vijay Chandrasekhar

  (* equal contribution)

  (Full Paper)

  [paper, arXiv, code]
  

• Semi-Supervised Learning With GANs: Revisiting Manifold Regularization

  International Conference on Learning Representations, Workshop Track (2018)

  Bruno Lecouat*, Chuan Sheng Foo*, Houssam Zenati, Vijay Chandrasekhar (* equal contribution)

  [paper, arXiv, code]
  

• Learning RNA secondary structure (only) from structure probing data

  ICML Workshop on Computational Biology (2017)

  Chuan-Sheng Foo*, Cristina Pop* (* equal contribution)

  [paper (bioRxiv)]
  

• The C2H2-ZF transcription factor Zfp335 recognizes two consensus motifs using separate zinc finger arrays

  Genes & Development 30: 1509-1514 (2016)

  Brenda Yuyuan Han, Chuan-Sheng Foo, Shuang Wu and Jason G. Cyster

  [paper]
  

• Zinc finger protein Zfp335 is required for the formation of the naïve T cell compartment

  eLife 3: e03549 (2014)

  Brenda Y. Han, Shuang Wu, Chuan-Sheng Foo, Robert M. Horton, Craig N. Jenne, Susan R. Watson, Belinda Whittle, Chris C. Goodnow, and Jason G. Cyster

  [paper]
  

• A majorization-minimization algorithm for (multiple) hyperparameter learning

  Proceedings of the 26th International Conference on Machine Learning, 321–328 (2009)

  Chuan-Sheng Foo, Chuong B. Do and Andrew Y. Ng

  [pdf, slides]

• Proximal regularization for online and batch learning

  Proceedings of the 26th International Conference on Machine Learning, 257–264 (2009)

  Chuong B. Do, Quoc V. Le and Chuan-Sheng Foo

  [pdf, code]
  

• Searching for rising stars in bibliography networks

  Proceedings of the 14th International Conference on Database Systems for Advanced Applications (2009)

  Xiao-Li Li, Chuan-Sheng Foo, Kar Leong Tew, See-Kiong Ng

  [pdf]

• A max-margin model for efficient simultaneous alignment and folding of RNA sequences

  Bioinformatics, 24(13):i68–76 (2008)

  Chuong B. Do, Chuan-Sheng Foo and Serafim Batzoglou

  [pdf, code]

• Efficient multiple hyperparameter learning for log-linear models

  Advances in Neural Information Processing Systems 20:377–384 (2007)

  Chuong B. Do, Chuan-Sheng Foo and Andrew Y. Ng

  [pdf]

• Discovering protein complexes in dense reliable neighborhoods of protein interaction networks

  Computational Systems Bioinformatics: CSB 2007 Conference Proceedings, 6:157–68 (2007)

  Xiaoli Li, Chuan-Sheng Foo and See-Kiong Ng

  [pdf, website]

• Interaction graph mining for protein complexes using local clique merging

  [ Best Paper Award, GIW 2005 ]

  Genome Informatics, 16(2):260–9 (2005)

  Xiaoli Li, Soon-Heng Tan, Chuan-Sheng Foo and See-Kiong Ng

  [pdf]

• Manifold regularization with GANs for semi-supervised learning

  Bruno Lecouat*, Chuan-Sheng Foo*, Houssam Zenati, Vijay Chandrasekhar (* equal contribution)

  [paper]
  

• Efficient GAN-Based Anomaly Detection

  Houssam Zenati*, Chuan Sheng Foo*, Bruno Lecouat, Gaurav Manek, Vijay Chandrasekhar

  (* equal-contribution)

  [paper]
  

• Deep learning the relationship between chromatin architecture, chromatin state, and transcription factor binding [ Platform Talk ]

  65th Annual Meeting of The American Society of Human Genetics

  Anshul Kundaje, Chuan-Sheng Foo, Johnny Israeli, Avanti Shrikumar, Jason Buenrostro, Alicia Schep and William Greenleaf

• ATAC-seq is predictive of chromatin state

  2015 Cold Spring Harbor Laboratory meeting on Systems Biology: Global Regulation of Gene Expression

  Chuan-Sheng Foo, Sarah Denny, Jason Buenrostro, William Greenleaf, Anshul Kundaje

• ATAC-seq is predictive of chromatin state [ Oral Presentation ]

  2014 RECOMB/ISCB Conference on Regulatory and Systems Genomics, with DREAM Challenges and Cytoscape Workshops

  Chuan-Sheng Foo, Sarah Denny, Jason Buenrostro, William Greenleaf, Anshul Kundaje

• Ab-initio identification of chromatin states from chromatin accessibility data with CASCADE

  2014 Cold Spring Harbor Laboratory meeting on The Biology of Genomes

  Chuan-Sheng Foo*, Sarah K. Denny*, Margaret X. Fu*, Jason D. Buenrostro, Anshul B. Kundaje and William J. Greenleaf (*equal contribution)

• Validation of and initial experience with a next-generation sequencing-based 98-gene expanded carrier screening assay

  Association for Molecular Pathology 2013 Annual Meeting

  Hyun-Seok Peter Kang, Jared Maguire, Jonathan Tritt, Chuan-Sheng Foo, Alexander Scott Patterson and Eric A. Evans

• Gene expression deconvolution

  Biomedical Computation at Stanford 2010

  Chuan-Sheng Foo, Shai S. Shen-Orr and Daphne Koller

• Computing Research Association Outstanding Undergraduate Researcher Award (2008)
• UCSD Data Mining Contest: 1st, 2nd (2006), 3rd (2007), 2nd (2008)
• Top 200 ranking on the Putnam Mathematics Competition (2005)
• President's Award for Academic Achievement in the Freshman Year (2006)
• Best Paper Award at the 16th International Conference on Genome Informatics (2005)
• A*STAR National Science Scholarship (2002)
• Bronze medal at the 33rd International Physics Olympiad (2002)