Scott Cheng-Hsin Yang

I am currently a post-doc with Patrick Shafto in the Math & Computer Science Department at Rutgers University–Newark. My research interests can be summarized by combinations of these four words— human, machine, learning, and teaching.

Current projects include:
  • using Bayesian teaching to explain AI (DARPA XAI),
  • developing unifying models of active and pedagogical learning,
  • understanding the interactions between people and recommender systems,
  • exploring cooperative inference for succeessful AI-human teaming (DARPA ASIST).

Prior to this, I was a post-doc with Daniel Wolpert and Máté Lengyel in the CBL Lab at the University of Cambridge. There I studied active sensing by tracking human eye movement and quantifying sensing efficiency with Bayesian active learning.

Prior to that, I did my PhD with John Bechhoefer in the Physics Department at Simon Fraser University. There I modelled the DNA replication as a stochastic process and applied the theory to analyze several types of replication experiment.

Contact: scottchenghsinyang[AT]gmail[DOT]com

Publications

Scott Cheng-Hsin Yang*, Wai Keen Vong*, Ravi B. Sojitra*, and Patrick Shafto (2020)
Understanding explainable artificial intelligence with Bayesian Teaching
Under review.
Scott Cheng-Hsin Yang, Chirag Rank, Jake Alden Whritner, Olfa Nasraoui, and Patrick Shafto (2020)
Unifying recommendation and active learning for information filtering and recommender systems
Under review.
Libby Barak, Scott Cheng-Hsin Yang, Chirag Rank, and Patrick Shafto (2020)
Replicating L2 learning in a Computational Model
Proceedings of the 42th annual conference of the Cognitive Science Society
Chi-Ken Lu, Scott Cheng-Hsin Yang, Xiaoran Hao, and Patrick Shafto (2020)
Interpretable deep Gaussian processes with moments
Proceedings of the 23st international conference on Artificial Intelligence and Statistics
Scott Cheng-Hsin Yang, Wai Keen Vong, Yue Yu, and Patrick Shafto (2019)
A unifying computational framework for teaching and active learning
Topics in Cognitive Science 11(2):316-337 [code] [slides] [15-min talk]
Chi-Ken Lu, Scott Cheng-Hsin Yang, Patrick Shafto (2018)
Standing Wave Decomposition Gaussian Process
Physical Review E 98:032303 [code]
Yue Yu, Patrick Shafto, Elizabeth Bonawitz, Scott Cheng-Hsin Yang, Roberta M. Golinkoff, Kathleen H. Corriveau, Kathy Hirsh-Pasek, and Fei Xu (2018)
The Theoretical and Methodological Opportunities Afforded by Guided Play With Young Children
Frontiers in Psychology 9:1152. doi:10.3389/fpsyg.2018.01152
Wai Keen Vong, Ravi B. Sojitra, Anderson Reyes, Scott Cheng-Hsin Yang*, and Patrick Shafto* (2018)
Bayesian teaching of image categories
Proceedings of the 40th annual conference of the Cognitive Science Society
Scott Cheng-Hsin Yang, Yue Yu, Arash Givchi, Pei Wang, Wai Keen Vong, and Patrick Shafto (2018)
Optimal Cooperative Inference
Proceedings of the 21st international conference on Artificial Intelligence and Statistics [poster]
Scott Cheng-Hsin Yang and Patrick Shafto (2017)
Explainable Artificial Intelligence via Bayesian Teaching
NIPS 2017 workshop on Teaching Machines, Robots, and Humans [poster]
Scott Cheng-Hsin Yang and Patrick Shafto (2017)
Teaching versus active learning: A computational analysis of conditions that affect learning
Proceedings of the 39th Annual Conference of the Cognitive Science Society [poster] [code]
Scott Cheng-Hsin Yang, Jake Alden Whritner, Olfa Nasraoui, and Patrick Shafto (2017)
Unifying recommendation and active learning for human-algorithm interactions
Proceedings of the 39th Annual Conference of the Cognitive Science Society [slides]
Scott Cheng-Hsin Yang, Daniel Wolpert, and Máté Lengyel (2016)
Theoretical perspectives on active sensing
Current Opinions in Behavioural Neuroscience 11:100-108
Scott Cheng-Hsin Yang, Máté Lengyel, and Daniel Wolpert (2016)
Active sensing in the categorization of visual patterns
eLife 5:e12215 [full content online] [powerpoint] [code] [20-min talk]
Shankar P. Das, Tyler Borrman, Scott Cheng-Hsin Yang, Victor W. T. Lui, John Bechhoefer, and Nicholas Rhind (2015)
Replication timing is regulated by the number of MCMs loaded at origins
Genome Research 25:1886-1892
Scott Cheng-Hsin Yang (2012)
Modelling the DNA replication program in eukaryotes
PhD Thesis
Antoine Baker, Benjamin Audit, Scott Cheng-Hsin Yang, John Bechhoefer, and Alain Arneodo (2012)
Inferring where and when replication initiates from genome-wide replication timing data
Phyiscal Review Letter 108:268101
Scott Cheng-Hsin Yang, Nicholas Rhind, and John Bechhoefer (2010)
Modeling genome-wide replication kinetics reveals a mechanism for regulation of replication timing
Molecular Systems Biology 6:404 [supplementary material] [slides] [code]
Rated by Faculty of 1000 Biology as MUST READ [link]
Nicholas Rhind, Scott Cheng-Hsin Yang, and John Bechhoefer (2010)
Reconciling stochastic origin firing with defined replication timing
Chromosome Research 18:35
Scott Cheng-Hsin Yang, Michel Gauthier, and John Bechhoefer (2009)
Computational methods to study kinetics of DNA replication
Methods in Molecular Biology 521:555-573
Scott Cheng-Hsin Yang and John Bechhoefer (2008)
How Xenopus laevis embryos replicate reliably: Investigating the random-completion problem
Physical Review E 78:041917 [slides]
Selected for a Viewpoint article: Just-in-time DNA replication