Baihan Lin

Affiliations: 
2013-2020 University of Washington, Seattle, Seattle, WA 
 2017- Columbia University, New York, NY 
Area:
Reinforcement learning, Natural language processing, Human-computer interaction, Computational neuroscience, Bioinformatics
Website:
https://www.neuroinference.com/
Google:
"Baihan Lin"
Bio:

Baihan Lin is a neuroscientist and machine learning researcher at Columbia University. During his previous work experience at IBM, Google X, Microsoft, Amazon and BGI Genomics, he has developed various pioneering machine learning solutions in the biomedical and engineering domains for real world applications in psychiatry, genomics and interactive systems. His research in reinforcement learning (RL), deep learning (DL), and natural language processing (NLP) has translated into deployed applications such as AI companion for therapists (INTERSPEECH-22), RL models for psychiatric disorders (IJCAI-19, AAMAS-20, HBAI-20), surrounding-aware virtual reality (IJCAI-20), adaptive prescriptor for epidemic control (CEC-22, FUZZ-22) and the first online learning speaker diarization system (INTERSPEECH-20, ACML-21). He is also a main contributor to RSAToolbox, an open-sourced software that performs statistical inference to understand the neural systems and the theory of neural networks. Before his PhD at Columbia University, Baihan held a masters degree in Applied Mathematics from University of Washington, Seattle. According to Google Scholar, he has authored 30+ publications with an H-index of 13 and served on program committees or reviewers for over 15 conferences including INTERSPEECH, NeurIPS, CVPR, ICML, AISTATS, ICCV, KDD, IJCAI, ICLR, AAAI, AAMAS, MICCAI etc., and over 20 journals including but not limited to Nature Scientific Reports, PLOS ONE, IEEE Transactions on Knowledge and Data Engineering, Expert Systems with Applications, Frontiers in Robotics and AI, Frontiers in Psychiatry, Frontiers in Psychology, Frontiers in Computational Neuroscience, Frontiers in Behavioral Neuroscience, Entropy, Advances in Complex Systems etc..
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Parents

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Jaime Olavarria research assistant 2014-2016 University of Washington - Seattle/ NIH
David Baker research assistant 2015-2017 University of Washington (Computational Biology Tree)
Shwetak N. Patel research assistant 2017-2018 University of Washington - Seattle/ NIH (Computer Science Tree)
Nikolaus Kriegeskorte grad student 2017- Columbia
Guillermo Cecchi research scientist 2017- IBM
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Publications

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Lin B, Bouneffouf D, Cecchi G. (2022) Predicting human decision making in psychological tasks with recurrent neural networks. Plos One. 17: e0267907
Lin B. (2021) Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers. Entropy (Basel, Switzerland). 24
Andelin AK, Doyle Z, Laing RJ, et al. (2019) Influence of Ocular Dominance Columns and Patchy Callosal Connections on Binocularity in Lateral Striate Cortex: Long Evans vs. Albino Rats. The Journal of Comparative Neurology
Chen Z, Johnson MC, Chen J, et al. (2019) Self-assembling 2D arrays with de novo protein building blocks. Journal of the American Chemical Society
Lin B. (2019) Cliques of single-cell RNA-seq profiles reveal insights into cell ecology during development and differentiation F1000research. 8
Teng Y, Liu S, Guo X, et al. (2017) An Integrative Analysis Reveals a Central Role of P53 Activation via MDM2 in Zika Virus Infection Induced Cell Death. Frontiers in Cellular and Infection Microbiology. 7: 327
Teng Y, Bi D, Xie G, et al. (2017) Model-Informed Risk Assessment for Zika Virus Outbreaks in the Asia-Pacific Regions. The Journal of Infection
Teng Y, Bi D, Xie G, et al. (2017) Dynamic Forecasting of Zika Epidemics Using Google Trends. Plos One. 12: e0165085
Teng Y, Wang Y, Zhang X, et al. (2015) Systematic Genome-wide Screening and Prediction of microRNAs in EBOV During the 2014 Ebolavirus Outbreak. Scientific Reports. 5: 9912
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