Sheng-Hsiou (Shawn) Hsu
I am a founding team member and senior Research Scientist at NextSense, Inc., a silicon-valley-based Medtech startup aiming to unlock brain health with data insights and scientific wisdom. Prior to the startup adventure, I was a Research Scientist at Google X , the moonshot factory, working on an early-stage moonshot project on brain/health sensing.

I received my PhD in Bioengineering from University of California San Diego (UCSD), working with Drs. Tzyy-Ping Jung, Scott Makeig, and Gert Cauwenberghs at Swartz Center for Computational Neuroscience (SCCN). My research focuses on developing signal processing algorithms and machine learning techniques and exploring their applications to biosignals intersecting the fields of computational neuroscience, brain-computer interfaces, and brain health. For more information, see the overview of research projects and my publications, invited presentations, and open-source codes. I received my BS in Electrical Engineering from National Taiwan University. 
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​Alongside my passion for scientific research and technology development, I am also a dedicated mentor and teacher, a freelance science writer, and a blogger. In my leisure time, I enjoy reading a wide range of books, playing saxophone and piano, playing tennis, surfing, hiking, and traveling. See more about me.
Contact Me:
​Professional: sh.shawn.hsu [at] gmail [dot] com
​​CV (available upon request) ​​​

Areas of Interests / Expertise

  • Mental Health: sleep | daytime sleepiness | stress |  guided meditation | emotion
  • Brain Health: clinical studies | sleep disorders | epilepsy and seizures | schizophrenia | autism | Alzheimer's' Disease
  • Wearable Technologies: neural, physiological, motion sensors and devices | neurostimulation | neuromodulation
  • Signal Processing: real-time and adaptive signal processing | noise and artifact removal | source separation and localization
  • Machine Learning: unsupervised learning for data mining (e.g. mixture models) | deep learning | feature engineering on time-series data | clustering
  • Data Science / Engineering: data pipeline | data warehouse
  • Biomedical Data Analysis: EEG, ECoG, EMG | multi-modal data analysis (e.g. PPG, GSR) | MRI images (structural, functional, angiographic)
  • Brain-Computer Interfaces: emotion decoding | drowsiness detection in driving | SSVEP-based BCI | stress reduction | * For an overview, see the slides of my invited talk "Real-world applications for brain-computer interfaces"

Explore More!

News

Apr, 2023 | Joint collaboration abstract with Takeda and Emory University was accepted at APSS SLEEP 2023 Annual Meeting, titled "A novel, wearable, in-ear EEG technology to assess sleep and daytime sleepiness." 
Dec, 2022 | Abstract was accepted at 2022 American Epilepsy Society (AES) Annual Meeting titled "EEG earbuds enable long-term monitoring of seizures."
Jul, 2022 | Conference paper was accepted at 2022 IEEE EMBC, "Novel EEG-Based Neurofeedback System Targeting Frontal Gamma Activity of Schizophrenia Patients to Improve Working Memory"
Apr, 2022 | NextSense' story featured on Wired magazine!
Jan, 2022 | First-authored paper "Unsupervised learning of brain state dynamics during emotion imagination using high-density EEG" published on NeuroImage. My favorite paper so far on advancing the techniques for studying human emotions!
Dec, 2021 | Our company NextSense, Inc., came out of stealth mode! Hello world! (News)
Aug, 2021 | Our paper on abnormal sleep physiology was published on Molecular Autism. Congrats to my collaborators, Vidya Saravanapandian et al., at UCLA. 
Dec, 2020 | Joined NextSense, Inc., as a founding team member and a senior Research Scientist!
Oct, 2020 | Our paper on decoding emotion was accepted 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Congrats to my student, Shihan Ran!
Mar, 2020 | Officially joined Google X, the moonshot factory, as a full-time Research Scientist!
Jan, 2020 | Co-authored paper "Modulation of frontal gamma oscillations improves working memory in schizophrenia" published on Neuroimage: Clinical. 
Dec, 2019 | Our abstract "Modeling EEG Dynamics Associated with Emotional Responses in a Music-listening Experiment " was awarded to present at Spotlight Session in IEEE EMBS Symposium on Brain, Mind and Body - Cognitive Neuroengineering for Health and Wellness. Congrats to my student - Shihan Ran!
July 2019 | Our paper "Evaluation of Artifact Subspace Reconstruction for Automatic Artifact Components Removal in Multi-channel EEG Recordings,'' was published in IEEE Transactions on Biomedical Engineering. Congrats to my student - Chiyuan Chang!
May 2019 | Gave two invited talks, titled "EEG and Brain-Computer Interfaces: Past, Present, and Future," at Institute for Brain and Mind (KIBM) for Young Researchers, UCSD (May 29) and Taiwanese Young Researcher Association (Tyra) (June 15). 
Aug, 2018 | First-authored paper "Modeling Brain Dynamic State Changes with Adaptive Mixture Independent Component Analysis,” was published in NeuroImage!
Mar, 2018 | Received a Travel Award to 7th International BCI Meeting (May, 2018)
Mar, 2018 | Awarded a Travel Grant to SIAM Conference on Data Mining (SDM) Doctoral Forum (May, 2018)
Mar, 2018 | Co-authored paper "The study of evaluation and rehabilitation of patients with different cognitive impairment phases based on virtual reality and EEG" was accepted for publication in Frontiers in Aging Neuroscience. 
Jan, 2018 | Defended my PhD dissertation "Tracking the dynamic brain: modeling nonstationarity in human EEG."
Sep, 2017 | Journal article "Monitoring alert and drowsy states by modeling EEG source nonstationarity" was published on Journal of Neural Engineering!
Aug, 2017 | Live demo of "Real-time artifact rejection using REST" at SCCN open house for 50+ SMPC conference attendees.
Apr, 2017 | Co-founded and organized the first SoCal Taiwanese Biotechnology Symposium which brought together 20+ speakers and 200+ attendees in BioTech industry and academics in Southern California.
Dec, 2016 | Gave an invited talk "Real-world applications for brain-computer interfaces" at Annual Meeting of North America Taiwanese Professors’ Association - Southern California Chapter.
Aug - Oct, 2016 | Research intern at Technical University of Berlin (TU-Berlin), Berlin, Germany.

Selected Publications

Full publications list
  • Xu, H.*, Hsu, S.H.*, Nakanishi, M.*, Lin, Y., Jung, T.P., and Cauwenberghs, Gert. (2023). “Stimulus design for visual evoked potential based brain-computer interfaces”. IEEE transactions on neural system and rehabilitation engineering. (in revision)
  • Hsu, S.H., Lin, Y., Onton, J., Jung, T.P. and Makeig, S., (2022). "Unsupervised Learning of Brain State Dynamics during Emotion Imagination using High-Density EEG". NeuroImage, p.118873.
  • Saravanapandian, V., Nadkarni, D., Hsu, SH. et al.  (2021) "Abnormal sleep physiology in children with 15q11.2-13.1 duplication (Dup15q) syndrome". Molecular Autism 12, 54.
  • Singh, F., Shu, I.W., Hsu, S.H., Link, P., Pineda, J.A. and Granholm, E., (2020). "Modulation of frontal gamma oscillations improves working memory in schizophrenia." NeuroImage: Clinical, 27, p.102339.
  • Chang, C.Y.*, Hsu, S.H.*, Pion-Tonachini, L. and Jung, T.P., (2019) "Evaluation of Artifact Subspace Reconstruction for Automatic Artifact Components Removal in Multi-channel EEG Recordings,'' IEEE Transactions on Biomedical Engineering. [PDF]
  • Wen, D., Jia, P.,Hsu, S.H., Zhou, Y., Lan, X., Cui, D., Li, G., Yin, S. and Wang, L., (2019) "Estimating coupling strength between multivariate neural series with multivariate permutation conditional mutual information." Neural Networks, 110, pp.159-169.
  • ​Hsu, S.-H., Pion-Tonachini, L., Palmer, J., Miyakoshi, M., Makeig, S., and Jung, T.-P., (2018) “Modeling Brain Dynamic State Changes with Adaptive Mixture Independent Component Analysis,” NeuroImage. [PDF]
  • Hsu, S.-H., Zi Y., Wu Y., Jackson P. M. and Jung T. P., (2018) "Exploring Mental State Changes during Hypnotherapy using Adaptive Mixture Independent Component Analysis," IEEE Biomedical Circuits and Systems Conference (BioCAS).
  • Buccino A. P., Hsu, S.-H. and Cauwenberghs, G., (2018) "Real-Time Spike Sorting for Multi-Electrode Arrays with Online Independent Component Analysis,'' in IEEE BioCAS.
  • Pion-Tonachini, L., Hsu, S.-H., Chang, C. Y. , Jung, T. P., and Makeig, S., (2018) “Automatic Artifact Rejection using the Real-time EEG Source-mapping Toolbox (REST).” Annual International Conference of the IEEE Engineering in Biology and Medicine Society (IEEE EMBC).
  • Chang, C. Y.* , Hsu, S.-H.*, Pion-Tonachini, L., and Jung, T. P., (2018) “Evaluating Artifact Subspace Reconstruction for Automatic Artifact Removal.” IEEE EMBC.
  • Hsu, S. H. and Jung, T.-P., (2017) "Monitoring alert and drowsy states by modeling EEG source nonstationarity." Journal of Neural Engineering. [PDF]
  • Hsu, S. H. and Jung, T. P., (2016) "Modeling and tracking brain nonstationarity in a sustained attention task." In International Conference on Augmented Cognition, pp. 209-217. Springer International Publishing. [Awarded Oral Presentation] [PDF]
  • Hsu, S. H., Mullen, T. R., Jung, T. P., and Cauwenberghs, G., (2016) "Real-Time Adaptive EEG Source Separation Using Online Recursive Independent Component Analysis," IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(3), 309-319. [PDF]
  • Hsu, S. H.*, Pion-Tonachini, L.*, Jung, T. P., and Cauwenberghs, G., (2015) "Tracking non-stationary EEG sources using adaptive online recursive independent component analysis." 37th IEEE EMBC. [Awarded UCSD Travel Grant] [PDF]
  • Pion-Tonachini, L.*, Hsu, S. H.*, Makeig, S., Jung, T. P., and Cauwenberghs, G., (2015) "Real-time EEG Source-mapping Toolbox (REST): Online ICA and source localization," 37th IEEE EMBC. [PDF]
  • Hsu, S. H., Mullen, T., Jung, T. P., and Cauwenberghs, G., (2015), "Validating online recursive independent component analysis on EEG data." 7th International IEEE/EMBS Conference on Neural Engineering, pp. 918-921. [Awarded UCSD Travel Grant] [PDF]
  • Hsu, S. H., Mullen, T., Jung, T. P., and Cauwenberghs, G., (2014) "Online recursive independent component analysis for real-time source separation of high-density EEG." 36th IEEE EMBC. [Awarded Oral Presentation] [PDF]

Awards and Honors

  • Travel Award, 7th International BCI Meeting (May, 2018) 
  • Travel Grant, SIAM Conference on Data Mining (SDM) Doctoral Forum (May, 2018)
  • Research Fellowship - Frontiers of Innovation Scholars Program, UC San Diego (2015-2016)
  • Silver medal, BCI Challenge @ NER, Kaggle competition (2015)
  • UC San Diego Travel Grants - IEEE NER (2015) and IEEE EMBC (2015)
  • Scholarship of government sponsorship for overseas study, Ministry of Education, Taiwan (2012)
  • Honorary Member, Phi Tau Phi Scholastic Honor Society (2011)
  • UIUC Exchange Student Scholarship, NTU EE Department (2010)
  • Presidential Awards, NTU EE Department (2007-2011)

Experiences

Work Experiences

  • Senior Research Scientist, NextSense, Inc., Sep 2020 - present, Mountain View, CA
  • Research Scientist, Google X (X Development), Mar 2020 - Sep 2020, Mountain View, CA 
  • Research Specialist, Veterans Affairs San Diego Healthcare System, Oct 2018 - Mar 2020, La Jolla, CA
  • Postdoctoral Scholar, University of California, San Diego, Mar 2018 - Mar 2020, La Jolla, CA
  • Advisor, Google X (X Development), June 2019 - Dec 2019, Mountain View, CA 

Academic Training

  • ​Graduate Researcher, Swartz Center for Computational Neuroscience, UC San Diego, Sep 2012 - Mar 2018, La Jolla, CA
  • ​Research Intern, Department of Psychology and Ergonomics, Berlin Institute of Technology (TU Berlin), Aug 2016 - Oct 2016, Berlin, Germany
  • Graduate Researcher, Computational Neurobiology Lab, Salk Institute for Biological Studies, Mar 2013 - Jun 2013, La Jolla, CA
  • Research Assistant, Functional and Micro-Magnetic Resonance Imaging Center, Academia Sinica, Aug 2009 - Aug 2011, Taipei, Taiwan

Teaching

  • ​Lead Teaching Assistant, BENG 221 Mathematical Methods in Bioengineering, UC San Diego, Fall 2013 & Fall 2014
  • Teaching Assistant, BENG 227 Transport Phenomena in Living Systems, Spring 2013
  • Teaching Assistant, BENG 186B Principles of Bioinstrumentation Design, UC San Diego, Winter 2013

Leadership

Mentorship

  • Yayu Lin (PhD student in ECE at UCSD) "Unsupervised Learning for Emotion Identification'', 2018 - present
  • Chi-Yuan Chang, (PhD student in Bioengineering at UCSD), "Real-time EEG Artifact Removal using Source Decomposition" Jan 2017 - present
  • Shihan Ran, (MS student in CS at UCSD "Online Emotion-State Decoding", 2019 - present
  • Qin Li, (MS/BS student in BioE at UCSD) "Decoding Algorithm for VEP-based Brain Computer Interface'" 2019 - present
  • Ting Yu, (BS student in Math/CS at UCSD) "Hidden Markov Model for Brain State Decoding" 2019 - present
  • Hao-Yin Xu, Yufan Lin, and Qiuyi Wang, (BS students in Neuroscience, BioE, Psychology at UCSD) "VEP-based Brain Computer Interface" 2019 - present
  • Yihan Zi, (MS student in Bioengineering at UCSD), Sep 2017 - present
  • Nguyen Diem, (MS in EECS at National Chiao Tung University, Taiwan), "Implementation of Online Recursive Independent Component Analysis on FPGA" Jun 2016 - Oct 2017
  • Quyuh Nguyen, Pourya Pourhosseini, Jasmin Hurtado and Pedram Pourhosseini, (Senior students in Bioengineering at UCSD), "EEG-based Biofeedback System for Stress Reduction​" Sep 2015 - Jun 2016

Online Profiles