CV

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Education

• B.S. in Aircraft Environment and Life Security Engineering, Beihang University, 2010
• M.S. in Mechanical Engineering, Beihang University, 2013
• Ph.D in Mechanical Engineering, Rensselaer Polytechnic Institute, 2020

Research Experience

• 2015 – 2020: Research Assistant
  • Rensselaer Polytechnic Institute
  • Supervisors: Professor Suvranu De and Professor Xavier Intes
• 2018 - 2019: Visiting scholar
  • University of Buffalo
  • Duties included: Neuromodulation and neuroimaging experiments
  • Supervisors: Professor Lora Cavuoto and Dr. Steven Schwaitzberg
• 2016: Researcher
  • Harvard Medical School
  • Duties included: Neuromodulation experiments
  • Supervisors: Professor Alvaro Pascual-Leone and Dr. Emiliano Santarnecchi

Work Experience

• Aug 2013 - June 2015: Motor design engineer
  • SAIC MOTOR (Shanghai)
  • Duties included: IP parts design

Skills

• Programming language: Python, C/C++/C#, VB, SQL;
• Statistical tools: Matlab, SPSS, Minitab, G*Power;
• Computer aided design/engineering: Solidworks, CATIA, autoCAD, ANSYS, NX, CFD;
• Operating systems: Windows, Linux (Ubuntu) and Mac OS;
• Hardware: fNIRS spectrometers; Trans-cranial electrical stimulation device; Laparoscopic skill trainer;
• Others: Microsoft Office Series, Latex.

Certification

• Introduction to transcranial direct current stimulation (offline) by Harvard (03/2016);
• Databases and SQL for Data Science (online) by IBM (03/2020)

Publications

A Machine Learning approach to predict surgical learning curves

Gao, Y., Kruger, U., Schwaitzberg, S., Intes, X., De, S. (2019). "A Machine Learning approach to predict surgical learning curves." Surgery. 167(2), 321-327.DOI: https://doi.org/10.1016/j.surg.2019.10.008.

Functional brain imaging reliably predicts bimanual motor skill performance in a standardized surgical task

Gao, Y., Yan, P., Kruger, U.,Cavuoto, L., Schwaitzberg, S., De, S., Intes, X. (2020). "Functional brain imaging reliably predicts bimanual motor skill performance in a standardized surgical task" IEEE TBME. Early Access. DOI: 10.1109/TBME.2020.3014299.

A comprehensive review of experimental neuroimaging studies of the effect of transcranial electrical stimulation on human motor skills

Gao, Y., Cavuoto, L., Schwaitzberg, S., Norfleet, J., Intes, X., De, S. (2020). "The effects of transcranial electrical stimulation on human motor functions: A comprehensive review of functional neuroimaging studies" Frontiers in Neuroscience. 14:744 (2020). DOI: https://doi.org/10.3389/fnins.2020.00744.

Deep Learning-based Motion Artifact Removal in Functional Near-Infrared Spectroscopy (fNIRS)

Gao, Y., Chao, H., Cavuoto, L., Yan, P., Kruger, U., Norfleet, J., Makled, B., Schwaitzberg, S., De, S., Intes, X. (2020). "Deep Learning-based Motion Artifact Removal in Functional Near-Infrared Spectroscopy (fNIRS)" Neuroimage. Under review.

Talks

Brain2Image: Converting Brain signals into images

June 21, 2018

Workshop at DL journal club at Rensselaer Polytechnic Institute, Troy, New York

DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing

August 09, 2018

Workshop at DL journal club at Rensselaer Polytechnic Institute, Troy, New York

Evaluating surgical skills from kinematic data using convolutional neural networks

September 12, 2018

Workshop at DL journal club at Rensselaer Polytechnic Institute, Troy, New York

Rethinking the Faster R-CNN Architecture for Temporal Action Localization

October 17, 2018

Workshop at DL journal club at Rensselaer Polytechnic Institute, Troy, New York

Recognizing Brain States Using Deep Sparse Recurrent Neural Network

December 19, 2018

Workshop at DL journal club at Rensselaer Polytechnic Institute, Troy, New York

Neuroimaging biomarkers for surgical skill level prediction

February 01, 2019

Poster at SPIE.bios, San Francisco, California

fNIRS as a quantitative tool to asses and predict surgical skills

April 01, 2019

Oral presentation at OSA Biophotonics Congress: Optics in the Life Sciences, Tucson, Arizona

A deep learning approach to remove motion artifacts in fNIRS data analysis

April 20, 2020

Oral presentation at OSA Biophotonics Congress: Optics in the Life Sciences, Florida, USA

Monitoring the effect of transcranial Electric current Stimulation (tES) during a bimanual motor task via functional Near-InfraRed Spectroscopy (fNIRS)

April 20, 2020

Poster presentation at OSA Biophotonics Congress: Optics in the Life Sciences, Florida, USA

Transcranial direct current stimulation speeds up surgical bimanual motor learning and increases functional activation

August 30, 2020

Oral presentation at MHSRS, Young Investigator breakout session, Florida, USA

Teaching

Thermal and Fluid Engineering II (MANE 4010)

Modeling and Analysis of Uncertainty (ENGR 2600)

Modeling and Analysis of Uncertainty (ENGR 2600)

Undergraduate Research Program (URP)

Modeling of Biomedical Systems (BMED 4200)

Thermal and Fluid Engineering I (ENGR 2250)