About

Research

My research develops new statistical machine learning algorithms to optimally fuse high-dimensional, heterogeneous, multi-modality data sources generated in the healthcare & military settings, such as imaging, physiological signals, and clinical records, in order to support medical decision making for telemonitoring, diagnostics, and combat recovery. 

Education

Industrial Engineering, Ph.D.

Arizona State University

Dissertation: Novel Semi-Supervised Learning Models to Balance Data Inclusivity and Usability in Healthcare Applications (Chair: Prof. Jing Li)

Biomedical Engineering, M.S.

Arizona State University

Thesis: The Role of Tactile Information in Transfer of Learned Manipulation Following Changes in Degrees of Freedom (Chair: Prof. Marco Santello)

Biomedical Engineering, B.S.E

Arizona State University

Barrett Honors College; student speaker for the Engineering Convocation

Work experience

Assistant Professor of Operations Research

Department of Operational Sciences, Graduate School of Engineering and Management

Air Force Institute of Technology

Postdoctoral Research Fellow

H. Milton Stewart School of Industrial and Systems Engineering (ISyE)

Georgia Institute of Technology

Research Affiliate

Department of Radiology

Mayo Clinic

Postdoctoral Research Fellow

ASU-Mayo Clinic Center for Innovative Imaging (AMCII)

Graduate Research Intern

Martinos Center for Biomedical Imaging

Harvard Medical School/Massachusetts General Hospital

Graduate Research Assistant

School of Computing, Informatics, and Decision Systems Engineering (SCIDSE)

Arizona State University

Honors & Awards

• CogPilot Datathon Challenge (hosted by AFWERX), 2021, nationwide challenge to predict flight difficulty and pilot error using multimodal sensor data (e.g., heart rate and eye-tracking), of the 10 awards my team was eligible for, we won 5:

  • Flight Difficulty Prediction (Best Model)

  • Pilot Error Regression (Runner-Up)

  • Most Innovative Approach

  • Most Interpretable Model

  • Best Pitch

• Best Paper Award (Applied Track), 2019, INFORMS Data Mining and Decision Analytics Workshop

• Achievement Awards for College Scientists (ARCS), 2019, awarded to 35 Ph.D. students in the state of Arizona for excellent scientific research and academic achievement

• Industrial Engineering Outstanding TA Award, 2019, ASU

• Excellent Reviewer Recognition, 2019, NeurIPS Machine Learning for Health Workshop; awarded to top 5% rated reviewers

• ASU-Mayo Clinic Center for Innovative Imaging Travel Grant, 2019

• INFORMS Principal Cup, 2nd place, 2018, an international challenge hosted by INFORMS; using historic data and operations research tools, participants were challenged to develop an objective decision-making process to buy, sell, or hold stocks that experience significant events

• INFORMS ASU Student Research Presentation Competition, 2nd place, 2018

• Graduate College Fellowship, 2018, ASU

• Graduate and Professional Student Association Travel Grant, 2017 & 2018, ASU

• School of Computing, Informatics, and Decision Systems Engineering (SCIDSE) Doctoral Fellowship, 2017, ASU

• Headache Trainees Tournament (International Headache Conference), 2017, conference abstract chosen as the top 3 out of 99 submissions of doctoral students to participate in a presentation tournament at the one of the largest conferences in headache medicine

• Harold Wolff-John Graham Award (Best Paper), 2016, American Academy of Neurology

• Harold G. Wolff Lecture Award (Best Paper), 2015, American Headache Society

• Dean's Fellowship, 2014, ASU

• Tau Beta Pi Fellowship, 2013-2014, ASU