About Me
Education
Ph.D. – Mechanical Engineering, GPA 4.00/4.00, 08/2020 – 03/2024
University of Texas at Austin, Austin, TX, USA
M.S.– Mechanical Engineering, GPA 4.00/4.00, 08/2017 - 12/2018
University of Michigan, Ann Arbor, MI, USA
B.S. – Mechanical Engineering, GPA 3.98/4.00, 01/2013 - 12/2016
Purdue University, West Lafayette, IN, USA
Honors and Awards
University Graduate Continuing Fellowship (09/2023)
Cockrell School of Engineering Fellowship, University of Texas at Austin (All Ph.D. Semesters)
ASME Automotive and Transportation Systems Best Paper Award (10/2022)
Professional Development Awards, University of Texas at Austin (12/2021,09/2022,12/2022,09/2023)
Graduate with Highest Distinction, Purdue University (12/2016)
Purdue Big Move Scholarship, Purdue University (05/2016)
Bottomley Research Scholarship, Purdue University (09/2015)
Dean’s List and Semester Honors, Purdue University (All Undergrad Semesters)
Doctoral Research Experience
Mobility Systems Lab, University of Texas at Austin, Austin, TX, USA
Graduate Research Assistant, Intelligent Automated Vehicle, Human-Automation Shared Driving, Intelligent Transportation, ADAS, Vehicular Control System, 08/2020 – 05/2024
Leading the research and development of various advanced autonomous/automated vehicle control, driver assistance, vehicle state estimation, and transportation electrification technologies synergizing advanced control theories (e.g., attracting-manifold-based control, robust adaptive control, linear robust control, etc.) and emerging machine learning techniques (artificial neuro networks, transformer, etc.).
Co-leading the traffic simulation development and human subject test for the mixed vehicular automation (L0 - L3) study, sponsored by the Texas Department of Transportation (TxDOT)
Industrial Experience
Virgin Hyperloop R&D Center, Los Angeles, CA, USA
Control Engineer, Control Algorithm & Embedded Software Development, 10/2019 – 08/2020
Development of the robust localization program, which fuses sensory inputs comprising IMU, transponder, and Lidar, for estimating the vehicular location/displacement, velocity, and acceleration.
Embedded software (C) development for multiple vehicle flight control programs, including levitation control and vehicle powertrain control (longitudinal proportion control, lateral guidance control, and brake control)
SERES EV (SF Motors) Silicon Valley R&D Center, Santa Clara, CA, USA
Control Engineer, Powertrain and Chassis Control Algorithm & Firmware Development, 03/2019 – 10/2019
Leading the torque vectoring control algorithm and firmware (C) development for the SFX supercar project, including torque vectoring hierarchical control strategy, direct yaw moment control, side slip angle regulation, traction control, and torque split algorithm respectively.
Co-leading the vehicle dynamics estimation algorithm and firmware development for both the SFX supercar project and SF5 production car project, including vehicle longitudinal velocity estimation, vehicle sideslip angle estimation, and tire slip estimation.
Co-leading the SIL and HIL (dSPACE) development for testing torque vectoring control and vehicle dynamics estimation.
Leading various firmware developments, including vehicle creep control, regenerative brake light control, motor stall detection & protection, torque manager safety check, to name a few.
Pre-Doctoral Research Experience
General Motors/University of Michigan Vehicle Systems Research Lab, Ann Arbor, MI, USA
Summer Research Assitant, Inflatable Modeling and Control, 05/2018 – 08/2018
Leading the development of analytical static and dynamics models under out-of-plane centric Hertzian contact loading for circular thin membrane inflatable structures for predicting the deformation behavior.
A discretized LQR based on the linearized discretized dynamics model is devised to regulate the inflatable membrane's deformation level.
The synthesized deformation controller is validated Simulink, followed by experimental tests.
A parametrical study is conducted on the model and control algorithm to develop guidelines for future design optimizations.
Von Karman Institute for Fluid Dynamics (VKI), Brussels, Belgium
Visiting Research Student, Low-speed Axial Compressor Experimental Study, 05/2016 – 06/2016
Analytical and empirical CFD models are developed for the low-speed axial compressor for laminar and turbulent flow.
Experiments are performed in a low-speed axial compressor to measure the aero-thermal properties of the wind flow.
Measurement sensors characteristics are studied and calibrated in terms of sensitivity, bias stability, noise variance, etc.
A Kalman Filter is designed to filter out the process and measurement noises from the experimental data.
Experimental data are studied in terms of construction of a compressor map, uncertainty quantification of aero-thermal measurements, quantification of errors due to signal discretization, and frequency domain analysis (FFT and PSD).
Purdue University School of Mechanical Engineering, West Lafayette, IN, USA
Bottomley Research Scholar, All-wheel Regenerative Braking System Modeling and Control, 01/2016 – 05/2016
The dynamic model of the regenerative brake system is studied, simplified, linearized, and followed by stability analysis.
An estimator-based output-feedback controller (devised as an LQG) is designed to manage the braking forces on each individual wheel in order to maintain the vehicular lateral stability during the regen-brake.