• Evaluating long-term investment opportunities from a hedge fund perspective• Used the Feature Selections Machine Learning tool in Python Package to identify the key drivers of revenue in 3M Healthcare division, resulting in 5 million Dollars profits • Developed a Vector Autoregressive (VAR) statistical model in R package • Conducted in-depth industry and company-specific fundamental equity research • Conducted data analysis, industry research and future trend investigation (FactSet, Pitchbook) and performed due diligence

• Led an over $1MM travel demand forecasting task in the I-5 Managed Lane project, including data analysis, budget planning, labor cost estimation, cross-functional team coordination, assessing climate impact and sustainability modeling and project management• Developed the Sacramento regional travel demand model with Cube Voyage• Forecasted commodity flows, energy/fuel consumption, truck movements, emissions of greenhouse gases (GHG) in 2050 by the California Statewide Forecasting Model (CSFFM)

• Co-authored 2040 Metropolitan Transportation Plan and the Sustainable Communities Strategy/ Environmental Impact Report Document• Used the Greedy Feature Selections and Random Forest classification, KKNN and LogitBoost in R library to train the machine learning model in Stanford University • Led the Central Coast Supra-Regional Activity-Based Model (ABM) Framework ABM framework for three MPO (AMBAG, SLOCOG, SBCAG) funded by Caltrans over $1MM• Managed a top federal funding project of the Strategic Highway Research Program from the Federal Highway Administration, $250K, only six states in the US were awarded (Infrastructure Investment Project)

• Developed the regional travel demand model to trend the future toll revenue, secure municipal bond investments, mitigate the financial burden on government budgets through the Public-Private Partnership (PPPs) financing• Developed the stand-alone Fright Model Enhancement to ensure the Freight model to be more compatible with FHWA’s FAF 3. • Developed Cincinnati, Cleveland and Columbus (3C) CT-Ramp Activity-Based Model, Columbus, Ohio, $1MM, sponsored by the Federal Highway Administration, the Ohio DOT and the MORPC

I-66 Managed Lane Study for VDOT: Worked on 4-Steps Travel Demand Model with Cube Software; Worked on traffic signal analysis arterial intersection using HCS and Synchro; conducting 3-D traffic simulation using VISSIM; responsible for CUBE model calibration and validation, toll diversion model implementation, and toll rate sensitivity analysis. I-4 Planning-Level Traffic and Revenue Study for FDOT: responsible for reviewing, modifying regional travel demand model; calibrating and validating model with Cube Voyage, and forecasting potential traffic and revenue for planning purpose.Wellness Way Parkway Planning-Level Traffic and Revenue Study for FDOT: responsible for collecting data, socioeconomic analysis, travel demand model calibration and validation with Cube Voyage, toll rate sensitivity analysis, and forecasting potential traffic and revenue for planning purpose.West Bay Parkway Planning-Level Traffic and Revenue Study for FDOT: responsible for Travel Demand Model calibration and validation with Cube Voyage, toll rate sensitivity analysis, and forecasting potential traffic and revenue for planning purpose.

Smart Work Zone Optimization Study for MassDOT: helping the Massachusetts Department of Transportation (MassDOT) develop Standard Operating Procedure for Smart Work Zone deployment and traffic impact mitigation strategy; also analyzing capacity and monitoring traffic data related to a specific Smart Work Zone deployment on Interstate 95.

Automatic Traffic Volume Report System Development, NE: developed a Traffic Volume Report Database system used for historical traffic volume data for the City of Lincoln with ACCESS and Visual Basic. Heavy vehicle adjustment factors for high percentages of trucks, NE: responsible for developing and maintaining a Video Archiving Database system for NDOR since the project archived a large amount of video for the Nebraska Department of Road (NDOR). Evaluation of Physiological Impact of Sight Distance Design of STOP Sign Intersection, Lincoln, NE: this paper examines the effects of intersection sight distance (ISD) on drivers’ physiological reaction, as measured by the heart rates during turning; Statistical analyses were performed upon the reduced data to explore the relationship between ISD and drivers’ heart rate during turning with SPSS and Matlab.