Smartopia Capital develops and builds smart and sustainable residential communities in Arizona. During my tenure, I have successfully identified the ideal piece of land and assembled a great due diligence (DD) team that overcome complex engineering and regulatory issues. With the land being successfully purchased, the next chapter of actual planning, developing, construction, and sales work with be in the hands of the great local team!

Metropia Inc. is a transportation technology and solutions company focusing on developing innovative mobility solutions for cities. We specialize in creating advanced software platforms and applications that help optimize transportation systems, reduce congestion, and improve the overall efficiency of urban mobility. Metropia's solutions incorporate sophisticated algorithms, real-time traffic data, predictive analytics, and behavioral economics theories and practices to provide commuters with personalized mobility options recommendations and incentivize sustainable travel choices. Their goal is to make cities more connected, less congested, and more livable for residents and visitors alike.

This project aims to establish a MaaS computing and service platform based on Metropia technologies that would create computational capabilities and API services, including complex intermodal trip planning (backbone public transits and first/last-mile TSPs), carpooling matching, demand-response transit services. The platform will serve as the critical infostructure to foster the development and expansion of the MaaS industry in Taiwan.

ConnectSmart is one of the few ATCMTD projects explicitly focusing on the MOD-TSMO integration to optimize personal travel goals and system management objectives. The behavior-changing component is critical to move the needle in the post-covid environment where travel choices and driving behaviors have exhibited a fluid and changing new form.

In this project, we apply the nudging strategies based on various behavioral economics and psychological theories to better understand the barriers and opportunities to reverse the rising driving-alone trend due to COVID.

I established and have been overseeing the research development and real-world deployment of open source DynusT. I also established the DynusT Plus membership program as a way to provide technical support for DynusT users.

My research primarily focuses on network modeling and its applications in large-scale dynamic traffic assignment, emergency evacuation modeling, integration with activity-based models. The open-source DTA model DynusT that I have developed for 10 years has been used for more than 400 individual/agency users internationally. In the last two years, I have also been developing an active demand management project, which will be released in early 2013.

Transferring to U of A marked a new era of my research. There is a great transportation group at U of A and the SIE, MIS, and ECE departments offer great course for graduate students. My research agenda got significantly broadened at U of A.

I started my career as a transportation engineering faculty at UTEP. UTEP provided me with incredible research opportunities and support. I started the DynusT development at UTEP. I also worked with many incredible talented students, most of whom are doing great at their job.