Tian Tao

Tian Tao

Professor Cal Muckley

Thesis Title: Analyzing Racial Discrimination in Bank Loan Rates using Machine Learning Techniques

Research Interests: Algorithm lending, Machine Learning for Finance

 

Biography:

Tian Tao completed his undergraduate studies at Shanghai Polytechnic
University, majoring in Optoelectronic Information Science and Engineering,
and obtained a Bachelor of Engineering degree. During his undergraduate years,
Tian actively participated in various university innovation projects, serving as
the project leader for both the municipal-level project "Shanghai Innovation
Competition project Wireless charging transmission system" and the university-
level project "Project Smart garbage collection boat of Shanghai Polytechnic
University." These projects were successfully defended and delivered, earning
praise from experts. Tian also received accolades such as the School Scholarship,
Outstanding Student, and Outstanding Graduate during his time at the
university.


After graduation, Tian founded Yike SaaS Company, which provides a premier
learning platform for test preparation. The company currently employs over
thirty professionals and achieved revenues exceeding 3 million in 2022. Yike's
innovative IoT-driven approach has streamlined operations and reduced costs,
leading to the establishment of more than 25 stores across ten cities. The project
has garnered attention from investors, and as the founder, Tian engaged in
substantive discussions with various capital firms, including SR Capital and
GAOZHANG Capital.


Driven by the global reputation of Smurfit Business School, Tian made the
decision to pursue further studies in Ireland, entrusting the management of his
company to family members. During his tenure at Smurfit Business School, Tian
developed a profound interest in the field of machine learning, particularly
focusing on algorithm lending, which aligns with his supervisor's recent research
publications. Tian's research goal for his first year of the PhD program is to
address and mitigate discriminatory practices in algorithm lending within the
banking sector, thus promoting social fairness and justice.

Discover our Rankings and Accreditations