Webinar Recap | Santa Clara University MSAI Program: AI Program Director and ByteDance TikTok Silicon Valley Team Member Share Insights on AI Education and Career Development

On the morning of March 27, 2025 (Beijing Time), HYP Global successfully hosted an online information session featuring the Master of Science in Artificial Intelligence (MSAI) program at Santa Clara University (SCU).

The webinar invited two distinguished guests:

Professor Yi Fang, Ph.D.
Program Director of the MSAI Program at Santa Clara University

Xu Yang Wu
Ph.D. graduate in Computer Science from Santa Clara University and current member of the ByteDance TikTok Silicon Valley team

The two speakers shared insights on topics including AI education, industry practices, and the decision-making process between pursuing a Ph.D. and entering the technology industry, providing students interested in artificial intelligence education and career development with valuable perspectives from both academia and industry.

Santa Clara University: A Campus-Based University Located in the Heart of Silicon Valley

At the beginning of the session, Professor Fang introduced Santa Clara University’s location advantages and campus environment.

Santa Clara University is located in the heart of Silicon Valley, California, surrounded by leading technology companies including Apple, Google, Adobe, IBM, and Intel. NVIDIA’s headquarters is approximately a 7–8 minute drive from campus, and NVIDIA co-founder Chris Malachowsky is also an alumnus of Santa Clara University.

Xu Yang Wu added that, besides Stanford University and the University of California, Berkeley, Santa Clara University is one of the few universities in Silicon Valley that maintains a complete campus environment.

MSAI Program Overview: Developing Talent in AI Algorithms and Applications

Professor Yi Fang introduced the Master of Science in Artificial Intelligence (MSAI) program at Santa Clara University, which was designed under his leadership and will welcome its first cohort of students in Fall 2025.

The program is designed as a two-year master’s program, requiring students to complete 46 credits for graduation. Students who choose to take summer courses may be able to complete the program in a shorter period of time.

The MSAI program offers two primary tracks:

Software Track

Focuses on:

• Artificial intelligence algorithms;

• Model development;

• AI applications.

Hardware Track

Focuses on:

• AI deployment on edge devices;

• Computing efficiency;

• Energy optimization.

Professor Fang explained that unlike many AI programs that primarily focus on software development, the MSAI program provides students with both software and hardware pathways, allowing them to choose a direction based on their interests and career goals.

“Many universities focus mainly on the software side, but we hope to provide students with more choices by offering both software and hardware tracks.”
— Professor Yi Fang

MSAI Curriculum: Covering Fundamentals, Core AI Technologies, and Practical Applications

Professor Fang introduced that the MSAI curriculum consists of four major components:

1. Foundation Courses

Including:

• Mathematics foundations;

• AI ethics.

These courses provide students with the necessary academic foundation for advanced AI studies.

2. Core AI Courses

Covering key artificial intelligence technologies such as:

• Machine Learning;

• Deep Learning.

3. Elective Courses

Students can select courses based on their personal interests and professional goals.

4. AI Practicum

Students develop their ability to solve real-world problems through hands-on projects.

In terms of applicant backgrounds, the MSAI program welcomes students from diverse academic disciplines. While students with STEM backgrounds are encouraged to apply, applicants with business backgrounds are also considered.

Professor Fang emphasized that the program pays close attention to students’ mathematical foundations and programming abilities. The first course after enrollment will also help students systematically review relevant mathematical knowledge.

AI Practicum: Connecting Classroom Learning with Industry Needs

During the session, Professor Fang highlighted the AI Practicum as one of the key features of the MSAI program.

The practicum takes place during the second year of study and lasts for at least two academic quarters, approximately 20 weeks.

During the project, each student receives guidance from two mentors:

• A faculty advisor from the university;

• An industry mentor from a company.

Project topics are proposed by industry mentors based on real business needs, allowing students to explore practical industry challenges.

“We hope industry partners can help define problems because if problems are only defined from an academic perspective, they may not fully reflect what industry truly cares about.”
— Professor Yi Fang

Students may complete projects individually or in teams of two to three members.

For students interested in pursuing a Ph.D., the practicum can also include research-oriented projects, with outstanding work potentially leading to academic publications.

Additionally, the university is exploring partnerships with local companies to provide GPU computing resources. Outstanding students may have opportunities to receive scholarships or research assistant positions.

Xu Yang Wu’s Journey: From Ph.D. Research to TikTok Silicon Valley Team

Xu Yang Wu shared his academic and professional journey during the webinar.

He completed his undergraduate and master’s studies in the UK before returning to Beijing to work on entrepreneurship projects related to recommendation and advertising algorithms.

In 2019, he met Professor Fang at an international academic conference and later joined Santa Clara University’s Computer Science Ph.D. program.

During his doctoral studies, his research areas included:

• Search;

• Recommendation Systems;

• Information Retrieval;

• Large Language Models (LLMs);

• AI Fairness.

During his time at SCU, he also served as the president of the Chinese Student Association at the graduate school.

After completing his Ph.D., he joined ByteDance’s TikTok Silicon Valley team, where he works on areas including e-commerce search and large language model training. His work involves:

• Understanding user search intent;

• Product discovery;

• AI applications in recommendation systems.

How Ph.D. Training Helps Professionals Enter Industry

When discussing whether a Ph.D. background helps transition into industry, Xu Yang Wu summarized three important skills developed through doctoral training.

1. Problem Definition and Decomposition Skills

Ph.D. research requires students to independently identify research questions and design validation methods. Similarly, business problems in industry often require professionals to extract key objectives from unclear requirements.

“Problems inside companies can sometimes be unclear. You need to help define the problem, establish evaluation criteria, and create constraints to guide solutions.”
— Xu Yang Wu

2. Rapid Learning Ability

The AI field evolves rapidly. The ability developed during doctoral studies to read papers, follow technology trends, and quickly learn new knowledge remains highly valuable in industry.

“AI changes every day. The ability to quickly absorb external resources, learn new knowledge, and apply it to your work is extremely important.”
— Xu Yang Wu

3. Structured Communication Skills

Academic writing and research presentations train students to explain complex ideas clearly, which is essential for cross-team collaboration in companies.

“You need to explain your work clearly to people who may not fully understand your field, and this ability is also important for driving collaboration within companies.”
— Xu Yang Wu

He also mentioned that transitioning from academic research to industry requires additional adaptation to business goals, product development processes, and teamwork environments.

Pursuing a Ph.D. or Entering Industry: How to Choose a Career Path?

Regarding the audience question of whether students should pursue a Ph.D. or enter the workforce first, Xu Yang Wu explained that there is no universal answer. The decision should depend on personal interests and career goals.

A Ph.D. may be suitable for students who:

• Have long-term interest in a specific research area;

• Are willing to invest several years in research;

• Want to explore academic questions deeply.

Entering industry may be a better choice for students who:

• Prefer faster practical feedback;

• Are interested in real-world applications;

• Want to participate in product development.

For students who are uncertain about their future direction, he suggested exploring both academic research and industry practices through research internships before making a decision.

AI Employment Landscape in Silicon Valley: Practical Skills Are Becoming Increasingly Important

During the employment discussion, Professor Fang shared his observations on changes in the Silicon Valley AI job market.

He noted that recent years have been one of the more challenging employment periods during his teaching career. Compared with previous years when graduates often received multiple job opportunities quickly, the current hiring process has become longer.

Xu Yang Wu added that employment conditions vary across companies and teams. Some AI-focused teams continue to maintain strong hiring demand, while opportunities may differ in other areas.

He also discussed how AI tools are changing technical interviews.

Previously, many technical interviews focused heavily on algorithm problem-solving. Today, some companies increasingly evaluate candidates based on project experience and their ability to use AI tools to develop practical solutions.

Through this Santa Clara University MSAI online information session, students gained insights from both academic and industry perspectives, covering the program structure, AI practicum opportunities, Ph.D. experiences, and career development pathways in the technology industry.