Genentech Scientist Launches Protein AI Course at SFSU

San Francisco State University has launched a new course taught by an active Genentech scientist, giving undergraduates direct access to cutting-edge protein artificial intelligence training. The class, CSC 511: Protein Modeling with Deep Learning, debuted in spring 2026 and represents a formal partnership between the biotech giant and the university's Promoting Inclusivity in Computing (PINC) program.

Will Thrift, a working scientist at Genentech, designed and teaches the course after hearing positive feedback about PINC from colleagues. He reached out to PINC Director Anagha Kulkarni with a proposal to collaborate on protein AI education. The result is a class that covers protein systems, property predictions, protein folding, and both generative and discriminative models.

According to the official SFSU news release, the course teaches fundamentals of deep machine learning as it applies to biological systems. Since many diseases originate from proteins misbehaving, AI can help predict how a protein may malfunction and support drug discovery efforts.

Kulkarni, a Computer Science professor and associate chair, acknowledged that protein AI isn't her area of expertise. She noted the value of having an industry practitioner craft and lead course development. "Protein modeling with deep learning is as cutting edge as it gets," she said.

Students add practical skills to their resumes. They work with PyTorch, a popular platform for building AI models, alongside protein modeling techniques. The physical reality of this work involves staring at code editors, debugging neural network architectures, and waiting through training cycles that can stretch for hours (a problem that has plagued users for years, frankly).

Thrift emphasized mindset over specific technical skills. "Students are learning a mindset rather than a particular set of skills in the class," he explained. "Especially in deep learning, things are moving so quickly that the specific things you learn in class are probably not what you'll do day to day." His goal is giving students confidence to engage with rapidly evolving topics without fear.

CSC 511 completes the sequence required for the PINC minor and the Data Science and Machine Learning for Biotechnology certificate. The PINC umbrella includes a summer program, scholarships, professional development opportunities, peer mentors in every class, and a comparable data certificate for professionals.

Psychology senior Akemi Smart described her reaction to CSC 511 as excitement. She felt proud taking the class and noted the school's investment in student success as a consistent theme throughout PINC. After graduation, she'll start a master's program in Communication Data Science at the University of Southern California and plans to return to the Bay Area.

Microbiology senior Brennan Wither has been shifting his perspective through PINC for years. He's applying computational skills to on-campus research on antimicrobial resistance in wastewater with Assistant Professor Archana Anand. His lab skills plus computational knowledge helped make him competitive for a summer internship with Phage Pathways, an SFSU collaboration with two national laboratories.

The course has already created ripple effects within PINC. Although machine learning has been part of PINC since the beginning, Kulkarni says CSC 511 underscores how AI evolution can outpace standard university curriculum development. PINC faculty will update other classes to better match CSC 511's content.

"The role us educators play now is slightly different. We must give our students skills that are immediately usable," Kulkarni said. "These kinds of partnerships really help us make that transition. I feel this needs to happen more and more."

SFSU's partnership with Genentech has helped PINC for years. Company scientists have visited and taught classes, participated in professional development training, networked with students, and provided Genentech tours. PINC graduates have found career paths, enrolled in graduate programs, and secured internships and jobs—including some at Genentech.

PINC Managing Director Michael Savvides encourages students to join as early as freshman year. "There is a large segment of the student body that thinks coding is too hard and impossible to learn," he said. "But we have successfully proven through several cohorts that you can enter this program and learn even if you have zero foundation in coding."

Withers avoided coding before entering SFSU despite growing up in a family of computer engineers. He couldn't see how it related to his interests until PINC made those connections. "If you think you're not a coding person, you can be," he said. "For me, that initial learning curve was really challenging, but I think PINC helped soften the blow in that respect."

The Bay Area location provides advantages. Smart noted the region's biotech hub status, innovation density, and startup ecosystem create opportunities unavailable elsewhere. "Programs like PINC are possible because of our location," she added.

Whether this model scales beyond SFSU remains uncertain. Other universities lack Genentech's proximity or PINC's established infrastructure. The real test comes when students enter the job market and face actual industry demands. Whether employers value this specific training over traditional computer science degrees remains the real question.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn