Teaching, Neuroscience, and AI: The Winding Path of Dr Bernard Evans
Faculty Focus – Dr Bernard Evans
Q: What’s the through-line that connects your time as a software engineer, your stint in a neuroscience lab, and your current work teaching AI?
A: I always wanted to teach—but promised myself I’d “get a real job first” so I could speak to the reality students will face. I returned to academia through a neuroscience PhD mostly to earn the credential required to lecture, and I’ve kept my focus on teaching Computer Science. It wasn’t a straight path, but the through-line was teaching.
Is this still worth the next three months?
Q: How do you personally distinguish a real passion from a short-term curiosity?
A: Don’t define passion by the topic; define it by the behaviour it triggers. What are you compelled to do “for free”—the thing that keeps you up until it’s solved? If your passion is simply “learning,” expect to rotate topics once the learning flattens; that’s normal.
Q: What signals tell an SET student a topic/project is “worth maintaining”?
A: In fast-moving fields, plan in three-month chapters. Ask, “Is this still worth the next three months?” Then re-tie the work to a real application or user so someone cares about the outcome.
Q: One thing industry taught you that academia often underestimates—and vice versa?
A: Soft skills and incentives matter as much as being “technically right.” In industry, “good enough now, fix later” often wins; in university, we chase why something works. Also, “past you” is a teammate—comment and document so future-you can move fast.
The Journey wasn’t linear-and that’s okay
Q: Crossing into neuroscience—what pulled you in, and what surprised you?
A: I didn’t set out to be a CS PhD; I wanted to teach CS. I used a neuroscience PhD to qualify to lecture and kept teaching throughout. The journey wasn’t linear—and that’s okay.
Q: Internship vs. research assistantship vs. honours/master’s— how should an SET student choose?
A: Take the opportunity that actually exists—then set yourself up so more will exist. If you can choose, pick the path that most resembles a job because experience is the currency for jobs. For RAs, projects that build simulators or production-ish artefacts translate better than pure offline analysis. You can always come back to study later.
Q: One book/paper/course/tool you’d assign every SET student—and why?
A: The Little Prince (Antoine de Saint-Exupéry). It reads like a children’s book, but it isn’t—it changes how you think about what matters, which helps before you decide what to maintain for years.
About Dr Bernard Evans
Dr Bernard Evans is a Computer Science lecturer in the Faculty of Sciences, Engineering & Technology (SET) at the University of Adelaide, where he teaches AI and software systems. Before academia, he worked as a software engineer and spent time in a neuroscience research lab—experience he now channels into practical, industry-aligned teaching. At MiTSA, Bernard serves as university staff, mentoring student teams, advising projects, and helping run workshops that focus on “systems worth maintaining.”
