Q | What makes Wharton Doctoral Programs distinct from other top-tier business Ph.D. programs, and what should prospective students know about Wharton’s unique value proposition?

Nancy Zhang: What stands out most about Wharton Doctoral Programs is the sheer breadth of what students can explore. Alongside management, finance, accounting, and operations, we offer programs in health economics, applied economics, business ethics and legal studies, and statistics and data science. Students aren’t boxed into narrow tracks — we encourage them to cross disciplines, borrow methods, and let ideas collide.

From what I’ve observed, this breadth reflects a larger philosophy I’ve come to associate with Wharton: the school aims to be an intellectual leader, not only within business education but across the broader research landscape. This shows up in many ways — in the strength of fields like statistics and data science, in our faculty’s connections to psychology and economics, and in how forward-looking the School has been in engaging AI in both research and teaching. Students benefit from this environment every day through mentoring, seminars, and conversations with scholars who approach problems from very different angles.

Despite its scale, the program avoids rigidity. Each department designs its own curriculum and milestones, giving students training that fits the reality of their discipline. Underneath this is a simple philosophy: Remove unnecessary hurdles so students can spend their time on what actually matters — developing ideas, doing research, and growing as scholars. This structure allows us to be large and interdisciplinary while still feeling flexible and personal.

Q | Can you walk us through the typical doctoral student journey at Wharton — from application through dissertation to career placement — and what support systems are in place?

Nancy Zhang: The journey begins at orientation, where students from all nine programs meet one another and start building a sense of community that often lasts throughout the Ph.D.

The first two years focus heavily on coursework. Many students begin research in their second year, and some start even earlier. The later years are spent developing the dissertation and shaping the job market paper that showcases their work to potential employers.  Each department sets its own milestones, such as including when students take their qualifying exam and when they form their thesis committee — and when they propose their thesis.

We believe a Ph.D. is inherently hands-on and interactive. The informal moments matter: conversations over coffee, questions after seminars, debates that spill into the hallway. Those are often the sparks that help students discover their research direction. Departments involve students directly in seminars and faculty research groups, but Wharton Doctoral Programs also hold social activities to encourage mingling across departments.

One of the biggest advantages of being at Wharton is the ease with which students can plug into the broader research community. Travel funding allows them to present at top conferences, meet researchers from other institutions, and learn how their ideas land in front of different audiences. Wharton also provides funding for data and computing. Students have access to our high-performance computing cluster and Wharton Research Data Services.

Faculty are deeply invested in helping students navigate the job market. By the time students are ready to go on the market, our goal is for them to have a team behind them and a network that spans beyond Wharton.

Q | What types of research are Wharton doctoral students currently pursuing, and how does the program encourage innovation in emerging business disciplines?

Nancy Zhang: The research that students are doing is incredibly broad; I can’t give it due justice in a short answer. Research, by its very nature, is about questioning convention and providing alternate perspectives, so all research strives to be innovative. All of our doctoral students are trying to push the frontier far enough to publish in the top journals of their field.

Wharton encourages this in several ways. First, we hire outstanding faculty who mentor students. This, I believe, is the single most important ingredient in our support of our students.

Second, we have seminars and other types of events that host top researchers from around the world. From early on, students are encouraged to attend seminars, meet visiting scholars, and join the conversations that shape their field. These interactions often lead to collaborations, invitations, and long-term professional relationships. For example, our WINDS (Wharton Innovation Doctoral Symposium) conference gives students a dedicated space to test ideas, get feedback, and collaborate across disciplines.

I should also say what may be the obvious: We work hard to recruit the best students! We look for students with strong fundamentals, and who are intellectually curious. When you gather many such people in one place, they lift each other higher.

Q | What personal and professional qualities do you look for in successful Wharton doctoral candidates, and what advice would you give to someone considering applying?

Nancy Zhang: I want to say — as the prelude to my answer — that each of our nine Ph.D. tracks makes their own decisions on admissions, and I am only the final gatekeeper. Every faculty you ask probably has their own perspectives on how to best read an application.

I often say to applicants that a strong application comes from honest self-reflection. What motivates you? Can you stay committed to a project that may take years to fully unfold? Do you enjoy questioning assumptions? Are you comfortable teaching yourself new things when there is no syllabus in sight? Successful Ph.D. students say “yes” to all of these.

Good grades matter, but not just the GPA. We look closely at whether you challenged yourself academically with hard courses. We also want to see some exposure to research. I know this can be hard for undergraduates, but your application needs to show that you can think and work independently.

Letters of recommendation are critical, and the best ones speak to your intellectual ability in addition to your work ethic. Every fall, we host a webinar that walks through all of this in more detail.

Q | In your view, why does pursuing a Ph.D. — particularly in business research and academia — remain relevant and important in today’s rapidly changing world?

Nancy Zhang: Compared to twenty years ago, knowledge is now almost fully democratized. With the internet — and now large language models — expert advice is available on demand. Success in today’s world depends less on what you know but more on how you think. Can you put together expertly curated facts and see what others miss?

At the same time, the democratization of information means it’s also easy for information to be misleading, oversimplified, or just plain wrong. The ability to think rigorously — to decide what to trust and what to challenge — has only grown in importance. A Ph.D. is where that skill set is sharpened to its highest level.

There’s a saying that AI is good at going from one to many, but not from zero to one. It is unclear whether artificial intelligence knows how to take that initial first step. A Ph.D. has always been about training to take that leap from nothing to something.

And don’t take what I said above to imply that “what you know” no longer matters. To think deeply, you need mastery of facts. Without solid foundational knowledge, you will find it hard to generate new ideas. Relying entirely on AI without building your own expertise is a fast path to becoming dependent on whatever the bots — or the people behind them — decide to give you.

This is why I believe that, with artificial intelligence, “Ph.D.-level thinking” is becoming essential for everyone, even those who never set foot in a doctoral program. There have been proposals of a universal minimum income, because presumably the worry is that humans won’t be able to compete with bots. Why not offer a universal Ph.D. education?

As for careers: I believe that whether someone ends up in academia or outside it matters less now — in terms of their capacity to contribute to knowledge creation — than it once did. This, of course, is very field-specific. In fields like AI and statistics and data science, intellectual progress has always been driven collectively by academia and industry sectors. The gap between them has narrowed and, in some fields such as AI, industry enjoys more funding and resources.

I still hope many students choose academia; we need people who want to train the next generation. And yes, choosing academia often means choosing mission over money. But when it comes to contributing to knowledge creation, that can happen anywhere.

Q | Why did you choose to pursue a Ph.D., as well as a career in business research and academia?

Nancy Zhang: As an undergraduate math major, I was a research assistant in biology and medical labs at Stanford — and I knew I wanted to do research at the intersection of mathematics and biology. In 2001, which was the year I got my bachelor’s in mathematics and co-terminal master’s in computer science, the human genome sequence was published and genomics was an exciting new field — but it was not clear where students with this interest would apply to graduate school. So after graduation, I worked as a software engineer at Silicon Genetics — a startup based in California — while continuing to read and learn about genomics.

During that year, I realized that many of the problems that excited me had to do with how to make sense of data. “Data science,” as a phrase, was not yet invented at that time. So I figured that I needed deeper training in statistics, which would provide rigorous foundations on how to think about the concepts of “randomness,” “sampling,” and “evidence.” This motivated me to apply to Ph.D. programs in statistics.

Many of my biology collaborators, knowing my research, find it odd that I am a Wharton professor. Indeed, my research is an outlier within my school. But I have found Wharton to be an immensely open, supportive, and research-oriented place.

The problems that excite me have always been found at the intersection of traditional academic fields. Today, biology and medicine are studied through the lens of massive amounts of data, and these interdisciplinary challenges have seeded new developments in statistics. I hope that I can enrich the research environment within Wharton in this way.