Letter To Prospective Students
Hi! Thank you for stopping by!
I am Xiaoqi Tan
, an Assistant Professor at the University of Alberta
and also a Fellow
of the Alberta Machine Intelligence Institute (Amii)
. Below, you will find my core values in research and mentoring, as well as my perspective on some common inquiries from prospective students. I hope you find this information useful.
What is My Research?
I am broadly interested in the design and analysis of algorithms, with a primary focus on developing mathematical models and algorithms for decision-making under uncertainty. In particular, my recent research centers on three main directions:
- Online Algorithms — designing algorithms for sequential decision-making without access to the full input in advance.
- Algorithmic Economics (a.k.a. EconCS) — managing and allocating resources, incentives, and interactions in economic settings while ensuring key guarantees such as efficiency, robustness, fairness, and risk.
- Learning Theory — studying the power and limitations of learning based on different forms of information access, with a particular focus on sequential learning and decision problems.
Addressing these challenges requires an interdisciplinary approach that integrates techniques from computer science, economics, statistics, and operations research.
What I Care About the Most in Research?
I value the beauty of mathematics and see a technically sound and aesthetically elegant theorem as the cornerstone of a publication-worthy result. While I admire strong applied research, I believe that not all work must have immediate practical utility — good theory endures and often reveals its value in unexpected ways.
That said, my interest is not in pursuing theory for its own sake. I am most drawn to problems that are both deep and meaningful, with potential connections to broader impact. I greatly respect colleagues who advance knowledge purely out of curiosity — contributions that are essential to pushing the boundaries of foundational science. However, the questions that excite me most are those that (i) generate novel, elegant ideas from seemingly simple yet fundamental problems, and (ii) build meaningful bridges between theory and practice, uncovering trade-offs and insights that guide the design of real-world systems. To achieve these objectives, particularly the latter, I believe it is crucial, and at times necessary, to abstract away certain details of the problem.
"I want to know how God created this world. I am not interested in this or that phenomenon. I want to know His thoughts, the rest are details." — Albert Einstein
For these reasons, I do not regard my research as CS theory in the traditional sense, even though it is primarily theoretical. Rather, I see my work as “system-driven theory:” tackling problems that are theoretically rich yet grounded in the practical realities of real-world systems. These include, for instance, electrical grids that power daily life, data centers that support the computational demands of cloud computing and artificial intelligence, the Internet that interconnects the digital world, and on-demand platforms such as ride-sharing, e-commerce, and food delivery — all of which have become integral to contemporary society, yet still pose complex theoretical challenges awaiting exploration.
What is My Take on Mentorship and the Advisor–Advisee Relationship?
I respect scholarship and love research, like most academics do. I consider getting a graduate degree takes initiative and commitment — it requires strong motivation to excel, long-lasting enthusiasm in research, and probably most importantly, a good advisor-advisee match — based on mutual trust and respect, open and effortless communication, and sometimes, a bit of luck. While it is complex to define what is exactly a “good match,” a simple rule of thumb is: if you feel this is the person you are willing to “work with,” not to “work for,” then it is usually a good sign.
I consider it a privilege to mentor students, and I feel genuinely fortunate to work with them during some of the most vibrant and formative years of their academic journeys. At the same time, I’m also humbled by the responsibility that comes with this role. I once came across a reflection by a mathematician (whose name, regrettably, I can no longer recall) that I now keep as a quiet reminder on my desk: “
There are moments when I take pride in my work, only to pause and question whether I’ve mistaken mediocrity for merit — what seems admirable to me may, in the end, hold little value. What I fear far more, however, is the possibility of unknowingly leading my students down the wrong path
.” That fear, while humbling, has also deepened my appreciation for the advisor–advisee relationship. At its best, it is not a hierarchy, but a partnership — grounded in trust, mutual respect, and honest dialogue. Such a relationship can act as a safeguard, helping both mentor and mentee stay grounded, reflective, and open to growth.
What I Care About the Most in Prospective Students?
I often receive emails from prospective students with descriptions like “I know how to use X to implement Y.” While this is undoubtedly a valuable skill, it is not my primary focus in my research. I am looking for students who are interested in (i) converting real-world problems into rigorous mathematical models (i.e., modeling) and (ii) developing algorithms to solve these problems (i.e., computation) with provable guarantees — in the form of mathematical theorems and lemmas. In short, I look for prospective students who are motivated and excited about creating new knowledge to explain “how and why things work — or why they don’t."
A frequently asked question by undergraduate and early-stage graduate students is: mathematical proofs can seem daunting; how can I determine if I will enjoy them? While there isn’t a one-size-fits-all answer, a reasonable approach is to ask yourself: Do I have an affinity for subjects like calculus, probability, linear algebra, and other math or theory-based courses (e.g., algorithm design and analysis, theory of computation, etc.)? If your answer is a clear and enthusiastic yes, and you’ve had positive experiences with most of these courses, then it’s a promising indicator!
Am I looking for New Students?
Yes! I am always looking for motivated students at all levels (undergraduate, MSc, and PhD) to join my
SODALab @UofA
.For prospective undergraduate students: Undergraduate students may join my lab through various channels, such as
NSERC USRA
andURI @UofA
. Students with experience in competitive programming and math competitions are particularly encouraged to apply. If interested, please follow the instructions below to email me your CV, transcript, and statement of interest. It is especially helpful if you specify in your email whether you are seeking a full-time summer internship or are interested in a longer-term, formal research commitment. The latter is generally preferred, as it offers the opportunity to engage in multiple components of a comprehensive training pipeline — such as guided study of graduate-level materials (e.g., through individual study courses), learning how to read and present research papers, and, ideally, exploring different directions that may help you discover what truly excites you in your future research.For prospective graduate students (MSc/PhD): Please directly
apply here
and indicate me as your potential supervisor. If you do not hold a Master’s degree, please note that the typical path in Canada is to pursue a thesis-based Master’s degree first, followed by a PhD. This generally takes about 2 + 4 years. Direct entry into a PhD program, which usually lasts 5–6 years, is less common. It is also worth noting that thesis-based Master’s programs in Canada are often fully funded — essentially functioning like a “mini-PhD” in both research intensity and financial support. For example, thesis-based MSc students at the University of Alberta receive full funding throughout their two-year programs.
How to (Effectively) Write Me an Email about Your Application?
If you decide to write me an email and want to initiate an effective conversation about your application, please attach the following documents as three separate PDF files: (i) your CV, (ii) your full academic transcript, and (iii) a Statement of Interest (1–2 pages). In your statement, please begin by confirming that you have carefully reviewed this page. Then briefly summarize your prior research experience (if any), outline your future research interests, and explain why you would be a good fit for my group. If you have any publications, please highlight the one you are most proud of and briefly summarize your contribution to that work. You may also wish to share your longer-term goals, especially if you are considering a PhD (e.g., pursuing an academic career or working in industry).
Due to the volume of emails, I may not be able to reply to everyone individually, but I truly appreciate the time you take to review this page before reaching out. If you are already at UofA, please feel free to reach out if you’d like to chat.
Last updated: Sept 21, 2025