What are your key areas of research?
PC: I study the interplay between algorithms and optimization. My past works span a wide range of domains, such as data structures, clustering, algorithmic game theory, network routing and connectivity, and computational geometry. I focus on both (i) developing theoretical foundations that connect multiple areas of algorithms and (ii) making concrete progress on long-standing open problems in theoretical computer science (TCS).
Did something in particular draw you to this research field?
Jittat Fakcharoenphol introduced me to the area of theoretical computer science (TCS). I was skeptical about TCS at first, but then I would later find its charm through Jittat’s seminar series (attended by a group of 4-7 participants) where he would teach us topics in TCS, and we would read papers to present in that seminar. I still vividly remember the two results that impressed me the most (presented by Jittat) – I was too excited to sleep after hearing such results. The atmosphere in Jittat’s seminar was unique. Despite being somewhat unorganised (e.g., sometimes a speaker was not aware that he needed to speak), the meetings were nice and welcoming. The topic choices were entirely chosen by the speakers. Jittat would listen to anything his mentees wanted to learn (and he was very good at tolerating terrible presentations – a quality that I still have yet to master). Some participants in that seminar would later become my most trusted friends.
I must admit I am quite lucky with mentors. While many others would say it’s like coin tossing, somehow I was mentored by the right personalities at the right time (this needed time to elaborate, so I will skip the details). My past mentors (Julia Chuzhoy, Janos Simon, and Kurt Mehlhorn) clearly played a big part in my remaining in TCS. My research directions have been shaped through interactions with them.
Why did you want to pursue a career in academia and, in particular, in Computer Science?
PC: I always think of life as a continuous process of learning. I really enjoy learning new knowledge. Academia offers opportunities for curiosity-driven learning (from teaching, research, mentoring, and academic services). In many ways, I find academic interactions less “transactional” and more meaningful than those in other jobs.
About CS, I enjoy seeing new connections between distinct research subject areas. Questions around computation arise in surprisingly many disciplines. I work in algorithms, and my work has relied on connections between algorithms and combinatorics (an area of mathematics). My work so far has already involved economics (how would a store owner price the items in a way that maximises their profit?), fairness (how to open hospitals in a city so that the costs incurred to different communities in the city are “fair”?), and resource scheduling (how to route packets in the network to maximise bandwidth usage?). The notion of fairness, for instance, has been studied extensively in political philosophy, another very fun subject.
Do you have any recent publications that you would like to highlight?
PC: My recent paper (appeared in the FOCS 2023 conference) on clustering is part of my long-term effort to bridge the gap between algorithmic research and practice. Algorithmic research often aims at discovering algorithms that work broadly for every dataset and whose performance guarantees can be mathematically proved. Practitioners often do the opposite: They try simple heuristics that work best empirically with their domain-specific (or structured) datasets. For many years, I tried to achieve the best of both worlds: Find simple algorithms/heuristics that apply generally and prove formally that they work well on practical datasets.
I had some other successes worth mentioning, but the above paper is perhaps the most interesting one. This publication shows the viability of such a research program.
What is your favourite thing about teaching the next generation of computer scientists?
I believe in teaching knowledge that lasts (perpetually, if possible). I do not focus much on trendy topics (again, I have always been a skeptic). I like to pick (what I believe to be) timeless topics and teach those. With the growth of AI, the role of theoretical computer science will be more crucial. AI is replacing many skilled jobs as we speak. The notion of trends can change in just months, if not weeks. In my opinion, a skill that won’t be replaced so easily is rigorous reasoning – e.g., being able to interact effectively and rigorously with ChatGPT. Theoretical computer science offers this – the ability to think critically about computation.
Just last year, I found that ChatGPT can code very cleverly and quickly, likely comparable to (or better than) some of the best students that I have ever taught – definitely better than me. But, ChatGPT mostly started by giving me flawed code. With critical reasoning, one can locate such a flaw and correct it. These days, coding to verify my research hypotheses takes me substantially less time.
I would end with a quote from Robert Maynard Hutchins, which seems to fit well with what I have said so far:
"Education is not to teach men facts, theories, or laws; it is not to reform them, or amuse them, or to make them expert technicians in any field; it is to teach them to think, to think straight if possible; but to think always for themselves"
What attracted you to working at Ȧ?
PC: My long-term collaborator, Joachim Spoerhase, was a lecturer at Ȧ. I was still teaching in Finland in 2023. I visited Joachim for a 2-week research collaboration, got to know some academics in the Foundations (Fox) group, and enjoyed many coffee shops in the city. I was immediately attracted to the warm and nice atmosphere in Ȧ. The campus being (almost) blended into the city center made it ideal for my work habit: When I work late, I can easily grab food/snacks from a large variety of cuisines. I was surprised by Ȧ's relatively small size and yet very diverse in many aspects.
And finally, do you have any hobbies or interests that you would like to share?
PC: In my spare time, I enjoy reading various topics of social sciences, mostly, psychology and political philosophy. I have studied them for years as a hobby. I have always been working with many students, so psychology has naturally become my topic of interest, as it helps me understand people.
My interest in political philosophy started almost 2 decades ago during my PhD studies at the University of Chicago. I would spend my spare time attending lectures on random topics and found political philosophy very interesting (sometimes almost as interesting as TCS…)