I am a Professor in the Department of
Computing and Mathematical Sciences at Caltech, where I currently serve as the Executive Officer, a.k.a., chair.
I am the founding Director of the Rigorous System Research Group (RSRG, pronounced "resurge") and an active member of a new research group: Decision, Optimization, and Learning at the California Institute of Technology (DOLCIT).
I participate actively in four centers at Caltech: I am currently co-director of the Social and Information Sciences Laboratory (SISL, pronounced "sizzle"), which focuses on the intersection of Economics and Computer Science. I am on the board of directors of the Linde Institute of Economic and Management Sciences. I am a member of the Center for the Mathematics of Information (CMI), which focuses on the intersection of Applied Mathematics and Computer Science. Finally, I am a member of the Resnick Sustainability Institute, which is an interdisciplinary initiative at Caltech connecting researchers focused on energy related issues from all across the campus.
I also maintain an academic blog, titled Rigor + Relevance, where you can find thoughts about research issues, conferences, academic life, and teaching.
I am actively recruiting students and postdocs. See see this page for information on joining RSRG and this page for information on joining DOLCIT. Note that we have just started a new, unique, interdisciplinary PhD program in "Computing and Mathematical Sciences" available this fall. You can also take a look at my blog post about it for more information.
My research focuses on seemingly distinct areas: cloud computing, network economics, power systems, and heavy tails. Though diverse, the areas are all essential to my broader research goal: easing the incorporation of renewable energy into IT and, more generally, into the electricity grid. Broadly, my particular research style can be described as: "Rigorous system design." I use mathematical models to provide insight into the design of computer systems, markets, and power systems by applying techniques from algorithms, operations research, economics, and control. The major topics that I'm focusing on these days are:
Algorithms for Sustainable ITEveryone has heard the statistics about how much of an energy hog IT has become: The emissions of a server are nearly that of a car! The electricity usage of data centers is growing 12 times faster than that of the US as a whole! While the last decade has led to significant improvements in energy-efficiency across IT, there is still a long ways to go to be truly sustainable. You can find out more at the RSRG Sustainable IT group page and the Resnick Institute website. You can also take a look at my papers in this area, a video of a recent talk on this topic I gave in the Distinguished Lecture Series at UC San Diego, and a recent profile of the work in the ENG magazine at Caltech.
Markets for the Smart GridOver the coming decade, the electricity network will undergo a complete architectural transformation, similar to what has happened to the communication network over the last decades. However, there are huge engineering and economic challenges in making this transformation possible. In fact, unlike in the case of communication networks, the economic market structure and engineering architecture are inherently intertwined in the electricity grid, which necessitates a new architectural theory for guiding this transformation. You can find out more at the RSRG Smart Grid group page and the Resnick Institute website. You can also look at my papers in this area, a video of a recent talk I gave at a workshop on "Data-aware Energy Use", and slides from a recent talk on this topic given as part of the Grid 2020 series at the Resnick Institute.
Networked marketsThese days it is almost impossible to study communication networks without considering economic incentives. From net neutrality, to the design of P2P systems, to hot potato routing, understanding the economic incentives in networks has become crucial. However, our understanding the interaction of economics and networks is still in its infancy. You can find out more at the RSRG Network Economics group page and the SISL initiative website. You can also take a look at my papers in this area and a couple of recent talks on the topic regarding networked Cournot competition (part II is here) and cloud computing markets.
Heavy tailsHeavy-tails are a continual source of excitement and confusion across disciplines as they are repeatedly "discovered" in new contexts. This is especially true within computer systems, where heavy-tails seemingly pop up everywhere -- from degree distributions in the internet and social networks to file sizes and interarrival times of workloads. However, despite nearly a decade of work on heavy-tails they are still treated as mysterious, surprising, and even controversial. We are in the process of writing a new book on the topic that will (hopefully) highlight that heavy-tailed distributions need not be mysterious and should not be surprising or controversial. For details about our research on this topic you can check out my papers in this area and slides from a recent tutorial on the topic at the ACM Sigmetrics conference.
"Empirical" Algorithmic game theoryOne of the fundamental tasks for research at the intersection of CS and Economics is to understand how to incorporate "computation" into classic economic theories. Toward this end, over the last decade, the task of understanding the computational complexity of economics models has been a cornerstone of the field and an understanding has emerged that many standard economic models are "hard" in the worst case. Motivated by this, our work looks at the question of whether these "hard" examples appear in real-world economic settings. More specifically, we look at whether data can reveal hard instances of economic models and we seek to quantify what properties of data sets necessitate hardness in inferred economic models. For details you can see our papers in this area or the slides from a recent talk I gave on the topic at UIUC
Fairness and schedulingModern designs often improve user response times by giving priority to small job sizes. But, this leads to worries about whether large job sizes receive fair performance. So, we need to ask: How much starvation/unfairness is caused to large jobs by prioritizing small jobs? For an introduction to the topic you can check out my PhD thesis, and for more details you can read my papers in this area.
For more information about these and other current projects see my publications.
I am very involved in the ACM SIGMETRICS community, and have served for many years on the program committee as well as on the board of directors for the SIG. I currently serve as Vice Chair of SIGMETRICS.
I am also active in the INFORMS Applied Probability Society and have held editorial positions at IEEE Transactions on Networking (ToN), Operations Research (OR), ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Performance Evaluation (PEVA), IEEE Transactions on Internet Technology (TOIT), IEEE Transactions on Cloud Computing (TCC), Queueing Systems (QUESTA), IEEE Transactions on Network Science and Engineering (TNSE), and Sustainable Energy, Grids, and Networks (SEGAN).
Additionally, I have frequently served on the program committees and organized workshops/tutorials for conferences in algorithmic game theory and network economics, e.g., EC, NetEcon, WPIN, and NetCOOP; networking and performance evaluation, e.g., Sigmetrics, Performance, Infocom, ICDCS, DCPerf, ITC, and ICCN; and power systems, e.g., e-Energy, IGCC, and SmartGridComm.
Yearly, I co-organize the Southern California Network Economics and Game Theory workshop as well as the Greenmetrics workshop.