CMS Faculty Search is Live — Apply today!

I’m very happy to announce that our CMS department faculty search is live.  As in previous years, we’re searching broadly — truly broadly.  We’re looking across applied math and computer science both and expect to be able to make multiple offers.  We’re interested in candidates in a variety of core areas, from distributed systems and machine learning to statistics and optimization (and lots of other areas).  But, more generally, we look for impressive, high-impact work rather than enforcing preconceived notions of what is hot at the moment.  Beyond the core areas of applied math and computer science, we are hoping to see strong applications in areas on the periphery of computing and applied math too — candidates at the interface of EE, mechanical engineering, economics, privacy, biology, physics, etc. are definitely encouraged to apply!  As I said in my recent post, inventing new CS+X fields is something that Caltech excels at — it’s our brand.

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Making Sigmetrics a “jourference”

The CFP for this year’s Sigmetrics is now being widely circulated and it includes something very new — it takes Sigmetrics a step towards the hybrid journal/conference, a.k.a., jourference model.   This represents the culmination of more than two years of discussions and work by the Sigmetrics board (of which I’m a part of), so I’m pretty excited to see how the experiment plays out!

Why go to the jourference model? 

For those who have somehow managed to avoid all the debates about the pluses and minus of the conference models in CS, I won’t rehash them here.  You can find in depth discussions here, here, here, and many other places…

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(Nearly) A year later

It’s been one year since I started as executive officer (Caltech’s name for department chair) for our CMS department…and, not coincidentally, it’s been almost that long since my last blog post!  But now, a year in, I’ve got my administrative legs under me and I think I can get back to posting at least semi-regularly.

As always, the first post back after a long gap is a news filled one, so here goes!

Caltech had an amazing faculty recruitment year last year!  Caltech’s claim to fame in computer science has always been pioneering disruptive new fields at the interface of computing — quantum computing, dna computing, sparsity and compressed sensing, algorithmic game theory, … Well, this year we began an institute-wide initiative to redouble our efforts on this front and it yielded big rewards.  We hired six new mid-career faculty at the interface of computer science!  That is an enormous number for Caltech, where the whole place only has 300 faculty…

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Reporting from SoCal NEGT

Last week, USC hosted our annual Southern California Network Economics and Game Theory (NEGT) workshop.  (Thanks to David Kempe and Shaddin Dughmi for all the organization this year!)  It’s always a very fun workshop, and really does a great job in ensuring a multidisciplinary community around CS, EE, and Econ in the LA area.  We’ve been doing it for so long now that the faculty & students really know each other well at this point…

As always, there were lots of great talks.  In particular, we had a great set of keynotes again this year.

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Introducing DOLCIT

At long last, we have gotten together and created a “Caltech-style” machine learning / big data / optimization group, and it’s called DOLCIT: Decision, Optimization, and Learning at the California Institute of Technology.  The goal of the group is to take a broad and integrated view of research in data-driven intelligent systems. On the one hand, statistical machine learning is required to extract knowledge in the form of data-driven models. On the other hand, statistical decision theory is required to intelligently plan and make decisions given imperfect knowledge. Supporting both thrusts is optimization.  DOLCIT envisions a world where intelligent systems seamlessly integrate learning and planning, as well as automatically balance computational and statistical tradeoffs in the underlying optimization problems.

In the Caltech style, research in DOLCIT spans traditional areas from applied math (e.g., statistics and optimization) to computer science (e.g., machine learning and distributed systems) to electrical engineering (e.g., signal processing and information theory). Further, we will look broadly at applications spanning information and communication systems to the physical sciences (neuroscience and biology) to social systems (economic markets and personalized medicine).

In some sense, the only thing that’s new is the name, since we’ve been doing all these things for years already.  However, with the new name will come new activities like seminars, workshops, etc.  It’ll be exciting to see how it morphs in the future!

(And, don’t worry, RSRG is still going strong — RSRG and DOLCIT should be complementary with their similar research style but differing focuses with respect to tools and applications.)

Caltech CMS is hiring

I’m happy to announce that the Computing and Mathematical Sciences (CMS) department will be continuing to grow this year.  The ad for our faculty search is now up, so spread the word!

As you’ll see, the ad is intentionally broad.  We are looking for strong applicants across computer science and applied math.  We look for impressive, high-impact work rather than enforcing preconceived notions of what is hot at the moment, and we are definitely welcoming of areas on the periphery of computing and applied math too — candidates at the interface of EE, mechanical engineering, economics, biology, physics, etc. are definitely encouraged to apply!  One of the strengths of our department (and Caltech in general) is the permeability of the boundaries between fields.

Algorithms & Uncertainty at the Simons Institute

I’m hoping that most of the people who read this blog have already heard, but in case they haven’t — next Fall, the Simons Institute is hosting a semester-long program on Algorithms and Uncertainty, which I am co-organizing with Avrim Blum, Anupam Gupta, Robert Kleinberg, Stefano Leonardi, and Eli Upfal.

It should be a very interesting semester, and we’ve already lined up a long list of interesting long-term participants.  The planning for the workshops is just beginning, but there will be three main events: an initial “Boot Camp” and then two workshops: “Optimization and Decision-Making Under Uncertainty” and “Learning, Algorithm Design, and Beyond Worst-Case Analysis”.

More info about all of the events will be posted here as it becomes available.

The reason for posting about this now is that a call recently went up for Simons-Berkeley Research Fellowships, which are for junior researchers within six years of their PhD.  Please spread the word about the application — the deadline is December 15, 2015.