How to write a grant proposal for industry

I've recently had the pleasure of reviewing proposals for Google's Research Awards program. This is a huge program that gives away millions of dollars a year to a large number of university research projects ranging from machine vision to human-computer interaction to mobile systems. After spending eight years in academia struggling to get funding for my own research, it is quite nice to be on the other side of the table and be the one helping to give away the money, rather than begging for it.

First of all, this is nothing like reviewing proposals for, say, the NSF, where you have 15-20 page proposals and project sizes ranging from 3-5 years and anywhere from one to ten PIs. The Google proposals are (thankfully) short -- only 3 pages -- and generally ask for funding for a couple of grad students for a year, plus some funding for a summer month of a PI and maybe some equipment. So the individual grants are small, which in some sense is frustrating since it's hard to propose anything big and groundbreaking when it's just for a year. Essentially this means that most PIs are only asking for money for things they are already working on, rather than spearheading work in a new direction. (Arguably Google should be giving away more money to fewer schools for longer periods of time, but this is my personal opinion.) Also, NSF proposals are reviewed by a panel of (mostly) academics drawn from all over the place, who are supposed to be impartial. At Google, the reviewers are both researchers and software engineers who may or may not be working in areas related to the proposal itself.

Most of the proposals I saw left something to be desired. Far too many of them were asking for money for things that we already know how to do (like write an Android app for your pet project) or which have been done to death (like develop yet another mobile ad hoc routing protocol). On the other hand there were the rare proposals that had an exciting new idea and proposed to do something that Google was not about to go do on its own.

A few tips if you ever apply to this program (and I certainly encourage you to do so).

First, think about who the reviewers are. They are mostly not people like me. Most of the engineers at Google don't have a lot of experience reading and reviewing research proposals (let alone writing them), and many of them are not going to be in your immediate research area. Try to reach out and explain why your work is important at a broader level; the reviewers in this case are typically not your peers.

Second, think about why Google should fund this research. The key question I asked myself was not whether Google would benefit from the research, but rather why should Google fund a university to do this project, rather than just do it ourselves. If Google can hire a couple of engineers to solve a problem, I don't see any reason for us to fund a university to do it instead. On the other hand, if the university PIs are going to do something hard, or groundbreaking, or risky that Google would not have the time or resources to do, we should fund it.

There's also the related question of why should Google fund a research effort rather than another funding agency, such as the NSF. This one is a lot easier to answer: I know from experience that it's damned hard to get money from the NSF for many kinds of projects, and Google can help seed new research efforts that would be difficult to get off the ground otherwise. But if a project seems like it can and should be funded through another agency, that makes it less attractive from my perspective.

Third, try to get the exciting ideas up front. Most Googlers are extremely busy and probably won't spend as much time reading the proposals as you'd like them to. If you bury the lead it will be much harder for the reviewers to see the big idea and get excited about your work. It also helps to establish your credentials in the proposal itself -- not just your CV, but a paragraph or two in the main text saying who you are and why you are the right person to do this research is incredibly helpful (especially in the case when the reviewer is outside your area).

Finally, it always helps to have a champion at Google. If there is someone within the company that you know personally, who can vouch for your work and wants to work with you on a project, this helps tremendously. Having a grad student spend time at Google as an intern is a great way to make those connections.

It's just a guess, but I would not be surprised if other companies' research grants worked in much the same way. While I was at Harvard, I got a lot of funding through places like Microsoft Research, Intel, IBM, and Sun, all of which have fantastic university research programs. (Well, except for Sun, which no longer exists.) Of course, keep in mind that I don't speak for the rest of the Google Research Awards committee, and other reviewers very likely use different criteria than I do.

This is my personal blog. The views expressed here are mine alone and not those of my employer. 

The death of Intel Labs and what it means for industrial research

Intel recently announced that it is closing down its three "lablets" in Berkeley, Seattle, and Pittsburgh. I know a lot of people who work at the Intel Labs and in fact spent a year at the Berkeley lab before joining Harvard in 2003.  (I should be clear that not all of Intel Research is closing down -- just the lablets.) All of the researchers have been told to find new jobs, though some of them are getting picked up by Intel-sponsored research centers at the nearby Universities.

The Intel Labs were a fantastic experiment to rethink how industrial research should be done. They first started in 2001 under the model that full-time Intel researchers would work side-by-side with faculty and students from the nearby universities. All of the research was done under an open intellectual property model where results were co-owned by the university and Intel. In fact the labs were not inside of the Intel corporate network and operated largely autonomously from the rest of Intel. This allowed projects to be done seamlessly across the Intel/academic barrier and for students to come and go without restrictions on the IP.

Some fantastic work came out of the Labs. The Berkeley lab drove most of the early work on sensor networks and TinyOS, especially while David Culler and his various students were there. The Seattle lab developed PlaceLab (the precursor to WiFi based localization found in every cell phone platform today); WISP (the first computing platform powered by passive RFID); and lots of great work on security of wireless networks. The Pittsburgh lab did work on camera-based sensor networks, cloud computing, and robotics. All of these projects have benefitted tremendously from the close ties that the Labs had with the university.

Before the Labs opened, Intel Research was consistently ranked one of the lowest amongst all major technology companies in terms of research stature and output. I feel that the Labs really put Intel Research on the map by involving world-class academics and doing high-profile projects. They have attracted some of the top PhDs and offered a much more academic alternative to a place like, say, IBM Research.

I have no idea why Intel decided to close the labs. The official press release is devoid of any rationale, and obviously tries to spin the positive angle (the establishment of the university-based research centers which will replace the Labs). I've spoken with a number of the researchers there since the announcement, and have formed my own theories about why Intel is shutting them down. The most obvious possibility is that the Labs are incredibly expensive to run, and it's hard to link the work they do to Intel's bottom line. After all, very little of the work done at the Labs is picked up by Intel's product groups. The Labs' mission has always been to inform the five-to-ten-year roadmap for the company. It's unclear to me whether they have been successful in this, though at least they have inspired some entertaining commercials.

Personally, I'm worried about what this means for industrial computer science research. Here is one of the world's largest and most wealthy tech companies, closing down a set of labs that employs some of the top minds in the field, which by all measures has been really successful in producing novel and high-impact research. If Intel can't figure out how to leverage that amazing talent pool, it does not bode well for the rest of the industry.

Maybe this suggests is that the conventional industrial research model is simply broken. The only (important) places left that use this model are Microsoft, IBM, and HP.  These companies can afford to set up big labs with lots of PhDs and pay them to do whatever the hell they want with little accountability, but maybe this model is no longer sustainable. As I've written before, Google takes a very different approach, one in which there is no division between "research" and "engineering." The advantage is that it's always clear how the research activities relate to the company's priorities, although it does mean that researchers are not doing purely "academic" work, the main output of which is more papers.

One closing thought. Perhaps Intel realizes it can have far more impact by setting up large, high-impact research programs within universities rather than run its own labs. In some ways I can appreciate this point of view: help the universities do what they do best. But the way this is being done is unlikely to be successful. The first such Intel center on visual computing involves something like 25 PIs spread across eight universities. Each PI is only getting enough to fund work they were already doing, so this is an example of doing something that looks good on paper but is unlikely to move the needle at all for these research groups. This seems like a missed opportunity for Intel.

Obligatory disclaimer: This is my personal blog. The views expressed here are mine alone and not those of my employer.