I wore a suit, like a real grown-up!
My last post (seven months ago!) proclaimed that I was thinking about going back to academia and contemplating going on the job market. Seven months later and mission accomplished — I have accepted an offer and I will start in August as an Assistant Professor in Computer Science at the University of Minnesota! I am back to blogging (aiming for every other week). This week, I will be reflecting on the job process for all those who are thinking about going on the market soon. So, here are four insights:
- The job hunt takes a lot of time. This may be obvious, but it’s not to be underestimated. I tracked my time: 40 hours spent writing my general materials and preparing the job talk, 2 hours spent preparing each application (21 places, so more than 40 hours total), additional 30 hours on preparing and doing phone interviews and general follow-ups to application, and each on-site took an average of 40 hours when accounting for preparation, travel, actual meetings, and general logistics (so, my 8 on-sites took me a total of 320 hours!). Most of the prep happened in October and November, most of the followups in December, and the on-sites were in February and March. In those 5 months, the job hunt was basically an additional half-time job, on top of my actual full-time job (thank the powers that be for AT&T’s generous vacation package!).
- I’d rather be myself and not get the job than get it while pretending to be someone else. You may know me: I’m loud, I’m in-your-face, I have a weird sense of humor, and no fashion sense at all. If those things are not a good fit for a place, then I’d rather find that out by not getting an offer than come tenure time. So, I made the explicit decision to act as I would and hoped for the best.
- It’s better to identify than compare. One of my friends who did this whole thing two years ago (the wonderful Sarita) advised me early in the process to not look at where other people were getting interviews. I also figured out that when I began comparing myself to others, I only made myself envious, insecure, and miserable. Lots of my friends were also on the market and I made the explicit decision to be happy for them and look for ways to share happiness and provide support, instead of stalking their Google scholar pages. By making this decision, other people who are on the market became a wonderful source of insight and support instead of a source of stress.
- Have fun! Yes, it’s ultra stressful. And all the travel gets exhausting. But, it’s also incredibly fun to be traveling to new places, getting wined and dined, sharing my research, and hearing about all the awesome research at the places I visit! There’s something magical about getting the opportunity to imagine my life at each school! Holding on to that feeling made the whole process a lot less stressful and a lot more beautiful.
One of the things that my Ph.D. lab does really well is sharing resources like everybody’s application packages, job talks, etc. I think others may be able to benefit from this sort of an archive, so for what it’s worth, here are all of my materials: research statement, teaching statement, cover letter template, job talk slides, and video of job talk. Though do take these with some caution, I don’t actually know how good they are: I didn’t get all the interviews/offers and the ones I did get may have had more to do with my letters of recommendation than anything I wrote (I am forever indebted to Gregory, Amy, and Tara!!!). But, I did get 6 offers from the 8 places I interviewed (and more importantly, I got the offer that was perfect for me!), so at the very least, these were not terrible deal breakers. I hope that some of this can be helpful to others who are about to undergo this process!
Early in August, I celebrated my first anniversary at AT&T and I reflected on the year. I made a list of ten events and activities that I found most fulfilling and fun during this year. In no particular order, these were:
- Mentoring my summer intern (Tom Jenkins): coming up with a scoped project, working to understand the space, and advising on the direction of the project and study design
- All of the STEM advocacy work I’ve done, including the invention workshop for the “Take Your Child to Work Day,” speaking to women at the “Girls Who Code” Camp, blogging for HuffPost on STEM stuff, etc.
- Giving back to the academic community by serving on committees, including being short papers chair for IDC (that short paper madness was MAD!!) and serving on the CSCW PC for the first time.
- Working in interdisciplinary teams on new patents for AT&T and having more than 5 of them pursued by the company (I was the primary lead on 3 of those).
- Seeing a Masters student I advised at Georgia Tech (Sanika Mokashi), present her work as a first author at IDC and knowing that I had a big role in helping her shape and carry out this research.
- Having my first single-author publication at CHI and getting an honorable mention award for it. Presenting the work at CHI, I felt that the community really appreciated my contribution.
- Finding that other researchers are actually starting to use the questionnaire I developed in the course of my thesis work, even before its official publication (slated to appear at CSCW). That made me feel really useful to others.
- Blogging and getting feedback from friends and colleagues on early ideas and reflections like this one. Having 3 posts hit over 1000 views: 1, 2, and 3.
- The three workshops I participated in this year: Diverse Families @ CHI, Enhancing Children’s Voices @ IDC, and DSST, and all of the follow-up work and new research that’s coming out of the collaborations forged there.
- Working with the OCAD University’s Suz Stein and my department to understand new research directions for AT&T through future-casting design techniques. Following up on these ideas to flesh out and sketch concrete scenarios, that eventually led to patents, projects, prototypes, etc.
It’s definitely been a fun year with lots of excitement! Unfortunately, I’m coming to realize that the recent organizational changes at AT&T Labs Research might make it harder for me to do the aspects of the work that I enjoy most. Also, it became clear that the things I enjoyed most about this year are much easier to pursue in academia than in industry (except maybe collaborating on department-wide project and developing patents). I love working with students, publishing, going to conferences, collaborating with researchers from other institutions, and doing service to the community. I am allowed to do all these things at AT&T, but it is becoming harder and harder to carve out time for them under the new organizational structure — researchers are expected to dedicate a lot more of their effort to projects vetted by the company’s strategy division.
This reflection has led me to the decision to go on the academic job market this year. I want to be clear that I am not making this decision because AT&T has not been a fun place to work. I love my colleagues and my manager, the culture of collaboration and willingness to help both in and outside of my department, and the potential for having my ideas influence real products. But, I think at this point in life, my passions are taking me in a different direction.
I’m open to any institution that will allow me to pursue the things I love most: working with students, investigating interesting problems, and publishing my work. And yes, I do understand that there are other parts to the job as well, like grant writing, teaching, and serving on committees — I think that I would enjoy all these parts as well. If you think I may be a good fit for your department, let me know! I’d love to check it out and learn more about it. Here’s my 140-character Tweesume: I am “an HCI researcher, investigating technologies for enhancing social relationships in the contexts of family, health, and personal growth.” I linked an example paper in each context (though, many more are available on my publications page).
There were a lot of sticky notes involved in figuring out my next research agenda. Luckily, I got great help at DSST!
Recently, I had an amazing opportunity to attend the DSST (Digital Societies and Social Technologies) Summer Institute in College Park, MD. DSST brings together junior (e.g., postdoc, pre-tenure faculty) and established researchers from fields like Computer Science, HCI, Social Informatics, Information Science, Sociology, Anthropology, STS, and more. While there, I participated in workshops, got more familiar with methods used in other fields, and got a lot of great tips on articulating my research agenda (this is frequently a struggle for me because I have such broad research interests).
In small groups, we mapped out the research space of DSST, focusing on how we fit into the picture of a research area that encompasses so many different communities and venues. Interdisciplinarity is not for the weak!
There is so much I could write about this event, but there is one particular issue that resonated in multiple presentations, workshops, and offline discussions — the issue of vocabulary. It seems to me, that the biggest problems in interdisciplinary work arise not when we don’t know the words the other person is using but when we use the same words in different way. Here are a few examples:
- Problem: In Computer Science, this term often means “research challenge,” as in “I’m working on the problem of how to connect parents and children who live apart.” However, in some Social Science domains the word “problem” may be reserved for situations that are broken or non-normative. In other words, “connecting parents and children” is not a problem to solve — I might be supporting families in facing the challenge of separation, but I’m not fixing something that is broken. In some ways, using the word “problem” takes agency away from the people we am trying to support, instead positioning the designer as “the fixer.” Usually, this is not what people who build systems actually mean. This is a loaded term and might be better avoided or replaced with “challenge.”
- Theory: In Computer Science, this term often refers to the study of abstract constructs like Algorithms and Data Structures and frequently developed through mathematical proofs. In the Social Sciences, there are many types of theories serving different functions (my favorite reading on this is Halverston’s “What Does CSCW Need to DO with Theories?”). Theories are frequently heuristics used to understand and discuss empirical data and may or may not need to have strong predictive power. My personal observation is that theorists of both sorts have keen minds and a love for an elegant explanation and can become great friends once the vocabulary issues can be resolved.
- System: In Computer Science, “system” usually refers to a set of software and hardware that performs a specific function. At DSST, it was more frequently expanded and used to refer not just to the software and hardware but also to the people, practices, and ecosystems around the use of that particular tool.
- Ethnography: I’ve heard builders use this terms to refer to any sort of formative work that involves observing and talking to users. Not surprisingly, people who are trained as ethnographers might see this as an over-simplification. It’s hard to put the same label on a single week of observation versus two years of being embedded in a particular setting. Perhaps, rather than using the loaded term, it might make more sense to refer to specific methods used such as “two weeks of participatory observation” and “contextualized interviews.”
- Social Computing: This is a slippery terms, because we are all still trying to figure out what it means. This area is at the intersection of social science and computational systems, but what is included or excluded? As I spoke to people at the workshop, many equated Social Computing with either large-scale social network analysis (e.g., “we looked at 3 mill Tweets”) or Crowdsourcing (e.g., “we leveraged the crowd to do citizen science”). I was happy to provide a third possibility that I believe should be included in the definition: mediated communication for supporting one-to-one and small-group relationships. I hope that we continue to include things like videochat, ShareTable, haptic connectedness devices, small online support groups, etc. in our definitions and investigations of Social Computing.
In industry, most of our work happens in interdisciplinary groups. This kind of reflection has helped me understand why at times I have had trouble explaining my work or outlook to somebody from a different background, like formal methods or software engineering. DSST reminded me the importance of establishing a common ground and a common vocabulary in any work that brings together diverse disciplines.