Why I Still Publish Academic Papers

Many people have asked me, “If you’re working in industry, why do you still write academic papers?” In hopes of providing a more complete answer to all who might be interested (professors, corporate managers, job seekers, recruiters, colleagues, economists, data scientists), I have prepared this list of reasons why I, as an industry research scientist prioritize writing and publishing academic papers:

  1. Professional credibility & status: By publishing, I can demonstrate to myself and to my managers (who may or may not be experts at evaluating my talents) that I am on the cutting edge of my niche of the field (either theory, empirics, practice, etc.). This also provides an up-to-date public portfolio to demonstrate the advancement of my talents to prospective employers or clients.
  2. Technical communication: By forcing myself to write up my technical work formally, I am forced to solidify & distill my understanding of the material in order to mentally move on to the next step of research or the next project. Further, I am much better at communicating my work in the future to others in both business and academia who have, in turn, evangelized my work more broadly; this has saved me hours of repeating myself, expanded my impact, and opened up new opportunities. Precise & concise communication is key.
  3. Intellectual community: I really like associating with top notch talent to talk shop and life in general. In particular, these are the people that I want to work with for the rest of my career because they are motivated by intellectual truth & science more than salesmanship or money. That said, I work in industry precisely because I want my research to have a direct impact by helping companies be more efficient and successful. To me, this balance is the best of both worlds. Also, a side benefit from coauthoring academic papers with external researchers is “free R&D” for the company, either in the form of improved communication, informed brainstorming, or actual data work (if permitted).
  4. Social preferences: I have benefitted greatly from the contributions of others, and I like giving back to the community. I learn a lot from referees and by reviewing others’ papers and attending conferences and discussing ideas.
  5. Portable research: Work that I publish is in the public domain and, hence, is portable across companies. I want to continue to push forward my research and professional development, regardless of which company I work for. And I want to be able to positively and publicly build upon prior work.
  6. Option value: If I decide to return to academia, I would probably teach at either a business school or a second tier liberal arts school. Having a solid publication record would help my prospects. However, a former academic + industry manager of mine once told me, “Randall, after 10 years, academia won’t want you, and you won’t want academia.” And, I suspect, he is right. If I were to return, I would likely take a significant pay cut, and at least for now, I am loving the type of industrial research I get to do at tech companies.
  7. NOT for corporate promotion or reward: At least in my current position, nobody will directly reward me for or directly encourage publications. However, I do have a level of status and expertise from my professional and research record. It is not clear how much status I would have without the publication record if I knew all the same technical material. Honestly, having the publications directly on my resume probably does not matter much, but I would not be as good with the technical material without pushing myself to achieve precise academic communication—having a community holding me up to a high standard helps me grow.

Publishing academic papers is a great input into my work, but I am still selective about what I publish. I recognize that I cannot publish everything (e.g., business sensitive work) nor would I want to due to the opportunity cost of formalizing communication. I currently focus on publication outlets that keep the returns to my academic paper-writing efforts the highest by reaching the right audiences for my work, by reducing the overhead of publication, and by focusing on papers that I genuinely think are important for all of the reasons above.

Finally, Writing and publishing a paper represents an investment of ~3 months of total work, after the basic R&D: perhaps 1 month to write up the paper and then a couple more months to deal with the referee process. That is a lot of valuable time, so I try to focus on publishing only about 1 paper a year now, only focusing on the most important ideas. I have considered writing blog posts as well, but that becomes a little hard given that I would need to go through all the same internal corporate publication release effort for blog posts as for formal papers which the academic community more formally recognizes. So, I have focused mostly on papers.

Whose job is it: the hardware’s, software’s, or programmer’s?

Perhaps the biggest question in parallel computing for Big Data is, “Who’s responsible for the logical work to harness parallel architectures: the hardware, the compiler, or the programmer?”

Today I found an interesting lecture on MIT’s Open Courseware titled L3: Introduction to Parallel Architectures given as part of the “Multicore Programming Primer” IAP course by Saman Amarasinghe. The lecture discusses high-level parallel computing architectures from the past 50 years of parallel computing and lends insight into this question.

The question is about the distinction between Implicit and Explicit Parallelism

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