Lesser-known Differences between Academia and Industry

The Chronicle recently published an interesting opinion piece that mentions several aspects of working in academia that may not be as evident as commonly discussed ones.

Having worked in industry and academia, I appreciated the commentary. There are indeed relatively subtle differences between the two career tracks that work for some but not for others. For example, when working in industry I found surprising how little I was allowed to say about my work to outsiders. This is the kind of difference whose importance varies widely from one person to the next: some enjoy sharing their work, some are OK one way or another, while others see sharing as a chore they are happy to drop when transitioning from academia to industry.

In the Chronicle piece McCormack mentions working on long-term projects as a distinguishing characteristic of academic work.

The long-term nature of academic work is real. As McCormack points out, individual projects in academia require thinking on a time span of years. Long-term goes far beyond that, thought. For example, leading an academic lab requires thinking 10, 15, and more years ahead. This is memorably observed by the author of Breath Becomes Air as he is contemplating an academic career path while incurably sick — starting on the academic track is a non-choice for him as he does not have the 15 years he’d need for it.

Researchers may be surprised that projects being-long term is not immediately apparent to everybody, that it is even worth mentioning as a characteristic.

In my experience the long-term nature of academic work is often misunderstood in the industry. The misunderstanding can be inferred, for example, from people equating “long-term” with “low-pressure”, and assuming professors must be leading stress-free lives with few responsibilities and entire summers off.

Industry operates on a range of timescales, with the vast majority of industry working on a mix of timelines along the lines of day-to-day, weekly, and monthly (e.g., operational work), and quarterly and yearly (e.g., on medium-to-large size projects, seasonal campaigns). Industry timescales approach decades only rarely and nearly always only at the highest levels (e.g., building landmark structures). There are indeed many books advising managers to think longer-term, despite pressures to focus on the day-to-day.

Industry R&D labs unfortunately get caught up in the middle. Researchers work their best when committed to long-term projects, while business leads expect that smart people can produce results quickly, and that people can be moved from project to project as necessary. As a result R&D labs struggle to justify their value to the business (if they try to stick with long-term projects), or to attract talented researchers (if they go along with business requirements). I don’t think any R&D lab has figured out a solution and settled on a model that works for everybody.

Overall, I am glad the Chronicle article brought this up. The long-term timelines of the academic work are a bug or a feature depending on one’s preferences; this is definitely something to know and something to think about when choosing a career path.

About Maria Gorlatova

Dr. Maria Gorlatova is the Sternberg Family Associate Professor of Electrical and Computer Engineering at Duke University. Her research centers on pervasive computing technologies, with a focus on spatial computing and next-generation augmented reality. She received her Ph.D. in Electrical Engineering from Columbia University and her M.Sc. and B.Sc. degrees (Summa Cum Laude) in Electrical Engineering from the University of Ottawa, Canada. She spent two years at Princeton University’s Electrical Engineering Department as an Associate Research Scholar and Associate Director of the Princeton University EDGE Lab. Dr. Gorlatova was named one of the N2Women Rising Stars and has received multiple awards, including the NSF CAREER Award, the DARPA Young Faculty Award (YFA), the DARPA Director’s Fellowship, the IEEE ISMAR 2025 Best Paper Award, the IEEE Communications Society Award for Advances in Communications, and research awards from Meta, Cisco, and IBM. She served as the TPC Co-chair of ACM/IEEE IPSN 2023, the General Co-Chair of the 2025 NSF Workshop on Networking and Systems Challenges in Immersive Computing, and the TPC Co-chair of ACM/IEEE SenSys 2025.
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