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Obvious Ways to Translate Research to Impact

Obvious Ways to Translate Research to Impact. George Kesidis The Pennsylvania State University kesidis@engr.psu.edu. Industrial/Gov’t-Lab O utreach – Short T erm. To determine specifically what is of interest: Faculty talks, faculty and grad student internships – trust, teach

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Obvious Ways to Translate Research to Impact

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  1. Obvious Ways to Translate Research to Impact George Kesidis The Pennsylvania State University kesidis@engr.psu.edu

  2. Industrial/Gov’t-Lab Outreach – Short Term • To determine specifically what is of interest: • Faculty talks, faculty and grad student internships – trust, teach • Learn relevant technology, needs, and market – talk the talk • Arrange supplemental research funding, contracts, seed $ • Patience, perseverance and … salesmanship • Industrial problems may not align with (or may have a gulf between) current academic trends • Surprising interest in theory: complex networks are hard to thoroughly simulate, and assumptions leading to concise theoretical insights are the “devil you know” • When selling empirical results: reproducibility involving realistic data, realistic emulations, prototypical deployment, open sourcing

  3. Cross-Disciplinary Research in Complex Networks • Proliferation of for-profit conferences and journals associated with enormous volume of published research articles from a large researcher population • Need focus through new books, surveys, course notes, and labs on trending subject matter (even targeting laymen esp. highschoolers) • Such “educational” activity: • is crucial for research in complex networks as they are cross-disciplinary • should be rewarded, but not mistaken for hard-fought core (incremental) research advances - protect core curricula and don’t just use H-index and other such bogus “research metrics” • Exploit interest in, e.g., multidisciplinary online social networking technology to recruit students from under-represented minority groups

  4. Long-Term Research • Past history indicates that it’s very difficult to predict what will be important long term – motivates principle of “curiosity driven” research by the many in quest for breakthroughs • Though NSF’s long-term/basic research mission is not as interesting to industry and gov’t labs, outreach still worthwhile as some folks there are trying to plan long-term • Cross-disciplinary work is high-risk/high-reward but: • its true quality is hard to assess in the short term – some breakthroughs not recognized for some years, while short-lived fads (of often simply recycled old ideas published in new venues) proliferate • need to navigate significant academic xenophobia and turf-wars on the ground • The quality of research you get is what you incent • Again, core incremental research attacking historically hard problems needs continued support in terms of both research funding and curriculum

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