Start-ups: A sense of enterprise
Universities aid entrepreneurs by helping them to turn their research into companies. In return, universities can reap financial benefits.
Michael Schrader knew he wanted to create a company, but he wasn't sure what it should do. After six years as a mechanical engineer in the automotive industry building plastic parts, in 2010 he began a master's degree in business administration at Harvard Business School in Boston, Massachusetts. In his quest for inspiration, he took a course in commercializing science at the Harvard Innovation Lab (i-lab).
The class heard presentations from researchers who among them had developed 17 different technologies that they thought had commercial value. One in particular caught Schrader's attention — a method devised by two engineers from Tufts University that uses a silk protein to stabilize vaccines. The vaccines could be formulated as powders and mixed with water when it was time to inject them, or embedded into a film that dissolves on the tongue like a breath-freshening strip. And, because they would not need to be refrigerated, they would be easier than conventional vaccines to distribute in places such as sub-Saharan Africa.
Along with other members of his class — an economics master's student, a former physics student earning a law degree and a postdoc in the chemistry department — Schrader spent the next few months looking into potential markets for the technology, making connections with business mentors and investors, and putting together a business plan. In 2012, the team founded Vaxess Technologies, which is attempting to bring vaccine formulations to market.
“We probably are a perfect model for how universities can forge together entrepreneurs and technologies to create companies,” says Schrader, now chief executive of Vaxess. The technology has not yet entered clinical testing, but the company has raised more than US$5 million, hired 11 employees, and started filing patents of its own in addition to those it licensed from Tufts University.
Although universities often license technology developed in their research laboratories to existing companies that are looking for new products, they also move discoveries off the bench and into the real world by encouraging inventors to start businesses from scratch. They offer classes in entrepreneurship, introduce researchers to investors and business experts, and even launch their own venture-capital funds. The path is trickier for life-sciences spin-offs, which take more time and money to get off the ground, than for companies based on software or electronics. And Europe has not caught up with the United States in its ability to create businesses. But universities are banking on entrepreneurs turning some of their research into products (see 'Start-up sampler').
Hubs of innovation
“We exist on taxpayer money. We have an obligation to try to get our research out into society.”
Universities tend to see commercialization as part of their remit to create and disseminate knowledge. “We exist on taxpayer money. We have an obligation to try to get our research out into society,” says Regis Kelly, director of the California Institute for Quantitative Biosciences known as QB3. The institute is a collaboration between the Berkeley, Santa Cruz and San Francisco campuses of the University of California. It supports life-sciences research across the campuses and tries to bring that research to market by partnering with industry and promoting entrepreneurship.
Part of the mission of the University of Colorado Boulder's BioFrontiers Institute is to aid students and faculty members who want to start new companies, says Jana Watson-Capps, associate director of the institute. “It fits with what we want to do in providing an education for our students so that they can find jobs and be good at those jobs,” she says.
A similar attitude is common in the United Kingdom. “We think it's important here in Oxford to see that the fruits of our research are actually developed to benefit society,” says Linda Naylor, managing director of Isis Innovation, a company created by the University of Oxford to commercialize its research.
Harvard's i-lab, which was opened in late 2011 to help students in any of the university's schools to develop businesses, is a relatively new entry in a long line of such efforts at many academic institutions. Students learn about idea generation, business-plan development and marketing. Budding entrepreneurs can attend workshops on specific hurdles that they are likely to encounter, such as how to apply for a Small Business Innovation Research grant from the federal government. A group of 'experts in residence' provides students with business expertise and introduces them to potential investors. The i-lab holds competitions such as the President's Challenge, which awards ideas that address the world's big problems. Vaxess took the challenge's top prize of $70,000 in 2012, as well as winning $25,000 in Harvard's Business Plan Contest the same year.
Because the main thrust of the i-lab is education, the university never takes a stake in any of the companies created there, says managing director Jodi Goldstein. Any intellectual property developed in a Harvard research lab belongs to the university and must be licensed, but ideas generated in the i-lab belong to the students. Goldstein hopes that the i-lab can help a future Mark Zuckerberg or Bill Gates to pursue their billion-dollar idea while still completing their degree. “We have several pretty famous dropouts around here, and I don't think that's necessary anymore,” she says.
As well as education and expertise, the i-lab provides a workspace for fledging companies. Meeting rooms, computer workstations and private storage space are available, as are a workshop for building prototypes and a pair of 3D printers. The i-lab is also planning to address one of the stumbling blocks that often trips up biology-based companies: finding a space to turn a discovery made in a university lab into a more marketable version. It is building a 1,400-square-metre wet lab with 36 research benches. When Vaxess reached that stage, it moved to LabCentral in Cambridge, Massachusetts. The provider of office and laboratory space takes care of regulatory requirements and provides administrative support and laboratory personnel so that new companies don't have to spend time and money setting up their own space. It opened in 2013 with a $5-million grant from the Massachusetts government (part of an initiative to bolster life-sciences business in the state) along with support from the Massachusetts Institute of Technology and the venture-capital arm of health-care giant Johnson & Johnson. Schrader considers this industry–government–academia web of support essential to his company's launch. “We have really taken advantage of this growing entrepreneurial ecosystem,” he says.
At QB3 in California, start-ups can rent lab space for as little as $85–100 per square metre per month. Unlike conventional landlords, who prefer to rent out an entire space, start-ups can rent a few hours in a fume cupboard or a shelf in a freezer, for example. “You only pay for what you actually use,” Kelly says. Charging is important, mainly because it is a way of weaning its users off the university teat. “It gets people more used to being in the private sector,” he says.
The need for lab space is just one reason why starting a life-sciences company can be much more challenging than, say, launching a business based on software. Any sort of pharmaceutical or medical device is subject to regulatory requirements, which leads to safety tests and clinical trials “If you're going to make a new drug you might need ten years and a billion dollars,” says Watson-Capps.
These time and capital requirements make it much more difficult to drum up investment for a life-sciences start-up. Although investors might be willing to risk a couple of hundred thousand dollars on a promising software idea, most life-sciences companies need initial funding of a few million dollars. “Obviously, people don't want to throw away a million dollars, so they have to do a lot more due diligence,” Kelly says. And because the time to realize a return on the investment can be so long, trading equity in the company in exchange for, say, legal services is not as popular as it is for other types of start-ups, he adds. These disparities are apparent in the investment statistics. Of the $77.3 billion in venture capital invested in the United States in 2015, software companies took in $31.2 billion — 40% of the total. Pharmaceuticals and biotechnology received a mere 12%.
Playing catch up
Europe lags behind the United States in producing start-ups of any kind, but the situation is improving. “We're certainly seeing a lot more spin-outs than we were a few years ago,” says Naylor. “There is more money around that is willing to go into the early stage.”
Vaxess Technologies are using silk proteins (L), which are extracted from cocoons (R), to stabilize vaccines. Image: Patrick Ho/Vaxess
She attributes that growth, in part, to the UK government's creation of the Seed Enterprise Investment Scheme in 2012, which provides tax breaks to investors in start-up companies. “The UK has been one of the leaders in providing tax incentives for investors in start-ups of all types,” says Karen Wilson, who studies entrepreneurship and innovation at Bruegel, an economic think tank in Brussels. Other countries across Europe, as well as Australia, have created their own tax incentives for investors modelled on the British scheme, although Wilson says that they're often controversial, derided as tax breaks for the wealthy. In the United States, tax incentives vary by state. The biggest legal change in the United States to promote spin-offs came in 1980, Wilson says, with the passage of the Bayh–Dole act, which allowed researchers to profit from inventions created with federal funding.
US and UK Universities have even been creating their own venture funds in recent years to invest in their spin-offs. The University of Cambridge, UK, created Cambridge Innovation Capital in 2013 with an initial fund of £50 million ($71 million). In 2014, the University of California began a $250-million fund. In May 2015, Isis launched Oxford Sciences Innovation to raise an initial £300 million from investors. And, in January, University College London opened the £50 million UCL Technology Fund, and the University of Bristol, UK, started its own enterprise fund (see 'Innovation income').
Entrepreneurial ecosystems in which inventors can find facilities, investors and business experts to help them to launch their companies are important for creating successful spin-offs, and they've been growing around many European universities, Wilson says. “There are an increasing number of these entrepreneurial hubs that are emerging across Europe, which are spawning these innovative high-growth firms,” she says.
In the United Kingdom, Cambridge is popular for life-sciences start-ups, and in Munich, Germany, the focus is mobile technology. In Switzerland, start-ups are clustered around the University of Zurich and the Swiss Federal Institute of Technology in Lausanne, where they focus on computing and technology. In Finland, Espoo is a hub: in 2010, three institutions combined to form Aalto University, which has strengths in communications, energy and design. Linked by a bridge across the Øresund strait, Copenhagen and Malmo in Sweden, make up another life-sciences centre. In the past year, however, the influx of refugees from the Middle East has led to a tightening of border security and made crossing the bridge more difficult for everyone.
The clampdown on migration within Europe, says Wilson, is making it harder for fledging companies to grow and spread. Expansion of their markets has always been challenging for start-ups in Europe, she says, where pushing into another country means dealing with differences not only in language and culture but also in taxes and other regulations. Many European companies get to a point at which, when they need to grow into a bigger market, they move to the United States, either of their own accord or at the insistence of their investors. “If you have a successful start-up in Italy it's much easier to go scale it in the US than it is to try to scale it across Europe,” Wilson says.
But many life-sciences companies won't grow on their own, particularly if their innovation is a drug — their endgame is often to be acquired by a large pharmaceutical company once they have advanced their therapy to a promising stage.
Although life-sciences companies demand more resources than other types of start-up, they have one characteristic that can make them uniquely appealing to investors — the potential for curing a disease or improving human health. As Kelly points out, “Almost any rich person has a sick relative.” If investors are going to risk their money, knowing that many of the companies they invest in will fail, they may prefer investments that have a potential for making a difference, he says. “If they're going to lose money on a business, they might as well lose it on something that could have some benefit to society.”
Meditation on a Caltrain: Understanding where to travel to next
Exploring options and thinking laterally about where you can use your scientific skills might be the key to successfully transitioning into industry, learns George Busby. This piece was one of two winners of the Science Innovation Union writing competition, Oxford. “This is downtown San Francisco, our train’s final stop. Can all passengers please detrain? All detrain please. All detrain.” Perhaps it was the heady fug of jetlag that made this broadcast particularly amusing to my UK-English language sensibilities, but I “detrained” all the same and stepped into the crisp morning air of the Californian rush hour. I was on the west coast to visit two genetics start-ups as part of a whirlwind three-day tour of the US. With a long postdoc and several first author papers tucked into my belt, I wanted to see if these credentials would pass muster in the tech haven of Silicon Valley. I’ve always found the loneliness of solo work-travel to be highly amenable to strategic thought, and this American adventure was an opportunity to reflect on why I was there and what I wanted. Back in Oxford, a few months earlier, I had begun to line-up my post-postdoc career options. A new and exciting big-data research institute has just opened and my supervisors were keen that I apply for money to start my own research group there. Excited by the prospect of doing interesting science somewhere new, I began to piece together the semblance of a research proposal with collaborative support. But then a strange thing happened. As the project began to take shape, the light at the end of the tunnel — the prize of scientific independence — began to feel not closer, but further away. Ahead of me were late nights and early mornings of writing pages and pages of a scientific proposal. After that, a year-long wait to find out that I’d been unsuccessful (a mere 15-20% of applicants for an early career Wellcome Trust Sir Henry Dale Fellowship get funded). Despite everything, my future was dependent on a number of factors that were out of my control. On top of this, there was the burgeoning realisation that no one actually reads the academic papers that I write. This is no moot point: writing papers is the main purview of a research scientist, and the central way we both communicate our results and measure success. However, compared to the proportion of the world’s population who can read, the number of people that had sat down to ingest my latest, dense, and fascinating (to me at least) treaty on the population genetics of Africa, three years in the making, was minuscule. The words of a colleague rang in my head: “99.9% of scientific papers just don’t get read”. Did I really want to spend the next 18 months slogging it out against funding agencies to get my own money just to do yet more science that no one was going to read? I forced myself to think more fundamentally about what I wanted to do. If I wanted to use my science to make a real and lasting impact and do things that make a real difference in the world, then writing academic papers is only one route to success. So, I blew the cobwebs off my LinkedIn account and started to hit up my small network of commercial contacts to investigate what companies out there in the big wide world might value my hard-won scientific expertise. This led me to California, where the streets are paved with gold and to the heart of the world’s tech industry. I’m by no means the first, and will certainly not be the last, person to have grown tired of the uncertainty of pursuing an academic research career. Despite the best efforts of university career departments, the option of staying in academia has always felt like the only real way to keep doing the science that I wanted to do: any other path would force a compromise or feel like I was quitting. But, perhaps I’d been looking at things the wrong way round. Rather than proposing whatever research was ‘hot’ at any given moment to funding bodies to maintain a decent university career trajectory, I should instead consider what my scientific ambitions are, then find the place to do them without limiting myself to academia. This way of thinking — that I could achieve my scientific objectives without compromise in either academia or industry — has been made possible for two reasons. Firstly, by luck as much as design. I work in a field, human genomics, where there are increasing options for work outside of universities: the number of commercial enterprises is exploding. If there was ever a time to jump into industry, it’s now. Second, I’d underappreciated how employable I am. I’ve led methodological and analytical research projects, written papers, and worked to communicate my science. Coupled with some in-depth genomics knowledge, these are all highly desirable qualities in the biotech world. So I reached out to two Californian companies, both of which do scientific research that’s not a million miles away from my day-to-day. Visiting them allowed me to see with my own eyes how work in industry differed from academia. I was surprised to learn that research jobs at both companies were not purely about making marketable products: there was a certain amount of trial and error to the work that they do, and not all of the research that they do is expected to end up as a viable product. They were also both mature enough to have teams of people working on marketing, accounts, PR, and software engineers, who were supported by the sales of the main product, but not scientists themselves. The possibility of collaborating with these people is exciting, providing new avenues for communicating and justifying the work of the research teams. Importantly, both companies sell my flavour of science to millions of customers — working for them would mean I could impact orders of magnitude more people, orders of magnitude more quickly than any scientific research I could hope to do in a university over the next few years. If impact and scientific reach is what I want, then this seems like a far better way to achieve it than waiting for a year to hear on the unlikely success of a research grant. I was beginning to feel like Lady Justice with my balance scales measuring the benefits and costs of academic versus commercial employment. Sure, academic research is dominated by uncertain funding cycles and can feel glacially slow at times, but that’s not necessarily a bad thing. Some view it as a privilege to be able to devote one’s time exclusively to fully understanding a specific question, and there’s no denying the satisfaction that comes with finding stuff out. Plus, I’ve been fortunate enough to work with incredibly talented people who’ve given me the intellectual freedom to spend my days thinking about the things that I want to think about. There’s clearly a lot to be said for being able to concentrate on the questions that one believes to be important and worthwhile. But with a wife and a growing family I’ve also reached the age where the pursuit of such scholarly freedom might appear not just selfish, but irresponsible. In common with around a third of UK families, both my wife and I work full time. Without my wife’s additional income, my postdoc salary would give us a higher household income than around 42% of the population. So, despite almost ten years at university (and the debt to prove it) without two incomes, we’d be struggling to get above the median of household earners nationwide. And the double whammy of living in the least affordable city in the UK with the cost of childcare increasing at three times inflation year on year, even with two incomes, there is little monthly return on my educational investment. Moreover, from a purely financial point of view, it pays to work in industry as a life scientist, with salaries being up to 30% higher than academia. As peers from school and university began to financially pull away from me, first by buying cars that are younger than ten years old, and more recently upgrading their small flats for family houses, I’ve consoled myself in the knowledge that although I can’t match them, I’m doing what I love. Who needs things anyway? But when you’re spending a third of your take-home pay on rent and another third on childcare, there’s little chance of saving much of the remaining third. Realising that you’re never going to be able to buy a house in the city where you work starts to get mentally draining. Can I really justify doing the science I do, which, let’s remember, no one actually reads, to just about get by? Of course, I’m far from being a pauper, or even a JAM, but wouldn’t it be nice for either my wife or myself to reduce the hours we work to spend more time with our children, without having to drastically change our quality of life? There is of course risk of job security associated with working in industry, particularly for an early stage start-up. But, there is also risk associated with staying in academia, particularly given the number of PhD and postdoc scientists in the workforce, many of whom will be pushing for the same jobs. And, in industry there is the distinct possibility that your pay could match your scientific success, which is not the case when you’re tied to a public sector pay scale. More than anything, my visit to California not only demonstrated that it’s possible to do interesting and worthwhile science commercially, but that perhaps it’s the only way to do some science. It would take many years and much grant money to generate the sorts of big datasets that some tech companies now have control of. If, as a scientist, you’re interested in answering some of the big questions, perhaps it pays to ask yourself whether the best way to achieve your ambitions is through a start-up, rather than academically. What’s more, at least in genomics, it’s beginning to feel like detraining from the academic express onto the industry platform might be the best way to do the most relevant and engaging science. George Busby is a postdoctoral research associate in statistical genomics at the Wellcome Trust Centre for Human Genetics, University of Oxford.
How a stint in Silicon Valley unleashed one researcher’s business skills
Tomasz Głowacki’s career now straddles academia and industry, thanks to his participation in a leadership programme organized by the Polish government. In 2007, when I started work as a research and teaching assistant at Poznań University of Technology in Poland (a job that straddled bioinformatics research and teaching discrete mathematics, algorithms and data structures), I thought academia would be a lifelong career. I enjoyed the intellectual freedom, chance to work on challenging problems and travel opportunities. Shortly after defending my computer-science PhD thesis in 2013, I secured a place on the Polish government’s Top 500 Innovators initiative, a nine-week programme in research commercialization and management at universities with high positions in the Academic Ranking of World Universities. It was set up because the Polish government thought a lack of cooperation between researchers and business was one of the main reasons for the country’s low position in European Innovation Scoreboard rankings. The focus at my interview was how to commercialize my research results. I was asked about factors such as potential customers, business models and pricing. Two months later, I was one of 500 scientists sent either to the University of California, Berkeley; Stanford University, California; or the University of Cambridge, UK. The goal was to learn from the very best researchers and business practitioners. While at the Walter A. Haas School of Business at Berkeley, I spent time with researchers, practitioners and entrepreneurs from Silicon Valley. What surprised me the most was the marriage between business and academic institutions in California. Lecturers shared their experiences of research commercialization, business and start-up firms. This was very different from Poland, where a scientific career does not recognize commercial activities in terms of cooperation between business and academia. In my experience, many Polish scientists see commercialization activities as a roadblock to their academic careers. During the Berkeley training, I heard how PhD students can successfully transition into business. These lectures were delivered by Peter Fiske, who is now director of the Water Energy Resilience Research Institute at Berkeley Lab, and whose career straddles both industry and academia. Fiske focused on transferable skills between academia and business, covering data analysis, resourcefulness, technological awareness, resilience, project management, problem solving, English proficiency and good written communication. Fiske is a strong advocate of the need to market yourself as a scientist. Mark Rittenberg, a business and leadership communications specialist at Haas School of Business, taught us about the power of communication and storytelling. As scientists, we focus mostly on research results. We tend to think that the content we present is enough to sell ourselves. But in business, how you present yourself, self-confidence, an interesting story and non-verbal communication are of at least the same importance. The innovators programme included one-day visits to technology companies in Silicon Valley, and the opportunity to undertake internships at some of them. I visited Google, the software companies Splunk and Autodesk, as well as NASA and biotechnology firm Genentech. These visits helped me to understand that ambitious work and challenging problems are not just the domain of universities. I did a three-week internship at PAX Water Technologies in Richmond, California, where I was one of five Polish scientists who set up an interdisciplinary team to work on reducing household water consumption. This was a long way from our research topics, and a new area for all of us. Willingness to learn new things, self-curiosity, creativeness and being open to unexplored areas helped us to drill down into the problem and to propose a solution. All of these are standard skills for a scientist. The programme helped me to understand that scientists can be effective and successful outside academia, and that the business world is full of challenging problems to work on. But the most important conclusion for me is that the applied aspect of what I do matters the most. The best fit for me seemed to be a transition into business. Between June and September 2013, after completing the innovators programme, I applied for several research and development positions in business. I prepared a long CV that covered my research achievements. No one got back to me. It was an important lesson. As scientists, we have to understand how our skills fit current job-market demands. So I connected with some old university friends who were working in business to discuss their interview experience. I decided to revamp my CV by making the description of my education shorter and focusing on my transferable skills; I included organizational skills, experience of data-analysis techniques, language skills and my structured approach to problem solving. As scientists we focus more on problems and solutions when we describe our work. But a potential business employer is more interested in how you get there. You should focus on the tools and methods you have used, knowledge of foreign languages, and how you organize and report your work. In 2013, I found a job as an analyst at BAE Systems Applied Intelligence at its new offices in Poznań, working with IT systems and insurance data to detect customer fraud. A year later, I discussed my transition with Fiske, who told me: “Now that you are on the other side, don’t lose touch with your friends in academia — seek ways to help them be more relevant to the outside world.” I wanted to give something back and to find my own way to contribute to the academic world. I am now head of product development at Analyx, an international marketing data-analytics company, and also work part-time at Poznań School of Banking as a business practitioner, teaching project management as well as systems analysis and design. I discuss the real business cases I face with my students. I also organize lectures and meetings for students with business experts, chief executives and consultants. Some of these have started long-term academic collaborations, and they provide a great opportunity for students to learn from practitioners and to land internships. I have managed to organize a master’s programme between academia and business. Students have the chance to get involved in hot industry topics supervised by business experts, and to present results and defend their theses at their universities. Teaching based on my personal experience is more satisfying for me. Leaving academia was not a failure. It helped me to explore new opportunities, to better understand my professional expectations and to find the career path that fits me best. This is an article from the Nature Careers Community, a place for Nature readers to share their professional experiences and advice. Guest posts are encouraged. You can get in touch with the editor at firstname.lastname@example.org.
From Academia to Silicon Valley - and back
Although faculty members transition from industry to academia (and vice-versa), it’s rare to go back and forth. How does each setting help a researcher grow, and what skills are critical in both environments? Sam King offers his insight. Five years ago, I left my tenured position in computer science at the University of Illinois at Urbana-Champaign to push myself intellectually and professionally in industry. During these years, I started a company (Adrenaline Mobility), sold my company to Twitter, worked as a software engineer, managed a two-person team, managed a 25-person organization, battled overseas fraudsters and fake accounts, and led a nine-month project (an eternity in industry) that ended up being the largest growth initiative in the history of Twitter. Now, I’m back in academia — at the Department of Computer Science at the University of California, Davis. Why? My transition to industry began when I was on sabbatical from Illinois to work on my startup in California, where we were working on ways to make it easy for other programmers to add encryption to their apps. The startup was born out of my academic research on digital security, and, after a couple of years, Twitter bought it. Suddenly, I had a decision to make: work at Twitter in San Francisco, or stay in academia. In the end, I left. Although I enjoyed the work and the stability, I wanted to step outside my comfort zone, and I wanted to experience the entire process of taking an idea all the way to production — instead of forgotten in a paper as so often happens in academia. I wanted to have impact, too: software developed in a research setting is used rarely outside of academia; industry provided an opportunity for other people to use the things I made. I spent two years at Twitter working on preventing fake accounts and improving security, before Lyft (a North America-only Uber competitor) recruited me away to help with fraud, where I spent another two years. What I learnt One of the unique aspects of industry that I enjoyed the most was the fast pace. At Twitter and Lyft most of my teams were focused on security. Both apps face active and worthy adversaries that regularly try to hack Twitter and Lyft accounts — or create fake accounts which could be used to make money. At Twitter, they could use compromised or fake accounts to send spam, and at Lyft they could use them to get free rides. In other words, I got to fight against bad guys. The faster we moved, the more successful we were in protecting our users and systems. In industry, you are always interacting with others, leading or building teams. There is more value in being able to manage people, having technical breadth and being able to see — and adapt to — a big-picture vision. You have access to a huge number of users, and the solutions you devise must be straightforward and simple to implement because they have to be carried out at a large scale. As a result, the impact you can have is tremendous. For example, signing up for a new account is a deceptively complex process at Twitter. From a user’s perspective, it means filling out three fields in a form and pressing a button. Behind that, Twitter uses vast, intelligent infrastructure to make it easy for genuine users to sign up while keeping bad actors and bots out. Building security to work within this requires respecting Twitter’s hunger to grow, while coordinating with different teams across the business and measuring impact quantitatively. Any changes to the sign up process have a direct and massive impact on the business, so security countermeasures must be well thought out. All of this is hidden behind one little button. In industry, having straightforward solutions is critical: simplicity is king. In academia, you can build complex systems because you’re trying to prove a concept. But in industry, people must be able to use the software you’ve created, which adds a unique set of design constraints. There is an open-endedness to work in academia that I enjoy that doesn’t translate to industry, which is driven by quarterly objectives and stakeholders. When I was in industry, I missed the academic freedom and the ability to create and implement my own vision for research. I also missed working on projects that focused on long-term outcomes (measured in years, not months) and a far-reaching, personal vision. This became a catalyst for my return to academia. I was also motivated by events in my personal life: two years ago, my son was diagnosed with Type I diabetes and I found myself trying to carve out time to research the topic while working in industry. In academia, I knew I could approach the topic with more time and access to additional resources and collaborators at the university. Strangely enough, I also missed failure! In industry, when you work on a successful product, your main job is execution. There are unique challenges and difficult problems, but by and large, a well-executing team in industry fails rarely. When I reflect back on my previous academic experience, the two projects that stick out the most are failed research projects, because we had no idea whether they were going to work. (They didn’t.) Coming back Leaving industry was scary. I was at Lyft, an up-and-coming company with a bright future, I worked with talented people who I trusted and had worked with for many years, and I loved the pace. In fact, each of the four years that I was in industry, people from academia asked me about coming back, and I always turned them down. It wasn’t until UC Davis, with a strong pedigree in security research and a deeply collaborative and collegial faculty, reached out that I even considered coming back to academia. With this, coupled with my motivation to help my son and desire to work on long-term research, I came to the realization that to pursue my own interests in research successfully, I had to come back to academia. When I came back to academia, it wasn’t a flawless reentry. I was wired to move and think fast, but I had to retrain myself to consume information slowly and deliberately. This adjustment showed up even in banal activities like reading papers: in industry, I was used to skimming articles to get the gist. But in academia, being a specialist means you must dive deep into the literature to understand minute details of other people’s research, compare your work with others’ efforts, and explain the concepts to other people when you teach. In contrast, I noticed that in either setting, and to succeed in any career, you need to have strong communication skills, both written and spoken, to make a case that is both well-laid out and logical. The big difference is that researchers are trained in this skill and practice it often, whereas many software engineers end up picking it up on the job. Upon reflection, having been in academia and industry has given me the best perspectives of both worlds: I am better at managing people, and I know what students encounter as they go through their educational experiences and careers, including going through multiple environments before finding the right fit. The best piece of advice I’d share: don’t be too afraid to make a change — wherever you go, you’ll learn something. Sam King, Ph.D., is an associate professor of computer science at the University of California, Davis. He returned to academia after spending four years in industry as both the Head of Accounts at Twitter and the Head of Fraud and Identity at Lyft.