Computer science as an academic discipline is less than a hundred years old, but our fascination with mechanical devices and procedures dates back millennia. Today, computer science is a huge academic (and professional) discipline, as the modern world has embraced computing in every facet of life—from big data in physics laboratories to social media apps on ubiquitous smartphones. In what follows, we’ll look at the most influential people in the field of computer science today.
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Computer science as an academic discipline is less than a hundred years old, but our fascination with mechanical devices and procedures dates back millennia. The 9th century Persian astronomer and mathematician Muhammad bin Musa al-Khwarizmi is often credited with the invention of the algorithm, a key idea undergirding all of computing. But modern computing started with the groundbreaking work of British mathematician and code-breaker Alan Turing. Turing’s ideas about mechanical procedure, later known as “Turing Machines,” laid the theoretical groundwork for what was to come-digital computers, programming languages, and the modern world of the Internet and smart phone. Turing, truly, was the father of computer science.
By 1946, the world’s first programmable electronic computer, called the ENIAC, launched an arms race for ever more powerful computer hardware, and the study of computer programming and algorithms design was also in full swing. The first academic degree in the fledgling field of computer science, called the Cambridge Diploma in Computer Science, was awarded in 1953 by the University of Cambridge in England. The degree proved to be auspicious, as it was quickly recognized around the world, as work continued and expanded in earnest on computing in the United States, Europe, and elsewhere. Computer science quickly became a “hot” and important academic degree, particularly as personal computers arrived in the 1970s and 80s. Today, computer science is a huge academic (and professional) discipline, as the modern world has embraced computing in every facet of life-from big data in physics laboratories to social media apps on ubiquitous smartphones.
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In what follows, we look at influential computer scientists over the last decade. Based on our ranking methodology, these individuals have significantly impacted the academic discipline of computer science within 2010-2020. Influence can be produced in a variety of ways. Some have had revolutionary ideas, some may have climbed by popularity, but all are academicians primarily working in computer science. Read more about our methodology.
Note: This isn’t simply a list of the most influential computer scientists alive today. Here we are focused on the number of citations and web presence of scholars in the last 10 years. There are other highly influential scholars who simply haven’t been cited and talked about as much in the last 10 years, whereas some new faces have been making a splash in the news, speaking events, and publishing, publishing, publishing. Our AI is time sensitive. To find some of the big names you might have expected to see here, we encourage you to use our dynamic ranking system and check influence over the past 20 and 50 years.Want more? Discover the history of influential computer scientists:
Areas of Specialization: Machine Learning, Artifical Intelligence, Computational Biology
Koller is a professor of computer science at Stanford University. She received her bachelor’s degree from Hebrew University of Jerusalem in 1985, and her Ph.D. from Stanford in 1993. Her former students include notable computer scientists Ben Tasker, Suchi Saria, and Eran Segal.
Koller’s work focuses on probabilistic reasoning, representation, and inference with graphical models like Bayes Nets. With Stanford colleague Andrew Ng, Koller launched the online learning platform Coursera in 2012, serving as co-CEO with Ng and later as the company’s president. Koller has also been active in using modern data science and statistics to improve areas of concern for us like health care. For instance, she has made important contributions to the development of techniques and software that help predict whether premature babies will have health problems. She has directed her focus on computer vision as well as computational biology toward the development of applications and systems that can help in decision making and diagnosis in medical and other industries.
Areas of Specialization: HTML, Invented World Wide Web
Tim Berners-Lee (also called “TimBL” or “TBL”) is a Professorial Fellow of Computer Science at the University of Oxford and a professor at the Massachusetts Institute of Technology (MIT). Berners-Lee is best known for inventing a markup language, the Hyper Text Markup Language (HTML) that has (of course) become the basis for Web pages. In a very real sense, Berners-Lee invented the World Wide Web! And more. In 2016, Berners-Lee received the prestigious Turing Award for “for inventing the World Wide Web, the first web browser, and the fundamental protocols and algorithms allowing the Web to scale.” Originally a physicist, Berners-Lee received a first-class Bachelor of Arts degree in physics at Queen’s College, Oxford.
Berners-Lee began his career as an engineer for a telecommunications company in England, and later worked as a researcher at CERN in Geneva. While at CERN, Berners-Lee first conceived of the design for hypertext (HTML links), implementing an early prototype known as ENQUIRE. The World Wide Web did not exist yet—but the Internet did, and Berners-Lee then extended his ideas about hypertext to the Internet, in effect inventing the World Wide Web, in his now famous proposal written in 1989. He then designed and developed the world’s first Web browser, WorldWideWeb (no spaces, and later renamed to Nexus to avoid confusion). He then published the world’s first web site, “info.cern.ch.” Naturally, the web site provided an explanation to neophytes (basically, everyone else!) of what a Web page is, and how the Web was intended to link together, or “work.” It also provided how-to information on how to use the web browser to set up a server, and how to build a website. Not bad. Berners-Lee later became Director of the World Wide Web Consortium (W3C), gathering together businesses to help create standards and recommendations for the growing Web. Berners-Lee also conceived of a follow-up “next generation” web, known as the Semantic Web, which would add computer-readable logical statements to web pages to enable computers to understand their contents better. The Semantic Web is a visionary project that perhaps has stalled as the Web evolved into what we now know, but the ideas seem ripe for exploration. In short, Tim Berners-Lee—TBL—is a true pioneer of the World Wide Web, and a hugely influential computer scientist.
Areas of Specialization: Artifical Intelligence, Deep Learning Networks
LeCun is one of the most important people in the subfield of computer science known as machine learning. In particular, he is one of the original scientists working on Deep Learning systems, which are enormously popular in work on Artificial Intelligence today. LeCun received his engineering degree from ESIEE Paris in 1983, and his Ph.D. from Université Pierre et Marie Curie in 1987.
LeCun’s long career has been laser-focused on research on neural networks, actually an old technique in machine learning dating back almost to the inception field of Artificial Intelligence—an important subfield of computer science focused on making intelligent applications—in the 1950s. However, LeCun’s research has been mostly on what are now called “Deep Learning” networks, neural networks that are organized in hierarchies of layers, making them more powerful for many tasks like recognizing objects in photos. Not surprisingly, LeCun’s work on Deep Learning attracted the attention of Web giant Facebook, where he now holds the position of Vice President, Chief AI Scientist at the company. He retains the title of Silver Professor of the Curant Institute of Mathematical Sciences at New York University.
Areas of Specialization: Quantum Computing, Complexity Theory
Aaronson is David J. Bruton Jr. Centennial Professor of Computer Science at the University of Texas at Austin, a position he has held since 2016. Before UT, he was a professor of computer science at Massachusetts Institute of Technology. Aaronson, a theoretical computer scientist who’s also one of the world’s leading experts in quantum computing, graduated from Cornell University with a degree in computer science (a minor in mathematics). He did his Ph.D. at the University of California, Berkeley.
Aaronson is known for his work on quantum computing, an important (and still unsolved) topic in computer science that seeks to model computers on quantum “bits” of information, known as q-bits. While performing fundamental work on quantum computing itself, Aaronson is also known for his “no-nonsense” admissions of the difficulties the field of quantum computing faces, as there is currently no working model of quantum computation scalable to handle real-world computing tasks. His much read article “The Limits of Quantum Computers,” appeared in Scientific American in 2008.
Areas of Specialization: Computational Origami
Demaine is a professor of computer science at Massachusetts Institute of Technology (MIT). His university education is extraordinary, because Demaine was a child prodigy. He completed his bachelor’s degree at Dalhousie University at age 14. By 20, he had completed his Ph.D. at the University of Waterloo. His dissertation on computational origami won Canada’s national prize for the best Ph.D. thesis in Canada in 2003.
Demaine’s research at MIT focuses on fundamental theory in computation as well as applications of mathematics in computer science and artificial intelligence research. He was the youngest professor ever hired by MIT when he joined them in 2001, becoming a full professor a decade later in 2011. Demaine was awarded the “genius grant,” the MacArthur Fellowship in 2011, and won the prestigious Nerode Award in 2015 for his work on the theory of algorithms in 2016. He also became a fellow of the Association for Computing Machinery (ACM) the same year.
Areas of Specialization: Computer Programming, Analysis of Algorithms
Knuth is professor emeritus of computer science at Stanford University. He received his Ph.D. in Mathematics at the California Institute of Technology (Cal Tech). As an undergraduate at the Case Western Reserve University (then Case Institute of Technology), Knuth received the extraordinary honor of receiving his bachelor of science degree together with a master of science in mathematics based on the strength of his work at Case. He also helped redesign an early IBM computer while at Case, and made fundamental contributions to programming—writing a program to help predict the scores of basketball players on his college team.
While an associate professor at Caltech, Knuth wrote the influential The Art of Computer Programming, a tome of seven volumes that quickly became a go-to book for anyone interested in the how’s and why’s of computer programming. Knuth’s publication is a notoriously deep-dive into programming. In fact, Microsoft Chairman Bill Gates once quipped that “If you think you’re a really good programmer ... You should definitely send me a résumé if you can read the whole thing.” His name has become synonymous with the fundamentals of computer programming.
Areas of Specialization: Cryptography, Algorithms, Computational Complexity
Zvi Galil is a computer scientist and mathematician who is the former dean of the Georgia Institute of Technology College of Computing. He earned a B.Sc. and M.Sc. in applied mathematics from Tel Aviv University (where he eventually served as president). He went on to earn a Ph.D. in computer science from Cornell University.
His mathematical and computer science research interests have included cryptography, the design and analysis of algorithms, stringology, sparsificaiton and computational complexity. He is a prolific writer with over 200 papers to his credit. His most frequently cited works include Efficient algorithms for finding maximum matching in graphs and Efficient algorithms for finding minimum spanning trees in undirected and directed graphs.
Areas of Specialization: Artifical Intelligence, Deep Learning
Hinton has been called one of the “Godfathers of Artificial Intelligence” by media sources for his work on a neural network system known as “Deep Learning.” He divides his year between working for Google Brain, the influential AI group at Google, and as a professor of computer science at the University of Toronto in Canada.
Hinton, along with researchers David Rumelhart and Ronald Wilson, designed one of the key features in modern neural networks, a type of machine learning algorithm that learns from experience. In 1986, he published a description of using backpropagation to train neural networks on data, and this technique has become a lynchpin for all neural network successes to date. Hinton truly is one of the “godfathers” of AI, an honorific especially relevant today as major Web companies like Google, Facebook, Twitter and many others now use neural networks ubiquitously. At Google and the University of Toronto, Hinton focuses on Deep Learning systems, a type of neural networks that involves stacking multiple networks together to create powerful results, like learning to recognize faces and other objects in online photos. Self-driving cars also use Deep Learning systems for autonomous navigation.
Areas of Specialization: Superintelligence, Human Enhancement Ethics
Nick Bostrom is the founding director of the Future of Humanity Institute at University of Oxford, the Oxford Martin Programme on the Impacts of Future Technology, and a philosopher at Oxford. He has earned a B.A. from the University of Gothenburg, an M.A. from Stockholm University, an M.Sc. from King’s College of London, and a Ph.D. from the London School of Economics.
Bostrom is best known for his work on superintelligence, human enhancement ethics, the anthropic principle and existential risk. He has also written two major books: Anthropic Bias: Observation Selection Effects in Science and Philosophy and Superintelligence: Paths, Dangers, Strategies. Superintelligence was particularly well-received, honored as a New York Times bestseller list and promoted by top minds such as Bill Gates and Elon Musk.
Areas of Specialization: Distributed Algorithms, Formal Modeling
Nancy Lynch is the head of the Theory of Distributed Systems research group at the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory, a mathematician, theorist and NEC Professor of Software Science and Engineering. She attended Brooklyn College, where she studied mathematics. She went on to earn a Ph.D. from the Massachusetts Institute of Technology.
She began her career teaching math and computer science at Tufts University, Florida International University, the Georgia Institute of Technology School of Computational Science & Engineering and the University of Southern California. She worked with colleagues to show that an asynchronous distributed system does not allow consensus if one processor crashes. Their research was awarded the PODC Influential-Paper Award for 2001, the first of two for Lynch, who was recognized again by the organization in 2007.
Areas of Specialization: Computational Complexity Theory
Manuel Blum is the Bruce Nelson Professor of Computer Science at Carnegie Mellon University. Born in Venezuela, Blum has had an impressive career working on the theoretical underpinnings of programming and algorithms, notably computational complexity theory (roughly, how long it takes a program to solve a problem), cryptography (code making and breaking), and program verification and checking, an area of immense importance to practical software development.
Blum received his bachelor’s and master’s degrees in electrical engineering and computer science (EECS) from Massachusetts Institute of Technology (MIT). His supervisor was the late Marvin Minsky, a pioneer of Artificial Intelligence and a founding member of the group that launched AI in the 1950s. He spent nearly four decades as a professor of computer science at the University of California, Berkeley, until 1999. He then joined the faculty of computer science at Carnegie Mellon, where he has developed his early research on complexity theory into practical results that have proven immensely important for algorithm design and study: the compression theorem, the gap theorem, and the Blum speedup theorem. Blum’s interest in cryptology has also yielded important results. Perhaps best known are CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart), the ubiquitous challenge-response quizzes that appear on web pages when users access or sign up for content. Blum and three other researchers coined the term in 2003, though there has been some dispute about who originated the idea.
Areas of Specialization: Computational Complexity Theory, Cryptography, Number Theory
Shafrira “Shafi” Goldwasser is the RSA Professor of Computer Science at Massachusetts Institute of Technology, as well as Professor of Mathematical Sciences at Weizmann Institute of Science in Israel. She received a bachelor’s degree in computer science and mathematics from Carnegie Mellon University, and a master’s and Ph.D. from the University of California, Berkeley.
Goldwasser’s impressive career spans many areas in computer science, including computational complexity theory, cryptography, and number theory. She has been in high demand during her impressive career in computer science, serving as chief scientist and co-founder of thr Israeli company Duality Technologies using cryptographic methods for data security, and has served as an advisor to a number of successful ventures, including companies focusing on blockchain technology, which has become hugely popular in recent years. Goldwasser is also a member of the Theory of Computation group at the world-renowned Artificial Intelligence Laboratory at MIT. Her primary focus is on fundamental aspects of computer security, like cryptography, a topic that is of both theoretical interest in computer science and mathematics and has obvious practical applications to many industries like finance, banking, and data protection.
Areas of Specialization: Cryptography, Algorithms and Data Structures, Computational Complexity
Michael J. Fischer is a computer scientist best known for his work on cryptography, algorithms and data structures, parallel and distributed computing and computational complexity. He earned a B.Sc in mathematics from the University of Michigan and an M.A. and Ph.D. in applied mathematics from Harvard University.
He has spent his career as an assistant professor of computer science at Carnegie Mellon University, of mathematics at the Massachusetts Institute of Technology, an associate professor of electrical engineering and a professor of computer science at the University of Washington and Yale University.
His computer science research work has yielded important theoretical and practical applications for the creation of parallel algorithms and protocol for oblivious transfer. His most-cited work, “The string-to-string correction problem”, explores methods for string matching and parsing and formal grammars.
Areas of Specialization: Artificial Intelligence
Stuart J. Russell is the founder of the Center for Human-Compatible Artificial Intelligence and professor of computer science at the University of California, Berkeley, adjunct professor of neurological surgery at the University of California, San Francisco and computer scientist. He earned a B.A. in physics from Wadham College at Oxford and a Ph.D. in computer science from Stanford University.
He is best known as the co-author of Artificial Intelligence: A Modern Approach, which is the most popular textbook on the subject. He is an active researcher in the field, exploring the history and future of artificial intelligence, machine learning, knowledge representation, probabilistic reasoning, inverse reinforcement learning and multitarget tracking.
Areas of Specialization: Hypermedia, Web Science
Hall is Regius Professor of Computer Science at the University of Southampton in the UK. She received her bachelor’s and Ph.D. in Mathematics at Southampton. She also has a master’s degree in Computing at City University in London.
Hall has the distinction of developing a working hypertext system before the World Wide Web existed. The team she led created the powerful Microcosm hypermedia system, which was later used commercially with the start-up Multicosm, LTD. For her groundbreaking work, Hall became the first female professor at Southampton. She was also Head of the School of Electronics and Computer Science, from 2002 to 2007.
Hall worked with founder of the Web Tim Berners-Lee as founding director of the Web Science Research Initiative (WSRI). Her work at WSRI helped establish Web Science, the study of behavior and interaction on large-scale networks like the World Wide Web.
Areas of Specialization: Artificial Intelligence, Structure and Interpretation of Computer Programs
Gerald Jay Sussman is the Panasonic Professor of Electrical Engineering at the Massachusetts Institute of Technology. He earned an S.B. and Ph.D. in mathematics at the Massachusetts Institute of Technology, studying under Seymour Papert.
Sussman has made important contributions to artificial intelligence, creating strategies for handling dependencies, propagation of constraints and the refinement of almost-right plans. He has worked with Hal Abelson on the free software movement, which is focused on opening up software for use, change and redistribution free of royalties or licensing concerns. He worked with his graduate students to develop computer-aided design tools for Very Large Scale Integration, as well as Scheme, a new programming language.
Sussman is also the principal designer for the Digital Orrery, which is used to do precision integrations for experimentation with orbital mechanics, and the Supercomputer Toolkit, which is a computer optimized for differential equations. The Supercomputer Toolkit was used in conjunction with the Digital Orrery to study the outer planets of our solar system and beyond.
Areas of Specialization: VLSI theory, Computer Programming, Algorithms
Charles E. Leiserson is a computer scientist, professor at the Massachusetts Institute of Technology, principal in the Theory of Computation research group at MIT, inventor of the fat-tree interconnection network, developer of Cilk programming language, and network architect for the Connection Machine CM5. He earned a B.S. in computer science and mathematics from Yale University and Ph.D. in computer science from Carnegie Mellon University.
He is a pioneer in the development of VLSI theory, having worked on retiming methods of digital optimization and systolic arrays. He founded Cilk Arts, Inc, which was later acquired by Intel.
Perhaps best well known for introducing the idea of cache-oblivious algorithms – featuring no tuning parameters for size or line-length – which somehow still use cache at near optimal levels. He also co-authored the most common introductory textbook on algorithms, Introduction to Algorithms, with colleagues Thomas Cormen, Ronald Rivest, and Clifford Stein.
Areas of Specialization: Computer Programming, Amorphous Computing
Hal Abelson is the founding director of Creative Commons and the Free Software Foundation and a professor of electrical engineering and computer science at the Massachusetts Institute of Technology. He earned a B.A. from Princeton University and a Ph.D. in mathematics from the Massachusetts Institute of Technology.
He directed the first use of Logo, a programming language for the Apple II, and worked with Gerald Sussman to develop MIT’s foundational computer science textbook, Structure and Interpretation of Computer Programs, which was based on the premise that coding languages were merely a structured means of communicating with computers. Among the hacker community, this text is referred to as the “Wizard Book”.
Areas of Specialization: Computer Science Theory, Models of Computation
Lenore Blum (retired) is a professor of computer science at Carnegie Mellon University. Blum initially studied architecture, but graduated with a degree in mathematics by taking math classes at Massachusetts Institute of Technology, though her bachelor’s was granted by Simmons College, a private women’s college. Blum went to MIT and completed her Ph.D. there in 1968.
Blum began her career at The University of California, Berkeley, though at the time (in the 1960s) they did not provide opportunities for women professors. She then taught at Mills College at Northeastern University, where she received a first from Mills: an endowed professorship as the Letts-Villard Chair at Mills. Her success at Mills led her to Carnegie Mellon University, where she became a Distinguished Career Professor of Computer Science at CMU in 1999.
Areas of Specialization: Robotics
Reddy is the founding director of the Robotics Institute at Carnegie Mellon University. The Robotics Institute at CMU is perhaps the world’s best center for robotics research in the world. (Robotics Business Review called it a “pacesetter in robotics research and education” in 2014.) Reddy is the Moza Bint Nasser Chair of Computer Science at CMU, and has been professor of computer science at Stanford University during his stellar career of five decades. Reddy has had a major influence on the development of the field of robotics in artificial intelligence.
Reddy was born in rural India, and is the first member of his family to go to college. He received his bachelor’s degree in civil engineering from an engineering school in India (College of Engineering, Guindy) and his Ph.D. in computer science from Stanford University. Reddy has been active in helping to create opportunities for gifted low-income youth in India by helping to form a technical university in India (the Rajiv Gandhi University of Knowledge Technologies).
Areas of Specialization: Robotics, Simulation, System Optimization
Oskar von Stryk is a well-known robotics expert, vice president of Robocup, and professor of simulation, system optimization and robotics at the Technische Universität Darmstadt’s Department of Computer Science. He studied mathematics and computer science at the Technical University of Munich, earning a doctorate in mathematics.
He has held teaching appointments at the University of California, San Diego and the Universidade Estadual de Campinas in Brazil. von Stryk is very active in robotics, competing in the DARPA Robotics Challenge, competing with both the Hector and ViGIR teams. Hector, short for Heterogeneous Cooperating Team of Robots was a first-place winner in the Rescue Robot League of RoboCup of 2014. Hector has won numerous awards, including Best in Class Autonomy and 1st place in the World Robot Summit’s Plant Disaster Prevention Challenge.
Areas of Specialization: Computer Security
Schneier’s name is synonymous with computer security. He is also respected as a cryptographer, and writes on issues of personal privacy arising from society’s ever changing relationship with new technology. In 1984, Schneier earned his bachelor’s degree in physics from the University of Rochester in New York. He received a master’s degree in computer science from American University in Washington, D.C. in 1988 and an honorary Ph.D. from the University of Westminster, London in 2011.
Over the years, Schneier has written extensively on core issues and problems with computer security, both for private individuals and for company and government security. Importantly, he has been an outspoken critic—or at the very least, he has sounded caution—of blockchain technology, arguing that it can create more problems than it solves. Central to much of Schneier’s thinking about computer security, he points out that supposedly “bullet proof” technology solutions for establishing security and trust tend to have weak points at the “ends” where humans add and receive data. The human components to end-to-end security is a key theme in his ideas. “Schneier’s Law” was coined by Internet theorist Cory Doctorow in a 2004 speech, capturing this theme: “Any person can invent a security system so clever that he or she can’t imagine a way of breaking it.”
Areas of Specialization: Computational Complexity Theory Khot is Julius Silver Professor of Computer Science in the Courant Institute of Mathematical Sciences at New York University. Khot received his bachelor’s degree in computer science from the IIT Bombay. He received his Ph.D. from Princeton University in 2003.
Khot has made key contributions to computational complexity theory applied to games theory, notably his “unique games conjecture,” in 2002, where he postulated that certain games, known as unique games, are very difficult to solve (for computer science students, they are NP-Hard). Khot’s work on unique games has proven practically relevant, as it helps illuminate certain problems with, for instance, voting results. It has application to what are known as “approximation results” in a variety of fields in disciplines seeking mathematical description and rigor.
Areas of Specialization: Computational Cryptography
Shamir is a cryptographer and professor of computer science at the Weizmann Institute of Science in Israel. He received a bachelor’s degree in Mathematics from Tel Aviv University in 1973, and a master’s and Ph.D. in computer science at Weizmann in the 1975 and 1977.
Shamir became famous for his co-invention of one of the world’s first public key cryptosytems, RSA (which bears his name: it’s an acronym for Rivest-Shamir-Adleman). The RSA public key system has been widely adopted by businesses and individuals to securely send encrypted messages, as in email or other data transmissions over a network. He has also done pioneering work in visual cryptography, and developed a powerful technique known as “differential” cryptography—though it was later revealed that the top secret National Security Agency (NSA) had developed and used the technique secretly. Nonetheless, for his many important discoveries in the field, Shamir is one of the true fathers of computational cryptography.
Areas of Specialization: Computer Systems, Sensor-Driven and Location-Aware Computing, Computer Technology and Sustainability
Hopper is professor of computer technology at University of Cambridge in England. He is also treasurer and vice president of the Royal Society, and is known for his success as an entrepreneur. Hopper received his degree from Swansea University in Wales, England, and his Ph.D. from the University of Cambridge.
Hopper’s research focuses on computer networks. He was part of the team that developed the Cambridge Ring, an early local area network for computer systems. He is known for his work on ActiveBadge, an indoor location system used by organizations. His work on location and network technologies has also led Hopper to contribute to the ongoing discussion about the potential problems and abuses of surveillance technology.
Hopper has founded or helped found numerous companies, including Cambridge Broadband in 2000. In 2013, Hopper co-founded TxtEz, a company that commoditizes business-to-consumer communications in Africa.
Cybersecurity is an emerging field within the discipline of computer science. According to the Bureau of Labor Statistics, jobs in the field of cybersecurity are expected to grow at an extremely robust rate of 33% between now and 2030. We explore this emerging field in the following articles:
A number of highly-ranked schools now offer online degree programs in cybersecurity. To learn more about one of these top programs, check out our interview with Jason Denno from the University of Arizona, discussing their online degree program in cybersecurity.