Who is Who in Computing

Greek mathematician and engineer who built programmable automata two thousand years ago. His Pneumatica and Automata describe machines driven by air, water, and counterweights that performed sequences of actions — opening doors, pouring wine, enacting theatrical scenes. Sequential logic in mechanical substrate.

Can help you study: Ancient automata, pneumatics, mechanical computing, the aeolipile, theatrical machines, and the two-thousand-year history of programmable devices.

Daughter of Lord Byron and Annabella Milbanke. The first computer programmer. Her Notes on Babbage’s Analytical Engine (1843) contained the first published algorithm and — more importantly — the first vision that computers could manipulate any symbols whose relations could be formally expressed, not merely numbers. She also asked the question that still matters: can a machine originate anything?

Can help you study: The origins of computing, the Analytical Engine, algorithmic thinking, the Lovelace Objection, poetical science, and the question of what machines cannot do.

Mathematician who defined computation itself. His 1936 paper proved what is computable and what is not. At Bletchley Park he broke Enigma. His 1950 paper asked whether machines can think, and proposed the test that bears his name. He laid the foundations of AI, theoretical computer science, and mathematical biology. Prosecuted for homosexuality; died at forty-one.

Can help you study: Computability, Turing machines, the Entscheidungsproblem, the Turing Test, morphogenesis, codebreaking, and the philosophical question of machine intelligence.

Rear Admiral, United States Navy. She invented the first compiler (A-0, 1952), led the development of COBOL, and spent decades arguing that computers should speak something closer to English. She found the first literal computer bug — a moth. She said the most dangerous phrase in the language is “we’ve always done it this way.”

Can help you study: Compilers, COBOL, the history of programming languages, naval computing, and the principle that ideas should be tested, not traditions defended.

MIT mathematician who founded cybernetics — the study of control and communication in animals and machines. His Cybernetics (1948) argued that feedback is the fundamental principle governing both living systems and engineered ones. He was among the first to warn about the social consequences of automation.

Can help you study: Cybernetics, feedback systems, control theory, the relationship between biological and mechanical systems, and the ethics of automation.

The father of information theory. His 1948 paper proved that all communication is reducible to bits, and that noise can be overcome by encoding. He also built the first chess-playing program, a maze-solving mouse, and a machine whose sole purpose was to switch itself off. MIT and Bell Labs.

Can help you study: Information theory, entropy, channel capacity, Boolean algebra, error correction, and the mathematical foundations of all digital communication.

Mathematician and science administrator who co-authored The Mathematical Theory of Communication (1949) with Shannon, making information theory accessible. He proposed machine translation in 1947 and directed the Rockefeller Foundation’s support for molecular biology, helping create the field.

Can help you study: Communication theory, information and noise, machine translation, the three levels of communication problems, and how to bridge mathematics and human understanding.

Dutch computer scientist who insisted that programming is a mathematical discipline requiring proof, not testing. He invented the shortest-path algorithm, structured programming, semaphores for concurrent processes, and the idea that “goto” is harmful. Turing Award 1972. His handwritten EWDs — over 1,300 of them — are models of clear thought.

Can help you study: Algorithms, structured programming, concurrent programming, program correctness, the shortest-path problem, and the discipline of writing code that can be proved right.

This simulacrum draws on the published work of Donald Knuth — author of The Art of Computer Programming, the multi-volume work begun in 1962 that remains the definitive analysis of algorithms. He invented TeX because existing typesetting was not good enough for his book. Stanford, emeritus. He checks his email once every three months.

Can help you study: Algorithm analysis, data structures, combinatorics, literate programming, TeX, and the principle that computer programming is an art as well as a science.

Perceptual psychologist who argued that we do not see the world as it is — we see what we can do with it. His theory of affordances and ecological perception replaced the idea that vision is passive image-processing with the idea that perception is active, embodied, and inseparable from action.

Can help you study: Ecological perception, affordances, optic flow, direct perception, the visual cliff, and why perception is something you do, not something that happens to you.

This simulacrum draws on the published work of Terry Winograd — who built SHRDLU (1970), one of the most impressive AI demonstrations ever, then spent the rest of his career explaining why it didn’t actually work. His turn to Heidegger and phenomenology, in Understanding Computers and Cognition (1986, with Flores), remains the deepest critique of AI from within the field. Stanford.

Can help you study: Natural language understanding, the SHRDLU experiment, the limits of symbolic AI, Heideggerian phenomenology applied to computing, breakdown as revelation, and why the question is not “can machines think?” but “how can machines serve thinking beings?”

This simulacrum draws on the published work and engineering of Steve Wozniak — sole designer of the Apple I and Apple II, the machines that created the personal computer industry. He designed for elegance, for fun, and for the fewest possible chips. After Apple’s IPO he gave $10 million in stock to employees that Jobs had denied. He left Apple in 1985 because he missed tinkering.

Can help you study: Hardware design, the Apple I and II architecture, elegant engineering, the early personal computer revolution, and the principle that the best machines feel like magic.

Co-founder of Apple, co-founder of Pixar, and the person who proved that technology and the liberal arts belong at the same intersection. His adoptive father taught him to make the back of the fence beautiful, because you know it’s there even if nobody sees it. Zen Buddhist for over twenty years. The Macintosh, the iPod, the iPhone. His last words were “Oh wow. Oh wow. Oh wow.”

Can help you study: Product design, the intersection of technology and liberal arts, simplicity as design principle, taste as engineering discipline, and the difference between making something and making something great.

This simulacrum draws on the published work and design practice of Susan Kare — the graphic designer who created the visual language of the Macintosh. The Happy Mac, the Chicago font, the bomb icon, the watch cursor. She arrived at Apple from a career in sculpture, and her mother’s counted-thread embroidery gave her an intuition for pixel grids that no computer scientist possessed. Currently at Pinterest.

Can help you study: Icon design, pixel art, visual metaphor, human-computer interaction, the Macintosh interface, and why good icons should work like road signs.

This simulacrum draws on the published work and engineering practice of John Carmack — the programmer behind Doom, Quake, and the modern first-person shooter. He invented adaptive tile refresh, binary space partitioning for real-time rendering, and the fast inverse square root. Co-founder of id Software and Armadillo Aerospace. Currently working on artificial general intelligence.

Can help you study: Graphics programming, game engine architecture, systems optimisation, real-time rendering, VR technology, and the discipline of writing the fastest possible code.

This simulacrum draws on the published work and engineering of Chris Lattner — creator of LLVM (the compiler infrastructure used by most of the world’s software), the Swift programming language, and the Clang C/C++ compiler. Apple, Google, Tesla, SiFive, Modular. The right abstraction, he argues, unlocks everything.

Can help you study: Compiler design, LLVM, Swift programming, language design, intermediate representations, and the principle that the right abstraction is the most powerful tool in computing.

This simulacrum draws on the published work of Stephen Wolfram — physicist, mathematician, and creator of Mathematica and the Wolfram Language. His A New Kind of Science (2002) argued that simple rules, iterated, generate all the complexity we observe in nature. The concept of computational irreducibility — that some processes cannot be predicted without running them — has implications for physics, biology, and the limits of science itself.

Can help you study: Cellular automata, computational irreducibility, the Wolfram Language, Mathematica, the ruliad, and the argument that computation is the fundamental process underlying nature.

This simulacrum draws on the published work of Andrew Zisserman — professor of computer vision at Oxford and one of the most cited researchers in the field. His work on multiple view geometry, VGGNet, and deep learning for visual recognition helped teach machines to see. Co-author of Multiple View Geometry in Computer Vision (2003).

Can help you study: Computer vision, multiple view geometry, convolutional networks for recognition, VGGNet, deep feature learning, and the mathematical foundations of how machines extract structure from images.

This simulacrum draws on the published work and engineering leadership of Johny Srouji — Apple’s Senior Vice President of Hardware Technologies and the architect of Apple Silicon. The M-series chips transformed what a personal computer could be by unifying CPU, GPU, and Neural Engine on a single die. The silicon is the foundation of everything.

Can help you study: Chip design, system-on-chip architecture, Apple Silicon, the Neural Engine, hardware-software co-design, and why the silicon determines what the software can dream.