About

Software engineer at Google. Previously: Mozilla, Syntensity, Ph.D. in Neural Computation (mostly math).

Created Emscripten and Binaryen and co-created WebAssembly.

Ported Doom to the Web in 2011.

Loves science fiction and fantasy, and also Agatha Christie.

The opinions stated here are my own, not anyone else’s.

• kripken
• @kripken.com on Bluesky
• @kripken on Mastodon
• (used to be "kripken" on twitter)

Articles

• A new way to bring garbage collected programming languages efficiently to WebAssembly (2023)
• Up to 4GB of memory in WebAssembly (2020)
• Outside the web: standalone WebAssembly binaries using Emscripten (2019)
• Why WebAssembly is Faster Than asm.js (2017)
• Compiling to WebAssembly: It’s Happening! (2015)

Threads

• About proofs described as “AI is intractable / AGI can’t work” (2026)
• We don’t understand neural networks at the algorithmic level (2026)

Publications

• Zakai, A. (2018). “Fast Physics on the Web Using C++, JavaScript, and Emscripten”. Computing in Science & Engineering (CiSE), vol. 20, no. 1, pp 11-19.
• Haas, A., Rossberg, A., Schuff, D.L., Titzer, B.L., Holman, M., Gohman, D., Wagner, L., Zakai, A., and Bastien, JF. (2017). “Bringing the web up to speed with WebAssembly”. In Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2017), pp. 185-200.
• Puder, A., Woeltjen, V., Zakai, A. (2013) “Cross-compiling Java to JavaScript via tool-chaining.” Proceedings of the 2013 International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools (PPPJ 2013), pp. 25 - 34.
• Zakai, A. (2011). “Emscripten: an LLVM-to-JavaScript compiler”. In Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion (OOPSLA ‘11), pp. 301-312.
• Zakai, A., Ritov, Y. (2009). “Consistency and Localizability.” Journal of Machine Learning Research, 10, pp. 827­-856.
• Goldberg, Y., Zakai, A., Kushnir, D, Ritov, Y. (2008). “Manifold Learning: The Price of Normalization.” Journal of Machine Learning Research, 9, pp. 1909­-1939.
• Zakai, A., Ritov, Y. (2008). “How Local Should a Learning Method Be?” Proceedings of the 21st Annual Conference on Learning Theory (COLT 2008), pp. 205-­216.
• Bickel, P. J., Ritov, Y., Zakai, A. (2006). “Some Theory for Generalized Boosting.” Journal of Machine Learning Research, 7, pp. 705­-732.
• Gati, I., Kleiman, T., Saka, N., Zakai, A. (2003). “Perceived benefits of using an internet­ based interactive career planning system.” Journal of Vocational Behavior, 62, pp. 272­-286.