computer science

Michael Luby

Michael Luby is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Michael Luby rather than just read about it. In short: Michael George Luby is a mathematician and computer scientist, CEO of BitRipple, senior research scientist at the International Computer Science Institute (ICSI), former VP Technology at Qualcomm, co-founder and former chief technology officer of Digital Fountain. In coding theory he is known for leading the invention of the Tornado codes and the LT codes.

Key takeaways

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Reference excerpt

Michael George Luby is a mathematician and computer scientist, CEO of BitRipple, senior research scientist at the International Computer Science Institute (ICSI), former VP Technology at Qualcomm, co-founder and former chief technology officer of Digital Fountain. In coding theory he is known for leading the invention of the Tornado codes and the LT codes. In cryptography he is known for his contributions showing that any one-way function can be used as the basis for private cryptography, and for his analysis, in collaboration with Charles Rackoff, of the Feistel cipher construction. His distributed algorithm to find a maximal independent set in a computer network has also been influential. Luby received his B.Sc. in mathematics from Massachusetts Institute of Technology in 1975. In 1983 he was awarded a Ph.D. in computer science from University of California, Berkeley. In 1996–1997, while at the ICSI, he led the team that invented Tornado codes. These were the first LDPC codes based on an irregular degree design that has proved crucial to all later good LDPC code designs, which provably achieve channel capacity for the erasure channel, and which have linear time encoding and decoding algorithms. In 1998 Luby left ICSI to found the Digital Fountain company, and shortly thereafter in 1998 he invented the LT codes, the first practical fountain codes. Qualcomm acquired Digital Fountain in 2009.

Awards Luby's publications have won the 2002 IEEE Information Theory Society Information Theory Paper Award for leading the design and analysis of the first irregular LDPC error-correcting codes, the 2003 SIAM Outstanding Paper Prize for the seminal paper showing how to construct a cryptographically unbreakable pseudo-random generator from any one-way function, and the 2009 ACM SIGCOMM Test of Time Award. In 2016 he was awarded the ACM Edsger W. Dijkstra Prize in Distributed Computing; the prize is given "for outstanding papers on the principles of distributed computing, whose significance and impact on the theory and/or practice of distributed computing have been evident for at least a decade", and was awarded to Luby for his work on parallel algorithms for maximal independent sets. Luby won the 2007 IEEE Eric E. Sumner Award together with Amin Shokrollahi "for bridging mathematics, Internet design and mobile broadcasting as well as successful standardization". He was given the 2012 IEEE Richard W. Hamming Medal together with Amin Shokrollahi "for the conception, development, and analysis of practical rateless codes". In 2015, he won the ACM Paris Kanellakis Theory and Practice Award "for groundbreaking contributions to erasure correcting codes, which are essential for improving the quality of video transmission over a variety of networks." Luby was elected to the National Academy of Engineering in 2014, "for contributions to coding theory including the inception of rateless codes". In 2015 he was elected as a Fellow of the Association for Computing Machinery. Luby was elected as a Fellow of the IEEE in 2009.

Selected publications Michael Luby (2021). "Repair rate lower bounds for distributed storage". IEEE Transactions on Information Theory. 67 (9): 1. arXiv:2002.07904. doi:10.1109/TIT.2021.3052488. S2CID 211171523. John Byers and Mike Luby (2020). "Liquid Data Networking". Proceedings of the 7th ACM Conference on Information-Centric Networking. pp. 129–135. doi:10.1145/3405656.3418710. ISBN 9781450380409. S2CID 221565728. M. Luby, R. Padovani, T. Richardson, L. Minder, P. Aggarwal (2019). "Liquid Cloud Storage". ACM Transactions on Storage. 15 (1): 1–49. arXiv:1705.07983. doi:10.1145/3281276. S2CID 738764.{{cite journal}}: CS1 maint: multiple names: authors list (link) M. Luby, A. Shokrollahi, M. Watson, T. Stockhammer, L. Minder (2011). "RaptorQ Forward Error Correction Scheme for Object Delivery" (RFC 6330). {{cite journal}}: Cite journal requires |journal= (help)CS1 maint: multiple names: authors list (link) Amin Shokrollahi and Michael Luby (2011). "Raptor Codes". Foundations and Trends in Communications and Information Theory. 6 (3–4). Now Publishers: 213–322. doi:10.1561/0100000060. S2CID 1731099. J. Byers, M. Luby, M. Mitzenmacher, A. Rege (1998). "A digital fountain approach to reliable distribution of bulk data". ACM SIGCOMM (Special Interest Group on Data Communications): 56–67.{{cite journal}}: CS1 maint: multiple names: authors list (link) Luby, Michael (2002). "LT codes". The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings. pp. 271–282. doi:10.1109/sfcs.2002.1181950. ISBN 978-0-7695-1822-0. S2CID 1861068. J. Hastad, R. Impagliazzo, L. Levin, M. Luby (1999). "A Pseudorandom generator from any one-way function". SIAM Journal on Computing. 28 (4): 1364–1396. doi:10.1137/S0097539793244708.{{cite journal}}: CS1 maint: multiple names: authors list (link) Luby, Michael (1996). "Pseudorandomness and Cryptographic Applications". Princeton Computer Science Notes, David R. Hanson and Robert E. Tarjan, Editors. Princeton University Press. R. Karp, M. Luby, N. Madras (1989). "Monte-Carlo Approximation Algorithms for Enumeration Problems". J. Algorithms. 10 (3): 429–448. doi:10.1016/0196-6774(89)90038-2.{{cite journal}}: CS1 maint: multiple names: authors list (link) M. Luby, C. Rackoff (1988). "How to Construct Pseudorandom Permutations from Pseudorandom Functions". SIAM Journal on Computing. 17 (2): 1364–1396. doi:10.1137/0217022. Luby, Michael (1986). "A Simple Parallel Algorithm for the Maximal Independent Set Problem". SIAM Journal on Computing. 15 (4): 1036–1053. CiteSeerX 10.1.1.225.5475. doi:10.1137/0215074. {{cite journal}}: Cite uses deprecated parameter |citeseerx= (help)

References

Illustrations

Worked examples

Example 1 — a first encounter with Michael Luby

Start with the simplest possible case. Write down what Michael Luby claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Michael Luby before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Michael Luby ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Michael Luby

In research: Michael Luby appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Michael Luby in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Michael Luby is common in secondary-school and first-year university syllabi. It links to neighbouring topics American chief technology officers, American cryptographers, American information theorists, so understanding it makes those chapters shorter.
In everyday life: Look for Michael Luby outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Michael Luby in 20 minutes

Read the reference excerpt below once, without taking notes.
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Frequently asked questions

What is Michael Luby in simple terms?

Why does Michael Luby matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Michael Luby?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Michael Luby.