engineering

Salman A. Avestimehr

Salman A. Avestimehr is a engineering 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 Salman A. Avestimehr rather than just read about it. In short: Salman A. Avestimehr is a Dean's professor at the Electrical & Computer Engineering and Computer Science Departments of University of Southern California, where he is the inaugural director of the USC-Amazon Center for Secure and Trusted Machine Learning (Trusted AI) and the director of the Information Theory and Machine Learning (vITAL) research lab.

Key takeaways

Salman A. Avestimehr belongs to engineering; place it in that map before memorising details.
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Reference excerpt

Salman A. Avestimehr is a Dean's professor at the Electrical & Computer Engineering and Computer Science Departments of University of Southern California, where he is the inaugural director of the USC-Amazon Center for Secure and Trusted Machine Learning (Trusted AI) and the director of the Information Theory and Machine Learning (vITAL) research lab. He is also the CEO and Co-Founder of FedML. Avestimehr's contributions in research and publications are in the areas of information theory, machine learning, large-scale distributed computing, and secure/private computing and learning. In particular, he is best known for deterministic approximation approaches to network information theory and coded computing. He was a general co-chair of the 2020 International Symposium on Information Theory (ISIT), and is a Fellow of IEEE. He is also co-authors of four books titled “An Approximation Approach to Network Information Theory”, “Multihop Wireless Networks: A Unified Approach to Relaying and Interference Management”, “Coded Computing”, and “Problem Solving Strategies for Elementary-School Math.”

Education Avestimehr completed his bachelor's degree in electrical engineering from Sharif University of Technology in 2003. He received his M.S. degree in 2005 in electrical engineering and computer science from University of California, Berkeley in 2005. Continuing his studies at UC Berkeley, he finished his Ph.D. in computer science in 2008; his doctoral adviser was David Tse.

Career and research Avestimehr was a postdoctoral scholar at the Center for the Mathematics of Information (CMI) at Caltech in 2008. He served as an assistant professor at the school of electrical and computer engineering of Cornell University from 2009 to 2013. Avestimehr was promoted to a Dean's professorship in electrical and computer engineering at the University of Southern California, where he has taught since 2013. He is also the inaugural director of the USC-Amazon Center for Secure and Trusted Machine Learning. He has been a general co-chair of the 2020 International Symposium on Information Theory (ISIT). He has also been an associate editor for IEEE Transactions on Information Theory. Current research areas of Prof. Avestimehr include information theory, distributed computing, machine learning, and secure and private learning/computing.

Awards and honors 2020. IEEE Fellow 2019. IEEE Information Theory Society James L. Massey Research & Teaching Award 2015. The Okawa Foundation Award 2013. IEEE Communications Society and Information Theory Society Joint Paper Award 2011. Presidential Early Career Award for Scientists and Engineers (PECASE, 2011) 2010. National Science Foundation CAREER Award

Bibliography “An Approximation Approach to Network Information Theory,” by A. S. Avestimehr, S. Diggavi, C. Tian and D. Tse, Foundations and Trends in Communications and Information Theory, 2015. “Multihop Wireless Networks: A Unified Approach to Relaying and Interference Management,” by I. Shomorony and A. S. Avestimehr, Foundations and Trends in Networking, 20114. “Coded Computing,” by S. Li and A. S. Avestimehr, Foundations and Trends in Communications and Information Theory, 2020. “Problem Solving Strategies for Elementary-School Math,” by K. Avestimehr and A. S. Avestimehr, Now Publishers, 2020.

Selected publications C. He, M. Annavaram, and A. S. Avestimehr, “Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge,” in NeurIPS, 2020. C. He, et al, A. S. Avestimehr, “FedML: A research library and benchmark for federated machine learning”. Q. Yu, S. Li, N. Raviv, M. Mousavi Kalan, M. Soltanolkotabim and A. S. Avestimehr, “Lagrange Coded Computing: Optimal Design for Resiliency, Security and Privacy,” in Proc. AISTATS 2019. M. Yu, Z. Lin, K. Narra, S. Li, Y. Li, N. S. Kim, A. Schwing, M. Annavaram, and A. S. Avestimehr, “GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training,” in NeurIPS, 2018.

S. Li, M. A. Maddah-Ali, Q. Yu and A. S. Avestimehr, “A Fundamental Tradeoff Between Computation and Communication in Distributed Computing,” in IEEE Transactions on Information Theory, vol. 64, no. 1, pp. 109–128, Jan. 2018. S. Li, M. A. Maddah-Ali and A. S. Avestimehr, “A Scalable Framework for Wireless Distributed Computing,” in ACM/IEEE Transactions on Networking, vol. 25, no. 5, pp. 2643–2654, Oct. 2017. N. Naderializadeh, M. Maddah-Ali, and A. S. Avestimehr, “Fundamental Limits of Cache-Aided Interference Management,” in IEEE Transactions on Information Theory, vol. 63, no. 5, pp. 3092–3107, May 2017. S. Li, M. A. Maddah-Ali and A. S. Avestimehr, “Coding for Distributed Fog Computing,” IEEE Communications Magazine, vol. 55, no. 4, pp. 34–40, April 2017. Q. Yu, M. A. Maddah-Ali and A. S. Avestimehr, “Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication,” in NIPS, 2017. C. Geng, N. Naderializadeh, A. S. Avestimehr, and S. Jafar, “On the Optimality of Treating Interference as Noise,” IEEE Transactions on Information Theory, Vol 61, No 7, 2015. N. Naderializadeh and A.S. Avestimehr, “ITLinQ: A New Approach for Spectrum Sharing in Device-to-Device Communication Systems,” IEEE Journal on Selected Areas in Communications Special Issue on 5G Wireless Communication Systems, Vol 32, No 6, 2014. I. Shomorony and A. S. Avestimehr, “Worst-Case Additive Noise in Wireless Networks,” IEEE Transactions on Information Theory, Vol 59, No 6, June 2013 I. Shomorony and A. S. Avestimehr, “Two-Unicast Wireless Networks: Characterizing the Degrees-of-Freedom,” IEEE Transactions on Information Theory, Vol 59, No 1, January, 2013. V. Aggarwal, A. S. Avestimehr, and A. Sabharwal, “On Achieving Local View Capacity Via Maximal Independent Graph Scheduling,” IEEE Transactions on Information Theory, Special Issue on Interference Networks, Vol 57, No 5, May 2011. A. S. Avestimehr, S. N. Diggavi, and D. N. C. Tse, “Wireless Network Information Flow: A Deterministic Approach,” IEEE Transactions on Information Theory, Vol. 57, No. 4, pp. 1872–1905, April 2011.

References

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Illustrations

Worked examples

Example 1 — a first encounter with Salman A. Avestimehr

Start with the simplest possible case. Write down what Salman A. Avestimehr claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In engineering, 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 Salman A. Avestimehr 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 Salman A. Avestimehr 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 Salman A. Avestimehr

In research: Salman A. Avestimehr appears in engineering 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 Salman A. Avestimehr 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: Salman A. Avestimehr is common in secondary-school and first-year university syllabi. It links to neighbouring topics 21st-century engineers, American information theorists, Coding theorists, so understanding it makes those chapters shorter.
In everyday life: Look for Salman A. Avestimehr 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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Frequently asked questions

What is Salman A. Avestimehr in simple terms?

Why does Salman A. Avestimehr matter?

Because it connects several engineering 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 Salman A. Avestimehr?

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 Salman A. Avestimehr.