PeopleofSuperintelligence

Researcher

Miguel R. D. Rodrigues

Also known as Miguel Rodrigues, Miguel Raul D. Rodrigues

Miguel Rodrigues is a researcher in information theory and machine learning whose work includes wireless security and robust deep networks. At Cambridge, he spoke on MIMO resource allocation in 2007 and coauthored a wireless-security paper that received the IEEE Communications Society and IEEE Information Theory Society Joint Paper Award in 2011. He co-chaired the 2016 IEEE Information Theory Workshop programme, studied deep-network generalization in a paper revised in 2017, and coedited Information-Theoretic Methods in Data Science in 2021. By 2023, he had earned degrees at Porto and UCL, held appointments at Cambridge, Princeton, Duke, and Porto, served as UCL Professor of Information Theory and Processing, led its IIML Lab, founded and directed its MSc in Integrated Machine Learning Systems, and was named an IEEE Fellow. As of October 2026, he is an ELLIS Fellow at UCL and co-leads a Responsible AI working group.

Now at
Department of Electronic and Electrical Engineering and European Laboratory for Learning and Intelligent Systems
Works
346
Citations
7,779
h-index
36
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2007–2011

    MIMO and wireless security

    At the University of Cambridge Computer Laboratory, he presents “Optimum resource allocation in MIMO systems: An information theoretic-estimation theoretic approach” in November 2007. In 2008, he coauthors “Wireless Information-Theoretic Security” with Matthieu Bloch, João Barros, and Steven W. McLaughlin for IEEE Transactions on Information Theory; the IEEE Communications Society and the IEEE Information Theory Society give the paper their Joint Paper Award in 2011.

  2. 2016

    Co-chairing an IEEE workshop

    In 2016, he co-chairs the Technical Programme Committee of the IEEE Information Theory Workshop in Cambridge, UK. His research spans information theory, information processing, and machine learning.

  3. 2016–2017

    Robust deep neural networks

    In May 2016, he submits “Robust Large Margin Deep Neural Networks”; the version revised in May 2017 studies generalization through classification margins and a neural network's Jacobian.

  4. March 2021

    A data science book

    Cambridge University Press publishes Information-Theoretic Methods in Data Science in March 2021, with Miguel R. D. Rodrigues and Yonina C. Eldar as editors.

  5. By 2023

    Degrees and past appointments

    By May 2023, he holds an undergraduate degree in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto and a PhD degree in Electronic and Electrical Engineering from University College London. Earlier appointments include Cambridge University, Princeton University, Duke University, and the University of Porto.

  6. 2023

    Professor at UCL and IEEE Fellow

    In May 2023, he is Professor of Information Theory and Processing at University College London, leads the Information, Inference and Machine Learning Lab at UCL, and is founder and director of the MSc in Integrated Machine Learning Systems. For its 2023 class, the IEEE Computer Society names him an IEEE Fellow for contributions to multimodal data processing and the foundations of reliable and secure communications.

  7. As of October 2026

    ELLIS and Responsible AI

    As of October 2026, he is an ELLIS Fellow at University College London and co-leads the Responsible AI working group with Jack Stilgoe. The group addresses data contributors' rights, responsibilities for AI malfunctions, and synthetic data for fairness.

Career

  1. Since 2002University College LondonFull Professor
  2. NowDepartment of Electronic and Electrical EngineeringLab Lead
  3. NowEuropean Laboratory for Learning and Intelligent SystemsFellow
  4. 2019–2022Alan Turing InstituteTuring Fellow
  5. 2012–2017Duke University
  6. 2007–2014University of Porto
  7. 2007–2014Instituto de Telecomunicações
  8. 2003–2007University of Cambridge

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Wireless Information-Theoretic Security2008 · IEEE Transactions on Information Theory · 1,851 citations
  2. Secrecy Capacity of Wireless Channels2006 · IEEE International Symposium on Information Theory (ISIT) · 828 citations
  3. Wireless Image Transmission Using Deep Source Channel Coding With Attention Modules2021 · IEEE Transactions on Circuits and Systems for Video Technology · 512 citations
  4. Robust Large Margin Deep Neural Networks2017 · IEEE Transactions on Signal Processing · 243 citationsWith Guillermo Sapiro
  5. MIMO Gaussian Channels With Arbitrary Inputs: Optimal Precoding and Power Allocation2010 · IEEE Transactions on Information Theory · 222 citationsWith Sergio Verdú

From OpenAlex, as of 21 October 2026.

  1. Google has the highest combined h-index among AI organizationsIncludes European Laboratory for Learning and Intelligent Systems. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  2. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University College London. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  3. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes University College London. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.
  4. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University College London. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Optimum resource allocation in MIMO systems: An information theoretic-estimation theoretic approach talks.cam.ac.uk. Checked 22 October 2026.
  2. IEEE Communications Society & Information Theory Society Joint Paper Award | IEEE Communications Society comsoc.org. Checked 22 October 2026.
  3. Information, Inference and Machine Learning Group at University College London | Members iiml-ucl.github.io. Checked 22 October 2026.
  4. [1605.08254] Robust Large Margin Deep Neural Networks arxiv.org. Checked 22 October 2026.
  5. Frontmatter - Information-Theoretic Methods in Data Science cambridge.org. Checked 22 October 2026.
  6. Talk “Deep Learning for Inverse Problems: Theoretical Perspectives, Algorithms, and Applications” – Técnico Lisboa tecnico.ulisboa.pt. Checked 22 October 2026.
  7. IEEE Computer Society Announces 2023 Class of Fellows | IEEE.org computer.org. Checked 22 October 2026.
  8. Miguel R. D. Rodrigues | European Laboratory for Learning and Intelligent Systems ellis.eu. Checked 22 October 2026.
  9. Working Groups — gen ai genai.ac.uk. Checked 22 October 2026.