PeopleofSuperintelligence

Researcher

Deniz Gündüz

Also known as Denız Gündüz

Deniz Gündüz is a Professor in Information Processing whose work connects machine learning with wireless communications and edge learning. He earned an M.S. and Ph.D. in electrical engineering at NYU, worked at Princeton, Stanford and CTTC, and joined Imperial College London in 2012. He coauthored research on machine learning for wireless communications, federated and edge learning, and DeepWiVe, an end-to-end neural system for wireless video transmission. He won an ERC Proof-of-Concept grant for DeepWiVe in 2023 and coauthored a 2025 paper on semantic compression with multimodal foundation models. As of October 2026, he leads Imperial's Information Processing and Communications Lab and is Deputy Head of the Intelligent Systems and Networks Group.

Works
792
Citations
22,205
h-index
71
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2004–2007

    Electrical engineering degrees

    He earns an M.S. in electrical engineering from NYU Tandon in 2004 and a Ph.D. in 2007.

  2. 2007–2012

    Research from Princeton to Imperial

    After his Ph.D. in 2007, he works as a postdoctoral research associate at Princeton and a consulting assistant professor at Stanford. From September 2009 to September 2012, he is a research associate at CTTC in Barcelona; in September 2012, he joins Imperial's Electrical and Electronic Engineering Department.

  3. 2017

    A CTTC Early Achievement Award

    The IEEE Communications Society gives him its Communication Theory Technical Committee Early Achievement Award in 2017 for contributions to source and channel coding, cooperative communications, and energy harvesting.

  4. 2019–2020

    Machine Learning in the Air

    In 2019, he coauthors “Machine Learning in the Air,” a review of machine learning for wireless communication systems focused on the physical layer. In 2020, he argues for a joint communication and learning approach to edge training and inference in “Communicate to Learn at the Edge.” He also coauthors “Federated Learning Over Wireless Fading Channels” with Mohammad Mohammadi Amiri.

  5. 2021

    DeepWiVe for wireless video

    In 2021, he and Tze-Yang Tung coauthor DeepWiVe, an end-to-end wireless video transmission system built with deep neural networks. The system combines video compression, channel coding, and modulation in one neural transform.

  6. 2023

    An ERC grant for DeepWiVe

    In 2023, he wins an ERC Proof-of-Concept grant for DeepWiVe. The project uses deep learning to transmit video over wireless channels and improve video quality.

  7. 2025

    Semantic compression with CLIP

    He coauthors “Compression Beyond Pixels: Semantic Compression with Multimodal Foundation Models” in 2025. The paper compresses CLIP feature embeddings while preserving semantic information across tasks.

  8. As of October 2026

    Professor in information processing

    As of October 2026, he is a Professor in Information Processing in Imperial College London's Electrical and Electronic Engineering Department, leads the Information Processing and Communications Lab, and serves as Deputy Head of the Intelligent Systems and Networks Group. In September 2026, he coauthors “SING: semantic image communications using null-space and INN-guided diffusion models.”

Career

  1. Since 2012Imperial College LondonProfessor in Information Processing
  2. 2010–2012CERCA Institution
  3. 2009–2012Catalonia Institute of Telecommunications TechnologyResearch associate
  4. 2007–2012Princeton UniversityPostdoctoral research associate
  5. 2007–2012Stanford UniversityConsulting assistant professor

Education

  1. 2007New York UniversityPh.D. in electrical engineering
  2. 2004New York UniversityM.S. in electrical engineering

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

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Imperial 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.
  2. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Stanford University. 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.
  3. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Imperial 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.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Imperial College London. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Colleagues

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

Sources and credits

Photo: We have no published photo of Deniz Gündüz yet. Send us a free-licensed photo.

  1. Deniz Gunduz – 5G Italy 2020 5gitaly.eu. Checked 21 October 2026.
  2. 2017 CTTC Early Achievement Award for Electrical Engineering | Imperial News imperial.ac.uk. Checked 21 October 2026.
  3. Machine Learning in the Air | arXiv arxiv.org. Checked 21 October 2026.
  4. Communicate to Learn at the Edge | arXiv arxiv.org. Checked 21 October 2026.
  5. The President's Page - September 2022 | IEEE Communications Society comsoc.org. Checked 21 October 2026.
  6. DeepWiVe: Deep-Learning-Aided Wireless Video Transmission | arXiv arxiv.org. Checked 21 October 2026.
  7. Two Imperial engineers win European grants for pioneering research | Imperial News imperial.ac.uk. Checked 21 October 2026.
  8. Compression Beyond Pixels: Semantic Compression with Multimodal Foundation Models | arXiv arxiv.org. Checked 21 October 2026.
  9. Deniz Gunduz | Research groups | Imperial College London imperial.ac.uk. Checked 21 October 2026.
  10. Deniz Gunduz | Publications | Imperial College London profiles.imperial.ac.uk. Checked 21 October 2026.