PeopleofSuperintelligence

Researcher

Nuno M. Vasconcelos

Also known as Nuno Vasconcelos, Nuno Miguel Borges de Pinho Cruz de Vasconcelos

Nuno Vasconcelos is an electrical and computer engineering professor at UC San Diego who heads the Statistical Visual Computing Laboratory, where research in computer vision and machine learning aims to give computers the ability to perceive complex visual scenes. He grew up in Portugal, studied at the Universidade do Porto, and completed an MIT PhD in 2000, with a CVPR 2000 paper on probabilistic image retrieval coauthored with Andrew Lippman. After research-staff work at Compaq and HP in Cambridge, he joined UC San Diego in 2003, won an NSF CAREER grant and a Hellman Fellowship in 2005, and became an IEEE Fellow in 2017. His papers include a 2010 CVPR study of anomalies in crowded scenes, the MS-CNN detector in 2016, and the Cascade R-CNN detector in 2018.

Badges

Timeline

  1. 1988–2000

    From Porto to an MIT PhD

    Raised in Portugal, he earns a bachelor's degree in electrical and computer engineering at the Universidade do Porto in 1988 and works as a researcher at the Instituto de Engenharia de Sistemas e Computadores until 1991. He is a research assistant at MIT's Media Laboratory from 1991 to 2000, earns a master's degree in Media Arts and Sciences at MIT in 1993, and receives his PhD from MIT in 2000. His CVPR 2000 paper with Andrew Lippman, "A Probabilistic Architecture for Content-Based Image Retrieval", presents a retrieval architecture whose modules all optimize the same criterion, the probability of retrieval error.

  2. 2003

    Joining UC San Diego

    After working on the research staff of the Compaq Cambridge Research Laboratory, which became the HP Cambridge Research Laboratory, he joins the Electrical and Computer Engineering faculty of UC San Diego's Jacobs School of Engineering in 2003. He heads the Statistical Visual Computing Laboratory.

  3. 2005

    NSF CAREER and Hellman awards

    In 2005, the National Science Foundation awards him a five-year CAREER grant of $435,000 for research on weakly supervised recognition, techniques that detect and recognize objects in large image and video repositories. He also receives a Hellman Fellowship in 2005.

  4. 2010

    Anomaly detection in crowded scenes

    In 2010, he coauthors the CVPR paper "Anomaly Detection in Crowded Scenes" with Vijay Mahadevan, Weixin Li and Viral Bhalodia. It models normal crowd behavior with mixtures of dynamic textures, labels outliers as anomalies, and tests the approach on a new dataset of 100 video sequences with five abnormality categories.

  5. 2016

    The MS-CNN object detector

    In 2016, he coauthors the multi-scale CNN (MS-CNN) with Zhaowei Cai, Quanfu Fan and Rogerio S. Feris, a unified deep network for fast multi-scale object detection. It reports state-of-the-art detection at up to 15 frames per second on the KITTI and Caltech datasets.

  6. 2017

    Elevated to IEEE Fellow

    He is elevated to IEEE Fellow in 2017 for contributions to computer vision, image processing, and multimedia.

  7. 2018

    Cascade R-CNN at CVPR

    In 2018, he and Zhaowei Cai publish Cascade R-CNN in the CVPR proceedings, a multi-stage object detector built from a sequence of detectors trained with increasing intersection-over-union thresholds. A simple implementation surpasses all single-model object detectors on the COCO dataset.

  8. As of October 2026

    Professor at UC San Diego

    He is a professor of electrical and computer engineering at UC San Diego, where he heads the Statistical Visual Computing Laboratory. His research aims to provide computers with the ability to perceive complex visual scenes and make inferences from them. In January 2026, he coauthors "Leveraging Data to Say No: Memory Augmented Plug-and-Play Selective Prediction", a paper on giving predictors a reject option for vision-language foundation models, which appears as an ICLR 2026 poster.

Career

  1. Since 2003University of California, San DiegoProfessor of Electrical and Computer Engineering
  2. 1991–2000Massachusetts Institute of TechnologyResearch assistant
  3. 1988–1991Institute for Systems and Computer EngineeringResearcher
  4. CompaqResearch staff

Education

  1. 2000Massachusetts Institute of TechnologyPhD
  2. 1993Massachusetts Institute of TechnologyMaster's degree in Media Arts and Sciences
  3. 1988University of PortoBachelor's degree in electrical and computer engineering

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of California, San Diego. 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.
  2. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes University of California, San Diego. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Massachusetts Institute of Technology. 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.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of California, San Diego. 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.

Colleagues

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

Sources and credits

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  1. Nuno Vasconcelos | Jacobs School of Engineering jacobsschool.ucsd.edu. Checked 22 October 2026.
  2. NSF Selects Two UC San Diego Experts in Computer Vision to Receive Five-Year CAREER Grants jacobsschool.ucsd.edu. Checked 22 October 2026.
  3. Computers that See | Benefunder benefunder.com. Checked 22 October 2026.
  4. A Probabilistic Architecture for Content-Based Image Retrieval | ML Anthology mlanthology.org. Checked 22 October 2026.
  5. Nuno Vasconcelos | Vision vision.ucsd.edu. Checked 22 October 2026.
  6. SVCL - Nuno Vasconcelos svcl.ucsd.edu. Checked 22 October 2026.
  7. Anomaly Detection in Crowded Scenes | ML Anthology mlanthology.org. Checked 22 October 2026.
  8. A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection arxiv.org. Checked 22 October 2026.
  9. 2017 IEEE Fellow - Professor Nuno Vasconcelos | Electrical and Computer Engineering ece.ucsd.edu. Checked 22 October 2026.
  10. CVPR 2018 Open Access Repository: Cascade R-CNN: Delving Into High Quality Object Detection openaccess.thecvf.com. Checked 22 October 2026.
  11. Leveraging Data to Say No: Memory Augmented Plug-and-Play Selective Prediction arxiv.org. Checked 22 October 2026.
  12. ICLR Poster Leveraging Data to Say No: Memory Augmented Plug-and-Play Selective Prediction iclr.cc. Checked 22 October 2026.