PeopleofSuperintelligence

Researcher

Mamshad Nayeem Rizve

Mamshad Nayeem Rizve is a computer vision researcher who works on learning with limited labels, including semi-supervised, few-shot and self-supervised learning. He studied electrical engineering at the Bangladesh University of Engineering and Technology, worked as a system engineer at Grameenphone from 2016 to 2018, and completed a PhD at the University of Central Florida's Center for Research in Computer Vision under Mubarak Shah in 2023. His Gabriella system for activity detection in security videos won a best paper award at ICPR 2020, and in 2024 his paper "Is ImageNet worth 1 video?", written with Shashanka Venkataramanan, João Carreira, Yuki M. Asano and Yannis Avrithis, earned an honorable mention at ICLR. After a postdoctoral post at Amazon Search Science & AI from 2023 to 2025, he is a Senior Applied Scientist at Adobe, where his recent papers cover controllable image generation and prompt design for text-to-visual generation.

Now at
Adobe
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Timeline

  1. 2012–2016

    Electrical engineering at BUET

    He studies electrical engineering for a BSc at the Bangladesh University of Engineering and Technology from 2012 to March 2016.

  2. 2016–2018

    System engineer at Grameenphone

    From September 2016 to July 2018, he works as a system engineer at Grameenphone Limited, where he supervises a transmission network of more than 15,000 nodes.

  3. 2018–2023

    PhD with Mubarak Shah

    He begins a PhD in August 2018 at the Center for Research in Computer Vision at the University of Central Florida, advised by Mubarak Shah, and finishes in 2023. His doctoral research centers on learning with limited labels: semi-supervised, few-shot and self-supervised learning.

  4. 2020–2022

    Gabriella and semi-supervised learning

    In 2020, he is first author of Gabriella, a real-time online system for activity detection in untrimmed security videos, which receives a best paper award at ICPR. In 2021, he is first author of an ICLR paper with Kevin Duarte, Yogesh S. Rawat and Mubarak Shah that selects pseudo-labels by their uncertainty for semi-supervised learning. In 2022, his ECCV oral paper Towards Realistic Semi-Supervised Learning, with Navid Kardan and Mubarak Shah, applies pseudo-labeling to open-world data that may contain unknown classes.

  5. 2023–2025

    Postdoc at Amazon Search

    In August 2023, he joins Amazon Search Science & AI as a postdoctoral scientist, working on video understanding and large language models. He holds the post until 2025.

  6. 2024

    ICLR honorable mention for DoRA

    In 2024, his paper Is ImageNet worth 1 video?, written with Shashanka Venkataramanan, João Carreira, Yuki M. Asano and Yannis Avrithis, receives an honorable mention among the ICLR 2024 awards. It introduces the Walking Tours dataset of first-person videos and the DoRA method, with which a single Walking Tours video becomes a strong competitor to ImageNet for several image and video tasks.

  7. 2025

    CompSlider at ICCV 2025

    In 2025, he co-authors CompSlider with Zixin Zhu, Kevin Duarte, Chengyuan Xu, Ratheesh Kalarot and Junsong Yuan, with Adobe as his affiliation. The ICCV 2025 paper controls several attributes of a generated image at once, such as age or smile, without retraining the text-to-image foundation model.

  8. Since 2025

    Senior Applied Scientist at Adobe

    He becomes a Senior Applied Scientist at Adobe in San Jose, California, in 2025. In 2026, he co-authors Rethinking Prompt Design for Inference-time Scaling in Text-to-Visual Generation at CVPR, with Subin Kim, Sangwoo Mo and others; its PRIS framework revises the prompt during inference and gains 15% on VBench 2.0.

Career

  1. Since 2025AdobeSenior Applied Scientist
  2. 2023–2025AmazonPostdoctoral Scientist
  3. 2016–2018Grameenphone LimitedSystem Engineer

Education

  1. 2023University of Central FloridaPhD in Computer Science
  2. 2016Bangladesh University of Engineering and TechnologyBSc in electrical engineering

From the biography.

  1. 16% of AI career moves in the 2020s went from a university to a companyIncludes Mamshad Nayeem Rizve. We estimate that 16% of AI career moves in the 2020s went from a university to a company; 29% of moves starting at a university went to a company, and 76% ended the university role.
  2. Among employers with 30+ full-time cases, OpenAI leads primary technical role H-1B pay at $310,000, and Amazon, Google and Microsoft file 57% of all casesIncludes Adobe. Across 440,669 certified US H-1B filings from 44 employers (FY2020–FY2026), OpenAI leads primary technical role base pay at $310,000 and xAI leads overall base pay at $290,000.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Adobe. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. Google has the highest combined h-index among AI organizationsIncludes Adobe. 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.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Mamshad Nayeem Rizve | alphaXiv alphaxiv.org. Checked 21 October 2026.
  2. Mamshad Nayeem Rizve nayeemrizve.github.io. Checked 21 October 2026.
  3. Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos – Center for Research in Computer Vision crcv.ucf.edu. Checked 21 October 2026.
  4. In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning arxiv.org. Checked 21 October 2026.
  5. Towards Realistic Semi-Supervised Learning arxiv.org. Checked 21 October 2026.
  6. Is ImageNet worth 1 video? Learning strong image encoders from 1 long unlabelled video arxiv.org. Checked 21 October 2026.
  7. ICLR 2024 Awards iclr.cc. Checked 21 October 2026.
  8. Congratulations to Shashanka Venkataramanan for his Best paper | Website of IRISA irisa.fr. Checked 21 October 2026.
  9. CompSlider: Compositional Slider for Disentangled Multiple-Attribute Image Generation (ICCV 2025 Open Access Repository) openaccess.thecvf.com. Checked 21 October 2026.
  10. CompSlider: Compositional Slider for Disentangled Multiple-Attribute Image Generation arxiv.org. Checked 21 October 2026.
  11. Rethinking Prompt Design for Inference-time Scaling in Text-to-Visual Generation (CVPR 2026 Open Access Repository) openaccess.thecvf.com. Checked 21 October 2026.