Atsuto Maki

Received PhD from KTH (after MEng from U Tokyo) and hold a position of Professor of computer science at the School of Electrical Engineering and Computer Science. In past he was an associate professor of the Graduate School of Informatics at Kyoto University, and has worked in industy for 10+ years (Toshiba Research Cambridge lab and Toshiba Corporate R&D) where he developed computer vision systems, e.g. for automatic Radar image analysis.

He teaches Machine Learning (DD2421) while being the Vice-Director of the Master’s Programme in Machine Learning (TMAIM). The course has been taken by 5K+ students in the last decade. He also serves as KTH coordinator for partnerships with The University of Tokyo as well as with The National Institute of Informatics (NII).

His main reseach interests cover a broad range of topics in machine learning, deep learning, and computer vision, including motion and object recognition, clustering, subspace analysis, stereopsis, and representation learning. He holds 30+ patents in the area of image analysis. He is a board member of Swedish Society for Automated Image Analysis (SSBA).

Some more information can be found here: http://www.csc.kth.se/~atsuto/

Current projects include:

• VR (Individual grant)
• WASP AI
• WASP AS
• VINNOVA/NFFP7
• SMaRC project
• COGMAR (The Research Council of Norway)

News

• Program co-Chair of ECCV 2026 (in Sweden).
• Visiting Researcher, The University of Tokyo, November-December 2023.
• My grant application to Vetenskapsrådet got accepted, called "SeDECI" - Semi-Supervised Deep Learning with Class Imbalanced Data. Thank you everyone who has supported me!
• Served as a faculty opponent of David Gillsjö's PhD thesis defence, June 2, 2023. Lund University.
• Served as a faculty opponent of David Nilsson's PhD thesis defence, June 13, 2022. Lund University.
• Assumed the Vice-Director of the Master’s Programme in Machine Learning (TMAIM) as of January. Welcome to apply for studies starting in Autumn 2020.
• Served as a faculty opponent of Van Nhan Nguyen's PhD thesis defence, December 3, 2019. UiT Machine Learning Group, The Arctic University of Norway.
• Gave a keynote at the 22nd Symposium on Image Recognition and Understanding (MIRU 2019), July 30, 2019. Location: Osaka International Convention Center.
• Served as Program Co-Chair for International Conference on Machine Vision Applications with Prof Paolo Favaro, held in May 2019 with fantastic invited lectures! Location: Tokyo.
• Gave a keynote at the 2nd Swedish Symposium on Deep Learning (SSDL 2018), September 5-6, 2018. Location: University of Gothenburg.
• RIKEN Center for Advanced Intelligece Project (AIP), Tokyo, and KTH School of EECS have signed an MoU on July 9, 2018. I'm serving as the contact at KTH.
• The Niwa-Takayanagi Best Paper Prize was awarded to our paper by the Institute of Image Information and Television Engineers (ITE) in Japan, May 30, 2018.
• Co-organised the 36th Swedish Symposium on Image Analysis (SSBA 2018), March 7-9, 2018. Location: KTH. Thank you all for sponsoring and participations!
• Gave an invited popular science talk on Machine Learning at KVA, February 14, 2018. Location: The Royal Swedish Academy of Science.
• Gave a keynote at Northern Light Deep Learning Worpshop (NLDL 2018), January 10-11, 2018. Location: The Arctic University of Norway.
• Co-organised the first Swedish Symposium on Deep Learning (SSDL 2017), June 20-21, 2017, a wonderful event with 220+ participants. Location: KTH.
• Co-organised KTH-University of Tokyo joint Workshop on Education and Academic Mobility, March 8-10, 2017. Location: The University of Tokyo.
• My grant application to Vetenskapsrådet has been accepted. That's called "Motion Representation Learning for Intelligence Surveillance - MoRLIS". Thank you everyone who has supported me!