Lambert Schomaker

Interests & projects

• Within artificial intelligence, my focus is on perceptual intelligence and (lifelong) machine learning
• Valedictory lecture, held in Groningen March 8th 2024 (.pdf of text with slides) Also see: https://zenodo.org/records/10967461 for the video.
• Neuromorphic computing: new analog electronic materials for next-generation low-power AI systems: CogniGron

  The traditional CMOS community thinks there is no problem and quantum computing has many claims for the future.
  Neuromorphic computing is positioned in the middle and will provide low-energy solutions soon,
  first 'on the edge' (IoT) but later also in HPC centers.

• Monk is our continuous project for allowing access to large and diverse historical archives which are difficult to access by means of traditional 'OCR' approaches due to their special fonts or handwritten style. Since 2009, Monk provides a means of continuously training handwriting recognizers that create indices of handwritten collections. Monk was one of the demonstrators in the EU/SNN Target project
• May 2019: EU/ITN Manic project approved, participation: ML and neuromorphic computing / cognitive materials
• 2018 EU/ITN Perico project participation: Machine learning for peroxisome classification
• Dead Sea Scrolls ERC project with Mladen Popovic (PI) and Hans van der Plicht (¹⁴C dating)

Recent

• 2026-09-28 - As I am retired now, I cannot accept Phd students, MSc project students (e.g. Erasmus) etc., sorry!

• 2026-05-01 - Frozen Monk: list of book/manuscript tarballs on the Monk system, with images and labels

• 2023-08-01 - Received: 10M€ grant: HAICu project on AI for the cultural heritage

• 2022-09-27 - Refs for discussion on brain & geometry LinkedIn discussion

• 2020-09-08 - EU project MANIC is to synthesize materials that can function as networks of neurons and synapses by integrating conductivity, plasticity and self-organization. PhD student Davide Cipollini

• 2020-03-03 - AI colloqium From Boston to Eden - or how to get systems that are really autonomous and sufficiently intelligent to survive in their niche. In this presentation I argue that reinforcement learning methods currently are still very much handcrafted. Only an optimal reward structure and schedule yields success, which requires often more than an single PhD project. On the other hand, the human and animal brain do not have the helping hand of an ever-present external engineer setting up the framework for survival. Modern AI should take a better look at what is known about the old brain, which provides a general but quick valuation of the current state of the world. This would allow for a really autonomous reinforcement learning which does not require the development of painstakingly handcrafted reward structures, neural-network hyper-parameter values and specifically optimized training schedules.

• 2016-10-15 Robot demo: "Alice the cleaning robot" With Amir Shantia, Francesco Bidoia and student team.

Activities

• Lambert Schomaker on ResearchGate
• Previous
• Current
• News on Research
• Old newspaper snippets
• Miscellaneous
• 'Current' AI Master Projects (this list is never up to date)
• Previous MSc/AI student projects
• Algorithms & Methods
  • Hinge feature for writer identification (Bulacu & Schomaker)
  • Allographic fraglet codebooks for writer identification (Schomaker & Bulacu)

• Publications
• Older Publications,
  • Abstracts,
  • Papers,
  • Slides
• People in my group
• Former M.Sc. Students
• Ph.D. involvement
• Courses

Former post-doctoral researchers

• Gideon Maillette de Buy Wenniger (machine translation, LSTMs)
• Hamidreza Kasaei (robotics)

• Sukalpa Chanda writer identification and curvilinear line segmentation, deep learning for word recognition

Current PhD students

1. Jordi Timmermans - Neuromorphic computing (electronic sensorimotor circuit modeling) with prof. Tamalika Banerjee, materials science)
2. Koen van Schuijlenburg - Lifelong machine learning with humans in the loop (HAICu)

(previous PhD students)

• Asmaa Haja - Deep learning methods for microscopy in biology
• Sha Luo - Reinforcement-based learning of object handling in robots
• Mahya Ameryan - Deep learning for text recognition and pictorial semantics
• Maruf Dhali - Dead Sea Scrolls, document dating and writer identification
• Anouk Goossens - Building blocks for electronic brains (co-supervisor with prof. Tamalika Banerjee)
• Davide Cipollini - Neuromorphic computing (deep learning for electron microscopy, with prof. Beatriz Noheda, materials science)
• Zhenxing Zhang - Text-to-image GANs (dissertation 7 Febr. 2023.) Zhenxing was ready in 3 years!
• Jean-Paul van Oosten - Continuous labeling and learning
  Jean-Paul has obtained, at the ICFHR 2012, the IAPR Best Paper Award: Jean-Paul Van Oosten, Lambert Schomaker (2010). Separability versus Prototypicality in Handwritten Word Retrieval, Proc. Int. Conference on Frontiers in Handwriting Recognition, September 18-20 2012, Bari, Italy, IEEE Computer Society, pp. 8-13, DOI 10.1109/ICFHR.2012.269
• Amir Shantia - Robotics perception and navigation (together with Marco Wiering)
• Bowornrat Sriman (camera-based text detection and recognition for Asian scripts)
• Sheng He (writing style-based dating of handwritten manuscripts, dissertation 2017, 'cum laude' - with honors)
• Marius Bulacu (writer identification, dissertation 2007)
• Tijn van der Zant (handwritten historical document retrieval, dissertation 2010)
• Axel Brink (robust writer identification and verification, dissertation 2011)
• Gert Kootstra (biologically inspired robot vision and navigation, dissertation 2010)
• Hado van Hasselt (reinforcement learning systems, with Marco Wiering, dissertation 2011)

Current M.Sc. projects

• M.Sc. project topics