• 2019, Making Alexa more Knowledgable, Innovation@Amazon, Gdańsk, Poland. Video
  • 2018, Scaling and tackling the fundamental challenges in drug discovery by developing innovative AI technology, Intelligent Health AI, Basel, Switzerland. Video
  • 2018, Predictive and Generative Deep Learning for Graphs, Re-Work Deep Learning, London, UK. Slides
  • 2018, AI Augmentation and Creativity, The Foundation for Science and Technology - The impact of ML on Society, London, UK. Slides, Audio recording
  • 2017, Machine Learning for Drug Discovery, London Machine Learning Meetup, London, UK. Slides
  • 2011, Learning with Ambiguities Tutorial, Visual Geometry Group, Oxford University, UK. Slides
  • 2010, Semi-Supervised Learning in Vision Tutorial, CVPR 2010
    • Introductions and motivations: Horst Bischof slides
    • Theory of Semi-Supervised Learning: Amir Saffari slides
    • Algorithms and Applications: Christian Leistner slides
  • 2009, Regularized Multi-Class Semi-Supervised Boosting, CVPR 2009. Slides
  • 2009, On-line Random Forests, ICCV. Slides
  • 2008, Boosting for Model-Based Data Clustering, Symposium of the German Association for Pattern Recognition (DAGM).
  • 2007, An Introduction to Ensemble and Boosting Methods, PASCAL Bootcamp in Machine Learning, Vilanova i la Geltrú, Spain. (PDF) (Video)
  • 2007, Introduction to CLOP Machine Learning Toolbox, PASCAL Bootcamp in Machine Learning, Vilanova i la Geltrú, Spain. (PDF) (Video)
  • 2007, A Comparisonal Study on Dynamic Texture Description and Recognition Methods using Local Features and Optical Flow, Institute for Computer Graphics and Vision, Graz University of Technology, Austria.
  • 2006, Ensemble and Boosting Methods for Clustering, Institute for Computer Graphics and Vision, Graz University of Technology, Austria.
  • 2006, Sparse and Overcomplete Representation, Institute for Computational Sciences, ETH Zurich, Switzerland.
  • 2005, Sparse and Overcomplete Representation: Finding Statistical Orders in Natural Images, Institute for Theoretical Computer Science, Graz University of Technology, Austria. PDF
  • 2005, A Short Review on HMAX Model for Biological Object Recognition, Mini-Workshop on Learning in the Cognitive Vision Project, Institute for Theoretical Computer Science, Graz University of Technology, Austria. PDF
  • 2005, Constellation Models for Object Recognition, Institute for Theoretical Computer Science, Graz University of Technology, Austria. PDF
  • 2005, An Introduction to NEST, Institute for Theoretical Computer Science, Graz University of Technology, Austria. PDF
  • 2004, An Introduction to Brain Theory and Neural Networks, SUT Research Week, Sahand University of Technology, Tabriz, Iran.
  • 2003, An Introduction to Chaos Theory, SUT Research Week, Sahand University of Technology, Tabriz, Iran. PDF
  • 2002, Information Processing using Chaotic Dynamics, M.Sc. Seminar, Department of Biomedical Engineering, Tehran Polytechnic (Amir Kabir University of Technology), Tehran, Iran.
  • 2001, Adaptive Stabilization of Lorenz Chaos, Adaptive Control Seminar, Biomedical Eng. Dept., Tehran Polytechnic (Amirkabir University of Technology), Tehran, Iran. PDF, Code
  • 2001, Pulse-Coupled Neural Networks (PCNN, Advanced Topics in Neural Networks Course Seminar*, Department of Biomedical Engineering, Tehran Polytechnic (Amir Kabir University of Technology), Tehran, Iran.
  • 2000, Mehdi Azizian, Chaos Theory, 3rd Conference of Electrical Engineering Students of Iran, Tehran, Iran.
  • 2000, Chaos, Perception and Cognition, Cybernetics and System Eng. Course Seminar, Department of Biomedical Engineering, Tehran Polytechnic (Amir Kabir University of Technology), Tehran, Iran.
  • 2000, Chaos and Fractal in CNS, Neuro-Muscular Control Systems Course Seminar, Department of Biomedical Engineering, Tehran Polytechnic (Amir Kabir University of Technology), Tehran, Iran.
  • 1999, Chaos Theory in Biomedical Engineering, 1st Conference of Biomedical Engineering Students of Iran, Tehran, Iran.