Summer School : Machine Learning and Deep Learning Applications
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IntroductionAt Summer School, we will discuss on how to implement machine learning algorithm and deep learning framework in various application focusing on images and signals. School participants will learn methods and techniques that are crucial for understanding current research in machine learning. Participant will also have an opportunity for hands-on code execution, learn modern stochastic optimization methods and regularization techniques for neural networks.
ObjectivesUpon completion of this course, participants will be able to:
- Aims at providing an introductory and broad overview of the field of Machine Learning and Deep Learning with the focus on real-world applications.
- Introduce major deep learning algorithms, the problem settings, and their applications to solve real world problems.
TrainersIbrahima Faye is a researcher at the Centre for Intelligent Signal and Imaging Research (CISIR), a national centre of excellence. He received a BSc, MSc and PhD in Mathematics from University of Toulouse and a MS in Engineering of Medical and Biotechnological Data from Ecole Centrale Paris. His research interests include Machine learning, Mathematics, Signal and Image Processing, Science of Learning. He has published over 150 papers in peer reviewed journals and international conferences and holds 2 patents in Image Processing. He is a senior member of the IEEE and currently the vice-chair of IEEE Computational Intelligence Society (CIS), Malaysia. Fabrice Meriaudeau was born on March 18, 1971, Villeurbanne. He received both the master degree in physics at Dijon University, France as well as an Engineering Degree (FIRST) in material sciences in 1994. He also obtained a Ph.D. in image processing at the same University in 1997. He was a postdoc for a year at The Oak Ridge National Laboratory. He was the director of the Institute Health and Analyt ics (2017/2018) at the Universiti Teknologi PETRONAS Malaysia and was the Director of the Le2i (UMR CNRS), Université de Bourgogne - France, which had more than 200 staff members, from 2011 to 2016. He is now with ImVia research group at the Université de Bourgogne- France and leads the Artificial Intelligence research group. He coordinated an Erasmus Mundus Master in the field of Computer Vision and Robotics from 2006 to 2010 and was the Vice President for International Affairs for the University of Burgundy from 2010 to 2012. He has authored and co-authored more than 150 international publications and holds three patents Germain Forestier received his PhD in Computer Science from the University of Strasbourg in 2010. He then spent one year as a postdoctoral fellow at INRIA Rennes / INSERM (French National Institute for Medical and Health Research), where he worked on biomedical data analysis. In September 2011, he obtained a position of Associate Professor at the University of Haute-Alsace (France) and is now Professor since 2018. Prof. Forestier also hold a position of Associate Professor (Adjunct) at the Monash University (Australia). His research interests include data science, data mining, time series, machine learning, big data, artificial intelligence and deep learning. More info: https://germain-forestier.info/ Tang Tong Boon received his received the B.Eng. degree (Hons) and Ph.D. degree from The University of Edinburgh. He is currently the Director of Institute of Health and Analytics, and an Associate Professor of Electrical and Electronic Engineering Department at the Universiti Teknologi PETRONAS. His research interests are in biomedical image analysis and artificial intelligence. He received the Lab on Chip Award in 2006 and the IET Nanobiotechnology Premium Award in 2008. He serves as the Secretary of the Higher Centre of Excellence (HICoE) Council and the Chair of the IEEE Circuits and Systems Society Malaysia Chapter. Eric Ho Tatt Wei received his MS and PhD degrees in Electrical Engineering from Stanford University in Silicon Valley, USA specializing in computer hardware and VLSI systems, As part of his PhD research, he developed real-time systems for fruit flies for biological research to conduct automated inspection and guide robotic manipulation. He is currently pursuing applications of deep neural network technology to network analysis on MRI brain images.
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Introduction At Summer School, we will discuss on how to implement machine learning algorithm and deep learning framework in various application focusing on images and signals. School participants will learn methods and techniques that are crucial for understanding current research […]
Price : 1,500 for Professional (Discount available for students, group registration, PETRONAS staff, and UTP alumni) MYR
Max Availability : 24
Location : Universiti Teknologi PETRONAS (UTP)