Machine Learning: Brain waves using EEG

Workshop TitleMachine Learning Based Brainwaves Electroencephalography EEG Decoding and Understanding

Workshop Date: 3rd & 4th Jan 2018

Presented by:
Dr Ebrahim A. Mattar
College of Engineering – University of Bahrain.

Workshop Contents:
DAY NO.1: WEDNESDAY, 3rd OF JANUARY 2018
09:00 – 09:15: INTRODUCTION
09:15 – 09:45: Part_01: Workshop Introduction and Robotics Precepts
09:45 – 10:00: Part_02: Why attending this workshop?
10:00 – 10:15: Part_03: Benefits of Advanced Robotics Applications
10:15 – 10:30: Coffee Break
10:30 – 11:30: Part_04: Data Mining for Robotics Applications
11:30 – 12:30: Lunch Break
12:30 – 13:30: Part_05: Machine Learning Tools, Learning Systems, Deep Learning.
13:30 – 14:30: Part_06: Neural Nets, Fuzzy Clustering, PCA, ICA, & SV Machine
END OF DAY ONE

DAY NO.2: THURSDAY, 4th OF JANUARY 2018

09:00 – 10:15: Part_07: Understanding Electroencephalography for Robotics Deep Learning.
10:15 – 10:30: Coffee Break
10:30 – 11:00: Part_08: Electroencephalography (EEG). The Experiments and International Setups
11:00 – 11:30: Part_09: Electroencephalography (EEG) Signals Processing and Filtering
11:30 – 12:30: Part_10: Decoding and Deep Learning of the EEG Brainwaves
12:30 – 13:30: Lunch Break
13:30 – 14:30: Part_11: Results and Verifications of Decoding and Deep Learning of the EEG
Brainwaves
14:30 – 15:00: Part_12: Certifications.

 

Workshop Abstract:
Electroencephalography – or EEG Brainwaves – Clustering and Decoding, do represent the most difficult challenges related in using brainwaves for typical BMI or BCI use and applications. This workshop will look into using modern tools and initiatives based on Machine Intelligence to understand these complex waves and data mining within there depth.

In this respect, robotics dextrous grasping, rehab applications and BMI, are just typical examples of such new engineering use and wide dimensions. For example, and in particular for robotics grasping, to find the best configurations of fingertips motions and forces, for dextrous applications, is not a straight forward task. Thus, we reply on the generated EEG brainwaves, to do this job. Still such EEG waves are totally massive, complicated, coupled, and sometimes are totally not understandable . We try to fine out the inner relations to do this job, and use them for robotics applications.

 

 

Speaker Bios:
University of Bahrain Assoc. Prof. of Cybernetics and Robotics, and a candidate for full professor. Qualifications: B.Sc. (Bahrain University-1986), M.Sc. (Southampton University-1989), Ph.D. (Reading University-1994, thesis written under Prof. K. Warwick supervision), Gulf Executive Program MBA (University of Virginia, Darden School of Business-2000 as selected with 30 others from GCC).

Holds other short qualifications. Professional memberships, MBSE, MIET, MIEEE, IFAC affiliate, and Bahrain IET Local Network H. Chair. Worked on (15) research projects, including KING SAUD UNIVERSITY (KSA) Robotics Project during (2010-2014). Supervised a number of (Ph.D., M.Sc., Undergraduate) thesis-projects, and currently working on multi-dimensional Brainwaves, biometric data mining, decoding and learning for robotics control and intelligence. Editor board member of a number of journals and conferences, and a reviewer for a number of journals. Awarded a number of awards, including University of Bahrain, best research in 2001, 2002, 2006, and 2007, Bahrain Police Academy Award (2012), and others research related awards. Chairing Continuing Engineering Education Dept. (1998-2002), Electrical & Electronics Engineering Dept. (2004-2009) and (2011-2013), at University of Bahrain. Over (2011-2013), was seconded to Bahrain Training Institute as Institute Director General. Headed a number of committees for research and accreditation, including: UoB ABET accreditation committee, (2005-2014), and leading a team for positive full Electrical Engineering and Electronics Engineering Programs accreditation over (2005-2010) and (2010-2014), X-member of Bahrain NATIONAL Higher Education Skills-Innovation Steering Committee, and UoB research Strategy Committee (2010-2015).

Organization of events: Organizing chair of (2) large scale conferences (2001) and (2008), regular technical events, and (11) IET Symposiums/Colloquiums. Run (20) Engineering and Educational short courses and workshops within area of Computational AI, Control-Automation. Computations Skills: C++, Matlab, Mathematica, Labview, LaTex, IMSL, NAG libraries, Unix, Windows.

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