Are you ready for the AI
revolution? How will machine learning impact your business, research and
career? Hear from academics researchers who are at the fore-front of
AI and Machine Learning in Europe and Pakistan. What are the most
important concepts in AI and Machine Learning today? Come and attend
in-depth talks on: Deep learning, 3D Object Tracking, Automatic
handwriting recognition, Speech recognition, Computer Vision and
Biomedical Applications of Machine Learning. This symposium is the
first in a series of upcoming workshops in Machine Learning and AI. The
objective of this workshop is to provide participants a high-level
overview of the basics of Machine Learning and introduce them to a
number of cutting edge applications.
This workshop is designed to provide you an introduction to the following topics
- Basics of Machine Learning.
- Current Trends in Machine Learning and AI.
- 3D Object Tracking.
- Automatic Handwriting Recognition.
- Multi-modal Photo-graphics Retrieval.
- Automatic Speech Recognition (Basics, Hidden Markov Models and Deep Neural Networks)
- Open source toolkits for Machine Learning and Speech Recognition
- Medical Imaging Applications of Machine Learning (Opportunities & Challenges)
After participating in this symposium, you will be able to:
- Develop an understanding of the
fast-changing landscape of Machine Learning – key breakthroughs, useful
Machine Learning tools for business and research applications.
- Get an overview of a number of cutting edge applications of AI.
- Get pointers to the best online educational resources for Machine Learning.
- Get advice on the best data repositories for training Machine Learning algorithms.
- Develop a strategy on how to prepare yourself for a career in Machine Learning.
- Dr. Faisal Shafait (Associate Professor, NUST SEECS)
- Dr. Hassan Aqeel Khan (Assistant Professor, NUST SEECS)
- Dr. Muhammad Ali Tahir (Assistant Professor, NUST SEECS)
Dr. Ulrich Schwanecke studied
Mathematics and Computer Science at the Johannes Gutenberg University
Mainz, where he graduated as a Diplom-Mathematiker in 1997. From 1997
to 2000 he was a research assistant at the Center of Applied
Mathematics at the University of Technology in Darmstadt, where he
gained a PhD in 2000. From 2000 to 2001 he worked as a postdoctoral
research assistant at the Max-Planck-Institute for Computer Science in
Saarbrücken. From 2001 to 2003 he worked as a research assistant at the
Research and Technology Center of DaimlerChrysler in Ulm. Since 2003 he
is a professor for Computer Science in Media at the RheinMain
University of Applied Sciences Wiesbaden Rüsselsheim Geisenheim. His
research interests include Computer Aided Geometric Design, Computer
Graphics, Digital Image Processing and Computer Vision.
Dr. Adrian Ulges
graduated from TU Kaiserslautern (2009 PhD in computer science, 2005
diploma in computer science) and has been as a researcher with the
German Research Center for Artificial Intelligence (DFKI) in
Kaiserslautern / Germany (2005-2011). His research interests are in
maschine learning, computer vision, and multimedia analysis. He worked
with Google as an intern (2005, Mountain View) and as a visiting
scientist (2011, Zurich). Since 2013, he is been a full professor at
RheinMain University of Applied Sciences (HSRM), with interests in
applied mathematics and machine learning. Adrian's research has been
awarded with a Google Research Award in 2010, and his publication
record includes over 30 peer-reviewed papers.
Dr. Faisal Shafait
completed his PhD from the University of Kaiserslautern, Germany in
2008 and his work has been published in top machine learning
conferences and journals such as the IEEE Transactions on Pattern
Analysis and Machine Intelligence, IEEE Transactions on Image Processing
and the IEEE’s Conference on Computer Vision and Pattern Recognition
(CVPR). Faisal served as a member of the leadership board of the
International Association of Pattern Recognition (IAPR) from 2013 –
2016. He also periodically serves on the program committees of
international computer vision and document analysis conferences.
Dr. Hassan Aqeel Khan
completed his PhD in Electrical Engineering from Michigan State
University, USA in 2016. During his PhD he worked on a number of NSF and
NIH funded projects within the domain of Biomedical applications of
Machine Learning. During his PhD he collaborated with industry giants
such as GE Healthcare. He is currently the Director of the Sigma
Research Lab at NUST SEECS whose focus is Medical Imaging and networking
applications of Machine Learning.
Dr. Muhammad Ali
Tahir has completed his Ph.D. in Automatic speech recognition from RWTH
Aachen University. During his 11 year stay in Germany he has worked on
different EU-funded projects related to speech recognition, primarily
aiming to bridge the language divide in a multilingual Europe. During
his time at NUST he has been collaborating with local industry to create
Urdu voice based solutions for conversational agents and vehicle
Who Should Attend?
- Industry professionals
- Graduate and Undergraduate students
- Business leaders
- Academics looking for inter-disciplinary research opportunities