Artificial Intelligence (AI) is changing the world as it is being increasingly applied to build Smart Cities for improving people’s lives with cutting-edge urban planning and infrastructure and latest digital and information technologies. This workshop explores how AI enables Smart Cities through foundational topics in AI, Big Data, Machine Learning, Cyber-Physical Systems (CPS), Internet of Things (IoT), Cyber Security and Blockchain, and Cloud Computing. Participants will engage in case study exercises to critically think about the application of these technologies that enable Smart Cities.

Learning Outcomes:
  • Building a knowledge base of the latest technological innovations, strategies, and policies being developed by industry and academia.
  • Developing new concepts and designs by participating in case study applications that focus on real-world implementation.
  • Developing a holistic and system-level perspective on AI and smart sustainable cities.

Who Should Attend:
This workshop does not assume any technical background. Executives, business unit leaders and managers, engineers/designers, investors and urban planners focused on the built environment, personal mobility and transit, energy, IT infrastructure, food,and Smart Cities development. Government leaders, ministry and agency leaders, department directors, innovation managers, policymakers and city planners responsible for new urban economic development and design of new cities.

Day 1:

Cyber Physical Systems
  • Introduction to CPS
  • Sensors
  • Microcontrollers
  • Control Systems
  • Smart structures
  • Real-time OS
  • Case Studies
Internet of Things
  • Introduction to IoT
  • IoT Architectures and Protocols
  • Programming the IoT
  • Integration with AI

Day 2:

Cloud
  • Introduction to cloud computing
  • Hosting AI on AWS, Google,Azure
  • AI tools on the cloud
  • AI/Cloud case studies
Artifical Intelligence
  • Introduction to Artificial Intelligence
  • Symbolic AI
  • Computer Vision
  • Robotics
  • Computational Linguistics
  • Case Studies in Smart Cities

Day 3:

Machine Learning
  • Introduction to cloud computing
  • Hosting AI on AWS, Google,Azure
  • AI tools on the cloud
  • AI/Cloud case studies
  • Introduction to Machine Learning
  • Supervised Learning Methods
  • Unsupervised Learning Methods
  • Deep Learning
  • Case Studies in Smart Cities
Cyber Security & Blockchain
  • Introduction to Security
  • IoT & Cloud Security
  • Smart City Infrastructure Security
  • Physical Security
  • Blockchain for Smart Cities
  • Case Studies

*Course structure may be subject to change.

The workshop will be presented by:

Dr. Fadi Aloul, Professor and Department Head of Computer Science and Engineering at AUS.

Dr. Aloul received his PhD from University of Michigan, Ann Arbor, USA, 2003. Dr. Aloul's areas of expertise include cyber security, mobile applications and design optimization. He is a Certified Information Systems Security Professional and the founder of several cyber security awareness initiatives in the UAE including the UAE's Cyber Academy. Dr. Aloul has received a number of awards including the Global Engineering Deans Council Airbus Engineering Diversity Award, Khalifa Award for Higher Education, Sheikh Rashid Award for Outstanding Scientific Achievement, Abdul Hameed Shoman Award for Young Arab Researchers, AUS Excellence in Teaching Award and the Semiconductor Research Corporation Fellowship. He has 100+ publications and 1 US patent. He is a frequently invited speaker and panelist at international conferences related to cyber security, technology, innovation and education.

Dr. Abdulrahman Al-Ali, Professor of Computer Science and Engineering at AUS.

Dr. Al-Ali received his PhD from Vanderbilt University, Nashville, TENN., USA, 1990. Dr. Al-Ali's research and teaching interests include embedded systems hardware and software architectures, interface and programming, and applications in smart grid, remote monitoring and control industrial plants utilizing Internet, GSM and GPRS networks Dr. Al-Ali has around 100 publications, one US patent and one European patent. He has been a keynote and an invited speaker at several conferences. He is a member of the Institute of Electrical and Electronics Engineers (IEEE). He previously taught at King Fahd University of Petroleum and Minerals in Saudi Arabia.

Dr. Imran Zualkernan, Professor of Computer Science and Engineering at AUS.

Dr. Zualkernan received his PhD from University of Minnesota, Minneapolis, USA, 1991. Dr. Zualkernan has taught at the University of Minnesota and Pennsylvania State University. He has held C-Level positions in various startup companies. His current research interests include ubiquitous tangible learning systems, wearable learning, and adoption and alignment models for learning technologies. He has published over 80 papers in refereed conference proceedings and journals.

Dr. Michel Pasquier, Associate Professor of Computer Science and Engineering at AUS.

Dr. Pasquier received his PhD from the National Polytechnic Institute of Grenoble, France, 1989. Dr. Pasquier has 15 years' experience teaching artificial intelligence and related CS courses at the Nanyang Technological University of Singapore. Previously, he was a researcher for the AIST and Sanyo Electric in Tsukuba, Japan. His research interests include cognitive computing and systems, adaptation and learning, knowledge discovery, as well as nature-inspired methods for approximate reasoning and decision making. He has published, led projects and served as a consultant in application areas including intelligent robotics and transportation systems, online learning, medical diagnosis and healthcare, and financial engineering.

Dr. Raafat Aburukba, Assistant Professor of Computer Science and Engineering at AUS.

Dr. Aburukba received his PhD from University of Western Ontario, London, ON, Canada, 2013. Dr. Aburukba's areas of expertise include cloud computing, decentralized scheduling, smart spaces, economic-based modeling and approaches, and collaborative intelligence and assistance. Prior to joining AUS he was a faculty member with the Department of Computer Science and Software Engineering at Pennsylvania State University. He was also a senior software engineer research assistant at EK3 technologies where he led multiple research and commercialization projects.

Dr. Salam Dhou, Assistant Professor of Computer Science and Engineering at AUS.

Dr. Dhou received her PhD from Virginia Commonwealth University, Virginia, USA, 2013. Dr. Dhou's areas of expertise include computer vision, medical imaging and informatics, robotics, machine learning, and data mining. Prior to joining AUS she was a visiting assistant professor in the Department of Mathematics and Computer Science at University of Missouri, St. Louis, USA. She worked also a post-doctoral research fellow for three years in the School of Medicine at Harvard University where she published and participated in multiple research projects. Dr. Salam is a member of the Institute of Electrical and Electronics Engineers (IEEE) Computer Society, and the American Association of Physicists in Medicine (AAPM).

Ms. Diane Gregorio
Department of Computer Science and Engineering
Administrative Assistant
Email: cse@aus.edu
Tel: +97165152969