I joined Huawei technologies research and development UK to lead the reinforcement learning team in London
I started a series of blog posts detailing some concepts in machine learning both theoretical and practical
I have a Forbes article describing the challenges in commercialising artificial intelligence
Our distributed multi-task reinforcement learning paper has been accepted for publication at the NeurIps 2018
Our distributed Newton method for large-scale optimisation has been accepted for publication in the IEEE Transactions on Automatic Control (TAC)
I gave a talk at the decision summit describing how artificial intelligence can disrupt operations research using some of the recent tools I developed.
Haitham leads the reinforcement learning team at Huawei technologies Research & Development UK. Prior to Huawei, Haitham led the reinforcement learning and tuneable AI team at PROWLER.io, where he contributed numerously to their technology in finance and logistics. He was one of the main contributors to large improvements in last-mile delivery.
Prior to joining PROWLER.io, Haitham was an Assistant Professor in the Computer Science Department at the American University of Beirut (AUB). Before joining the AUB, Haitham was a postdoctoral research associate in the Department of Operational Research and Financial Engineering (ORFE) at Princeton University. Prior to Princeton, Haitham conducted researcher in lifelong machine learning while being employed as a postdoctoral researcher at the University of Pennsylvania. Being a former member of the General Robotics Automation Sensing and Perception (GRASP) lab, he also contributed to the application of machine learning to robotics.
Haitham acquired his Ph.D. in Artificial Intelligence (AI) at Maastricht University in the Netherlands. He shortened a four-year study in two after publishing over 30 articles in world-leading AI and machine learning conferences and journals. He attained his Masters in Mechatronics Engineering with a summa cum-laude from the University of Applied Sciences in Ravensburg-Weingarten in Germany. Being the basis for his Master studies, Haitham acquired his Bachelors in Mechatronics Engineering from the Harriri Canadian University in Lebanon.
His primary research interests lie in the field of statistical machine learning and artificial intelligence, focusing on lifelong learning, multitask learning, knowledge transfer, and reinforcement learning. He is also interested in learning using massive amounts of data over extended time horizons - a property common to "Big-Data" problems. His research also spans different areas of control theory and nonlinear dynamical systems, as well as social networks and distributed optimization.