I am an assistant professor of computer science at An Najah National University. I have a Ph.D. in Computer Science from University Autonoma De Barcelona. My Ph.D. research was on data assimilation of wildfire simulators. We used meta-heuristic and evolutionary algorithms, the same techniques used in Artificial Intelligence (AI) and Machine Learning (ML). Simulators, in general, are based on assumptions and parameters that are hard or impossible to measure accurately in real life. Wildfire simulators depend on wind speed and direction that is extremely hard to predict and is highly variable. The vegetation (fuel) conditions and characteristics are another important input to the simulator that affects its accuracy and is difficult to collect at sufficient resolution. The conclusion of our work was that a simulator can adapt and learn from data.

After I returned to Palestine, I started working on developing traffic simulators to make them “smart” and learn from the data. This makes the simulators better adapt to specific traffic conditions. Later, we extended our work to make cities smarter and make the traffic system intelligent by adapting themselves to the traffic volume. By changing traffic light schedules we are able to improve traffic flow. We now are working to introduce sensor systems to traffic lights to implement our findings in the real world. This work can be classified as reinforcement learning to make traffic lights self-adaptive in real-time.

In the past few years I started to use genetic algorithms to synthesize reversible circuits. Reversible circuits are necessary in the development of quantum computers. Recently, I started implementing genetic algorithms and meta-heuristic optimization techniques for optimal positioning of water sensors for precision agriculture.