JULY | Alex Long

July 17th, 2020

Alex is a final year Computer Science PhD student at UNSW, focusing on Sample Efficient Reinforcement Learning.

Alex Long

UNSW, Distrbuted Systems Security group | Security Data Science team

  • Tell us a bit about you.

    I am a final year Computer Science PhD at UNSW, focusing on Sample Efficient Reinforcement Learning. Before that, I simultaneously completed an M.E. (UQ, 1st hons.) and MSc. (TUM, 1st hons.) in Electrical Engineering from the Technical University Munich with a thesis on humanoid robotics that received a rarely awarded 1.0. I also administer and guest lecture for the Neural network and Introduction to AI course at UNSW.

    What is your research focus?

    The amount of data national security agencies are faced with is growing rapidly, resulting in manual analysis by both human and automated systems becoming increasingly infeasible. My research focuses on developing Reinforcement Learning based algorithms that are able to learn where to search for important information, combining the intuition of a human analyst with the scalability of an autonomous system. By knowing where to look, critical information can be identified and passed to a human analyst quicker, more robustly, and more accurately than existing methods. Ultimately, this results in national security threats being detected earlier, and a reduction in the probability of such threats ever occurring.

    What is your role in SCS?

    I am working under the supervision of Senior Software Engineer, Terry Moschou as part of the Security Data Science (SecDS) group.

    Where would you like to see your research take you?

    My goal is to found a reinforcement learning based start-up focusing on autonomous information extraction, or do applied research in industry.

  • LocationSydney, NSW