Aditya Paul





Aditya Paul

PhD Candidate


International Student from India


Supervisors:  Assoc Prof David Rey,  Prof. S. Travis Waller


Areas of Interest:

  • Applications of Machine Learning in Optimization
  • Game Theory in Logistics and Supply Chain
  • Same-Day Delivery in E-Commerce 

I became interested in mathematical optimization and programming through a course on operations research in my undergraduate years. Successfully completing a research internship practicum at UNSW during my undergraduate career was an exciting journey. I realized that research was the right option for me.

Optimization as a practice is vital in today’s world because we do not need revolutionary solution concepts for many problems, we just need to utilize our existing resources better. Otherwise we would leave much of our society’s potential untapped. My focus is on resource allocation, particularly in on-line environments where data becomes available in real-time, and decisions have to be made on the go. In such cases machine learning techniques like reinforcement learning have proven useful as an accompaniment to conventional optimization methods. Using an AI approach to solve optimization problems, if successful, provides valuable insight into the best performance strategies in real time scenarios, which are becoming increasingly common day by day. 

In my free time I like to play chess and the guitar. They help remind me that ultimately meaningful progress takes time and little improvements each day can quickly compound over time to give good results.

The best piece of advice I have ever been given is that good things take time, and things that come quickly often go away quickly as well. There is no shortcut to the best and most important things in life.

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