Employee Spotlight: Brian Cheung
Tell us about yourself and how long you’ve been with Optimal Dynamics.
My name is Brian and I am based out of NJ. I have been a part of the Analytics team at Optimal Dynamics for about four and a half years. Prior to that, I was a graduate student at the Operations Research and Financial Engineering Department at Princeton University.
Can you briefly summarize your job?
I work primarily on designing and implementing algorithms around/for our core optimization engine. This largely falls into the following two buckets: 1) behind-the-scenes work (sometimes experimental) that allows our engine to run more efficiently, and 2) customer feature requests.
What inspired you the most to join Optimal Dynamics?
I received an invitation to join from Warren Powell out of the blue and it seemed a rather exciting project to be part of (and it still is!). I had spent a summer benchmarking the solution quality of our core optimization engine a couple years prior to my time at Optimal Dynamics, so I was familiar with our technology and knew how powerful it was first hand.
What do you like best about our company culture?
I love how everyone is highly collaborative and that our projects move at a very fast pace.
What is unique about what we do at Optimal Dynamics?
Our product brings together advanced decision science and automation to handle complex, real-time logistics decisions — areas where most tools today still rely on manual rules or heuristics.
What is your favorite part of your job?
I enjoy designing solutions and seeing them implemented in the real world.
How does your work impact our product, and, therefore, the industry?
My work allows us to continually refine our solution quality and supports our ever-growing set of modeling capabilities, which not only translates to better decisions, but also enables our product to handle more real-world complexity and adapt to diverse customer needs.
What have been your biggest accomplishments on our team, and what was the impact on the company?
A more recent one would be Home Time Value Function Approximations (VFAs) to address customer feedback and driver preferences. Deployed about a year ago, this piece of logic allows us to factor in home time information while retaining our ability to approximate future/downstream values of drivers.
How have you grown professionally while on our team?
Being part of the company early on has allowed me to participate directly in functions such as running Proof-Of-Value exercises for prospective customers and calibrating for deployments, for which we now have dedicated teams. This experience has helped me better understand some of the gaps between theory and practice, enabling me to design more practical and implementation-ready solutions.
What do you like to do in your free time?
I am an avid field hockey player, and like to stay active through running, cycling, and weight training when the sport is not in season.
Can you share a hidden talent no one knows about you?
This is yet to be discovered!
What’s the best advice you can give to someone who wants to work at Optimal Dynamics?
Be curious and flexible, and do not mind figuring things out as you go.
