Carnegie Mellon University

Machine Learning PhD Graduate 2018 Highlight of the Week – Benjamin Cowley

May 25, 2018

Machine Learning PhD Graduate 2018 Highlight of the Week – Benjamin Cowley

Byron Spice
  • Director of Media Relations
  • 412-268-9068

To celebrate our PhD Graduates for 2018, we are releasing a series of articles that will be published in the upcoming weeks, highlighting each one of our Machine Learning graduates, follow #MLCMUGrads18 in social media or follow our RSS feed to stay updated with new articles as they come along.

Benjamin Cowley recently graduated with a PhD in Machine Learning, after successfully defending his thesis: "Neural Population Activity in the Visual Cortex: Statistical Methods and Application" - Ben's research focuses in the field of computational neuroscience, where he develops and applies machine learning techniques to understand the brain in all senses. He analyzes high-dimensional neuronal population activity, and develops dimensionality reduction methods to aid in such analysis. He also develops adaptive stimulus selection methods to elicit large and varied neural responses in order to study how neural variability affects the fidelity of stimulus information. Ben is also affiliated with the Center for Neural Basis Cognition in Pittsburgh, PA.


How do you think that Carnegie Mellon University has prepared you for the future?

Considering I was both an undergraduate and a PhD student at CMU, the university has given me technical expertise, while challenging me to flex that expertise to answer tough scientific questions.  I'm a firm believer that impassioned, hard work will win out over smarts every time. When I saw Carnegie Mellon's motto was "My heart is in the work." - I knew we would be a perfect match. CMU gave me many challenging, interesting problems to solve, and showed me how to efficiently and creatively solve them.

What is your favorite quote?

"Think cortically, act neuronally."

What is your main takeaway from your trajectory here at CMU?

You don't learn when it works right the first time. You learn when it repeatedly fails and you keep asking why.

What are you planning to do now that you have graduated?

Literally the next day after my last work day, I am going to hike half the Appalachian Trail, from Harpers Ferry, WV, to Mount Katahdin, Maine. Then, I will start a postdoc at Princeton using machine learning to gain insight into the underlying computations of the brain.

Do you have any advice for current PhD students in our department?

Do not compare your achievements with those of others, and always ask for help. Welcome and receive as much critical feedback as possible. Try to have 2-3 projects to work on, so when you get stuck on one, you can think about it while working on the others. Also, finishing a project is not the end goal---sometimes the collaborations, friendships, and new ideas that come out of a project are much more worthwhile. And finally: the pomodoro technique!

We are incredibly proud of Ben for being a recent graduate from the Machine Learning Department at Carnegie Mellon University, and all his achivements and contributions to Machine Learning. Remember to stay tuned to #MLCMUGrads18 in social media or follow our RSS feed to stay updated with new highlights as they come along.