Mentoring

If you’re a student seeking research experience in a computational lab, I occasionally mentor students on research projects in the Philadelphia area. Typically I mentor students on projects in the fields of:

Whether it’s a blog post or a research paper, I expect to produce some sort of tangible result with my students by the end of the mentorship program, and the projects we work on together will reflect that expectation.

If you would like to schedule an interview, please send me an email. Note that I no longer mentor students remotely; we must be able to meet in-person on a regular basis.

Current research assistants

None

Previous research assistants

Sahil Shah

Nichole Rigby was a Biology Masters student at Temple University. Over Fall 2016, we gathered several datasets from Kaggle and evaluated TPOT on over a dozen real-world data science problems. Nichole has since graduated and is now a full-time Data Scientist at a local Philadelphia company.


Sahil Shah

Sahil Shah is a Computer Science major at the University of Pennsylvania. Over Fall 2016, we continued the development of an award-winning automated machine learning framework called TPOT, which automates the process of designing and optimizing machine learning pipelines.


Daniel Angell

Daniel Angell is a Computer Science major at Drexel University. Over Summer 2016, we continued the development of an award-winning automated machine learning framework called TPOT, which automates the process of designing and optimizing machine learning pipelines.


Tuan Nguyen

Tuan Nguyen is pursuing a double major in Mathematics and Computer Science at Swarthmore College. Over Summer 2016, we developed a Python version of the Multifactor Dimensionality Reduction (MDR) feature construction algorithm and integrated it into our automated machine learning framework, TPOT.


Rolando Garcia

Rolando Garcia is a Computer Science major at Arizona State University. Over Summer 2016, we developed a Python tool called DELFT that automates the process of designing artificial neural network architectures for deep learning.


Akshay Varik

Akshay Varik is a Mechanical Engineering and Applied Mechanics Masters student at the University of Pennsylvania. We collaborated on a massive benchmark of the scikit-learn machine learning library in Python, and aided the scikit-learn developers in choosing more reasonable default parameters for their model implementations.


Zairah Mustahsan

Zairah Mustahsan is an Embedded Systems Masters student at the University of Pennsylvania. We collaborated on a massive benchmark of the scikit-learn machine learning library in Python, and aided the scikit-learn developers in choosing more reasonable default parameters for their model implementations.


Patrick Haley

Patrick Haley is a Computer Science undergraduate student from the University of Texas at Austin. In 2015, we published our third publication resulting from our research on the many-eyes theory and its effect on the evolution of animal grouping behavior. Patrick has since moved on to bigger and better things, such as interning at the German Aerospace Center in Germany and being named a finalist for the Rhodes Scholarship.


Robert Bato

Robert Bato is a Computational Mathematics undergraduate student at Michigan State University. Over Fall ’14 and Spring ’15, we collaborated on several data analysis projects (e.g., [1] [2] [3]) while Rob refined his data science skills in Python.


Erik Miller-Galow

Erik Miller-Galow was a Mathematics undergraduate student at Michigan State University. Over Fall ’14 and Spring ’15, we developed a new method for applying evolutionary computation to MNIST hand-written digit classification. Erik has since graduated and is now working as a Software Engineer at Applied Dynamics International.


Zoë Beckett

Zoë Beckett was an Economics undergraduate student at Oberlin College. In Summer ’14, she visited our lab to work with Tracey Jabbour on an applied Markov Brain project. In this project, we evolved Markov Brains to learn and detect what factors have the largest impact on consumer decision making when it comes to purchasing American-made cars. Zoë has since graduated and is now working as an Underwriter at United Shore.


Tracey Jabbour

Tracey Jabbour was a Mathematics undergraduate student at Michigan State University. In Summer ’14, she joined the lab to work with Zoë Beckett on an applied Markov Brain project. In this project, we evolved Markov Brains to learn and detect what factors have the largest impact on consumer decision making when it comes to purchasing American-made cars. Tracey has since graduated and is now a Financial Analyst at General Motors.


Michael Bauer

Michael Bauer was a high school student from Okemos High. In Summer ’13, we followed up on a previously published Avida study looking at the long-term stability of evolved ecosystems. In this follow-up study, we used Avida to produce a high-resolution view of how rapidly evolving digital ecosystems change over time.