# Prospective Students

Prospective student information from Dr. Dligach:

Prospective student information from Dr. Albert:

Minimal requirements for interested students:

• One-year programming experience (Python or Java preferred) - this is an absolute minimum, no exceptions.
• Statistics or machine learning experience
• GPA > 3.3
• Writing ability: all projects efforts are documented. Your writing ability will be assessed
• Test-driven development and version control are encouraged

Prospective students outside of Chicago:

Late program Loyola students (late Junior, Senior undergrad, 2nd year MS):

We have a computer science summer research program that you are encouraged to participate in. Your experience there is greatly appreciated, and the program is set up so that your participation can comfortably be done in a limited time frame. However, outside of that summer program, if you are within one year of graduation, the options for participating in the lab are limited as it takes approximately a half a year of intense effort to be prepared for contribution to lab goals.

Early program Loyola students (Freshman, Sophomore, 1st year MS, also external Ph.D. students):

You are strongly encouraged to contact our lab if you are interested. Please include a current CV or resume if you are serious about working with us (you should have one anyway). Depending on your experience, you may or may not be able to immediately join a project, however, an early interest or long-term commitment is very valuable as training is necessary to be productive in the lab.

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Sample technical questions from PAC-lab fellowship interviews in 2016 (note, you are not expected to know the exact answers, though the approach students had to these questions said a lot about how they did in the group):

1. Write pseudocode for printing the Fibonacci sequence (explained if students didn't know what it was):
2. You want to design a system to classify images of city scenes from rural scenes: explain how you would do that. What data would you collect? What features? How would you test it?
3. Estimate the probability that in a room of 23 people, two people will share the same birthday.
4. Give the most formal definition of â€śstatistically significantâ€ť that you can. Include P values if possible.
5. Someone designs a visual terrorist recognition system for use in airports. They claim to be able to identify known terrorist with 99% accuracy. How might this number be misleading, and how would you provide a score that is more appropriate?