Mia Minnes

 

 


 

Mia Minnes is a mathematician and computer scientist. She is an Assistant Teaching Professor (LPSOE) in the Computer Science and Engineering Department at the University of California, San Diego. She researches the theory of computation, mathematical logic, and algorithmic randomness, and she develops curricula and university programs on algorithms, problem solving, the overlap of math and computer science, and writing in the discipline. Her work has been supported by several grants from the National Science Foundation. Dr. Minnes earned her PhD in Mathematics at Cornell University in 2008, co-advised by Anil Nerode and Bakhadyr Khoussainov. Previously, she earned Master's degrees in Computer Science (2006) and Mathematics (2006) from Cornell and Bachelor's degrees in Mathematics and Engineering (2003) and Philosophy (2003) from Queen's University. Her postdoctoral work was at MIT (Massachusetts Institute of Technology, 2008-2010) and UC San Diego (2010-2013). She has taught many different courses in mathematics and computer science, ranging from large-lecture introductory freshman courses to senior undergraduate and graduate seminars. She was awarded the Best Teacher award 2013-2014 in CSE in the Jacobs School of Engineering at UC San Diego.




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Dec 12th 2016

How does Google Maps plan the best route for getting around town given current traffic conditions? How does an internet router forward packets of network traffic to minimize delay? How does an aid group allocate resources to its affiliated local partners? To solve such problems, we first represent the key pieces of data in a complex data structure. In this course, you’ll learn about data structures, like graphs, that are fundamental for working with structured real world data.

Average: 6.3 (12 votes)
Dec 12th 2016

How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? In this course, you will use and analyze data structures that are used in industry-level applications, such as linked lists, trees, and hashtables.

Average: 6.3 (4 votes)
Dec 12th 2016

Welcome to our course on Object Oriented Programming in Java using data visualization. People come to this course with many different goals -- and we are really excited to work with all of you! Some of you want to be professional software developers, others want to improve your programming skills to implement that cool personal project that you’ve been thinking about, while others of you might not yet know why you’re here and are trying to figure out what this course is all about.

Average: 6 (9 votes)
Dec 12th 2016

You’ve hit a major milestone as a computer scientist and are becoming a capable programmer. You now know how to solve problems, write algorithms, and analyze solutions; and you have a wealth of tools (like data structures) at your disposal. You may now be ready for an internship or (possibly) an entry-level software engineering job. But can you land the internship/job? It depends in part on how well you can solve new technical problems and communicate during interviews. How can you get better at this? Practice!

Average: 7.2 (5 votes)