Marc Rubin

How did you discover Western?

I always wanted to teach and do research at a small, liberal arts college in a mountain setting. Western was on my radar ever since being an undergraduate at Colorado College.

What are some of the highlights of your career?

My undergraduate degree was in Psychology and I worked in a neuro-imaging laboratory for a year. It turned out I was more interested in learning how the MRI machine worked than understanding how the brain functioned. For my Master’s degree, my thesis involved training artificial neural networks to classify various musical instrument (e.g., violin vs. viola).

During my Ph.D. at Mines, I was an NSF IGERT Fellow and worked on an interdisciplinary research group called SmartGeo. I was able to collaborate with geophysicists, geotech engineers, mechanical engineers, and geologists on some very interesting multidisciplinary problems like non-invasive earth-dam monitoring.

My research involves using computing technologies to aid with avalanche forecasting. In 2012, I spent the summer in Davos, Switzerland to help engineer a wireless seismic sensor system to detect snow avalanches. I’ve also conducted applied machine learning (ML) research to use algorithms to detect avalanches in seismic data. My current research involves using ML algorithms to differentiate snow grains and to help engineer a “smart probe” that can probe the snowpack and detect weaknesses.

What most excites you about your field?

Computer Science is present in almost every industry; it’s hard to name an industry that doesn’t use computation in some way, shape, or form. I particularly enjoy applying computer science algorithms and technologies to help others solve challenging problems. Also, computer science is an ever-changing field; there’s always something new to learn.

What is your favorite thing about the Gunnison Valley?

There are almost too many things to count. I love how friendly all the locals are; everyone is very respectful and helpful to each other. Gunnison feels like a tight-knit and cheerful community. I also like the endless options for outdoor recreation at our doorstep. There is a lot to explore within just an hour’s drive (or less). Mountain biking, hiking, skiing, paddle boarding, climbing, camping, you name it. It’s a great place to work and play. It definitely gets cold here in the winter, but as Prince once said: “I like the cold weather, it keeps the bad people away.”

Courses Taught

• CS 190: Introduction to Computer Science I
• CS 250: Web Application Development I
• CS 303: Machine Learning
• CS 310: Programming Projects in C++
• CS 310: Programming Projects in Kotlin
• CS 350: Web Application Development II
• CS 370: Systems Programming
• CS 380: Internet of Things
• CS 412: Software Engineering I
• CS 435: Mobile Application Development
• CS 470: Algorithms
• CS 495: Capstone
• HWTR 100: Let’s Get Physical (Computing)

Publications and Research Interests

My research involves using computing technologies to aid with avalanche forecasting. In 2012, I spent the summer in Davos, Switzerland to help engineer a wireless seismic sensor system to detect snow avalanches. I’ve also conducted applied machine learning (ML) research to use algorithms to detect avalanches in seismic data. My current research involves using ML algorithms to differentiate snow grains and to help engineer a “smart probe” that can probe the snowpack and detect weaknesses.

1. Rubin, M. Wakin, and T. Camp, “Lossy Compression for Wireless Seismic Data Acquisition”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17 pages, 2016.
2. Camp, M. Rubin, and S. Gonzalez, “Challenges in Developing Intelligent Geosystems (and the pros/cons of interdisciplinary research)”, IEEE International Conference on Computing, Networking and Communications (ICNC), 7 pages, 2015.
3. Rubin and D. Haire, “An Update Regarding AvySenseNet: A Prototype Wireless Sensor Network Funded by the American Avalanche Association Graduate Student Research Grant,” The Avalanche Review, 2 pages, 2014.
4. Rubin, “The Effectiveness of Live-Coding to Teach Introductory Programming,” ACM Special Interest Group on Computer Science Education (SIGCSE), 6 pages, 2013. Acceptance Rate: 37.8%
5. Rubin, T. Camp, A. Herwijnen, and J. Schweizer, “Automatically Detecting Avalanche Events in Passive Seismic Data,” IEEE International Conference on Machine Learning and Applications (ICMLA), 8 pages, 2012. Acceptance Rate: 37%
6. M. Rubin and T. Camp, “SkinTrack: A Wireless Embedded System to Monitor Lift-Served Backcountry Access Gates,” The Avalanche Review, 2 pages, 2011.