Student and Faculty Work
Students and faculty in the computer science department are very active in research. There are numerous student-faculty research projects, independent projects, and group projects.
Students present their work at different research forums, both on-campus and off-campus, and there are several faculty research projects with active student participation.
Professor Andrews works in the areas of visual analytics and computational art. Recent work has focused on supporting the development of bespoke analytic tools. This culminated in the development of MiddGuard, a flexible web framework that serves as scaffolding for the development of highly interactive collaborative visual analytics tools. Primarily developed by Dana Silver ‘17, the framework has been used to compete in several analytic contests at the VAST conference, winning an award for “Integrated Analytic Environment”. He has also been working with students on bridging the gap between computer science and the arts through explorations of generative and evolutionary artwork.
Professor Basu is interested in programming languages as a way to interact with computing systems, and as a medium for human thought and expression. His current work explores the legal applications and implications of computing technologies. He is looking at how software systems can express and enforce legal restrictions and intent, and conversely, how those restrictions affect software development and deployment. HIs previous work has applied techniques and tools from programming languages to software-defined and optical networks.
Professor Briggs works on expanding access to computer science education in K-12. She is one of the creators of the AP Computer Science Principles Course as co-PI on the National Science Foundation award to the College Board on broadening participation in computing. She has worked collaboratively with students in organizing outreach efforts with middle school and high school girls. She supported the creation of the WiCS++ group and continues to serve as one of the faculty advisers.
Professor Chodrow works on mathematical and computational tools for understanding our increasingly complex world. He is especially interested in network science, the study of interconnected systems in society and nature. Much of his work involves the development and analysis of algorithms for learning from network data. In pursuing this work, he draws freely on methods from applied mathematics, machine learning, statistics, and physics. Other work focuses on the development, simulation, and analysis of theoretical models of human and animal societies. Professor Chodrow also enjoys applied data science. Several of his data science projects study questions related to sustainability, equity, and social justice.
Ananya Das (Christman)
Professor Das’s research is in algorithm design and analysis, with a focus on graphs, scheduling, and vehicle routing problems. She is interested in developing online, approximation, and randomized algorithms, and testing these algorithms on real-world data. She is also interested in modeling and simulating stochastic networks for routing and traveling problems.
In recent years, Professor Dickerson has turned his attention from traditional problems in computational geometry and geo-spatial computing to the growing field of agent-based modeling, also known as multi-agent simulation—a field closely related to what biologists refer to as individual-based ecology and social scientists refer to as complex adaptive systems. He has worked with students on computer modeling/simulation projects related to forest succession and competition of big-leaf mahogany in the Amazon, population dynamics of transient killer whales in southeast Alaska, and the impact of invasive trout on stream ecology and forest-stream dynamics. His interest in computer modeling in ecology has also corresponded with work outside of computer science as a narrative non-fiction nature and environmental writer.
Professor Johnson works in the area of systems and network security. Under his guidance, Kit Tse ‘16.5 produced a framework for verifying protocol sessions, including a proof of concept for TCP, the protocol that undergirds the entire Internet. She presented this work at the Fourth Workshop on Language-Theoretic Security in May 2017.
Professor Kimmel designs algorithms for quantum computers, and tries to prove that these algorithms are faster than their classical counterparts. Recent students have worked on designing algorithms for graph problems like cycle detection, and analyzing the average runtime of quantum algorithms that run faster on not-worst-case inputs.
Professor Linderman’s research interests include heterogeneous computing (GPGPU), genome analysis and genomics education for the public, patients and providers. He is the PI of a NIH-funded project to create a genomics knowledge measure and is pursuing several genome analysis projects with Middlebury students. Current projects include: DECA, a software package for CNV calling that began as a senior thesis project; MySeq, a web application for exploring your own whole genome sequencing data; and a novel method for identifying disease causing mutations using simulation.
Professor Scharstein is known in the computer vision community for the “Middlebury Benchmarks,” a collection of datasets and online leaderboards that were developed in collaboration with student research assistants over the last 20 years. Researchers around the world use these benchmarks to test their stereo vision and 3D reconstruction methods. Professor Scharstein also works on novel algorithms for stereo vision. A collaboration with Dylan Quenneville ‘18 resulted in a paper “Mondrian Stereo,” which Dylan presented at the International Conference for Image Processing (ICIP) in China in September 2017.
Professor Vaccari’s research interests include image and signal processing with emphasis on remote sensing and biomedical/biological images, model-based data mining for large spatiotemporal datasets, and graph signal processing as well as novel approaches in experiential undergraduate and graduate education.