Faculty Research Opportunities
CIS 693, 690/695 Faculty Research Interests
If you are looking for ideas for a Master's project or thesis, this page describes the current problems and areas that faculty are looking for students to help. If any of these ideas interest you, please feel free to reach out to the faculty and ask them about it several weeks before the semester you are planning to take CIS 693 or 690.
Robert Adams - I have two broad research interests: procedural content general for video games, and digital humanities (solving problems outside of computing). Specific areas currently include (1) generating levels for games that have a specific difficulty; (2) player modeling and adaptation, allowing for the generation of content that is tailored to the individual player; (3) automatically determining guitar chords for music.
Denton Bobeldyk - I'm looking for graduate students with excellent communication skills that are interested in projects involving computer vision and machine learning.
Yuan Cheng - I'd love to have one or more graduate students help me with the following research areas:
- A forensic analysis of private browsing mode: We'll delve into the mechanics of private browsing to understand what it truly offers.
- An empirical study of a Duo usage dataset on a campus: Let's explore how a university campus community uses Duo security and identify potential improvements on usability.
- An empirical study of user perception on security questions: We'll investigate how users perceive security questions and their effectiveness in keeping accounts safe.
- An empirical study of user perception on CAPTCHAs: We will uncover what users think about CAPTCHAs and how they impact the online experience.
- Feature selection and benchmarking for large-scale IoT attack datasets: Help me and Dr. Boit develop a novel solution to protect IoT devices by selecting the right features and building a benchmark for existing and future IoT datasets."
Zach DeBruine - Students in my lab train high-performance AI models for insights into genomics. I'm always looking for students who are comfortable in Python, R, or C++, and have linear algebra and/or introductory biology knowledge.
Erik Fredericks - I am currently working on search-based software engineering, focusing on search problems within run-time testing, test oracles, and requirements engineering. I am working in applying those to robotics to reduce uncertainty, as well as to applying evolutionary computation for creating interesting generative art and extending the capabilities of procedural content generation in video games. It would be great to have a graduate student that is interested in developing additional capabilities in one of these areas!
Kamrul Hasan - I am looking forward to working with some graduate students on following topics:
- Data Science for Precision Farming: In this project, we want to take advantage of the latest data science techniques and develop tools for farmers aiming to reduce their cost, improve throughput, and leave less (negative) environmental impacts. Looking for students wanting to contribute to promoting a sustainable environment.
- Distributed Semi Supervised Learning: In this research, we are developing new machine learning models that can learn both from labeled and unlabeled data. We want to extend the learning mechanics to be working in a distributed fashion pursuing a common and coordinated objective. Looking for curious students wanting to explore beyond traditional machine learning approaches.
- Music composer software agents: We will build an AI baked music composer agent (software) using the latest Generative AI tools and techniques. Music composition data is complex, and we are looking for students with backgrounds in music and computing.
Zachary Kurmas - I am a math nerd at heart who also happens to enjoy programming. I like writing code that explores mathematical structures (such as boolean circuits/functions, or the instances of an NP-Complete problem). I especially enjoy writing software that makes life easier for either professors or students. For example, I have written tools to automate the testing of assembly language and digital logic circuits. Finally, I have not done work in this area for a long time, but I find also operating systems and computer architecture interesting (for example exploring branch prediction algorithms, cache replacement policies, etc.)."
Alexander Lalejini - My research intersects computer science and evolution, applying the principles of each field to advance the other. Broadly, my work focuses on (1) developing digital systems to investigate fundamental questions about how evolution works, (2) harnessing our understanding of evolution to engineer new algorithms to solve computational problems, and (3) facilitating knowledge transfer between the fields of evolutionary biology and evolutionary computing.
Dimitrios Melissourgos - I'm currently working on two areas in computing: 1) network traffic measurement and 2) machine learning and AI. Network traffic measurement aims to collect important information about packets that pass through networking devices, such as routers and switches. My focus on AI is security and privacy, but I like to study all aspects of it.
Rahat Ibn Rafiq - I'd love to have a graduate student help me build interactive systems leveraging natural language processing and machine learning to solve real world problems.
Sara Sutton - I am looking for a graduate student to research and work on Machine Learning and Cybersecurity issues related to Cloud Computing and the Internet of Things.
Christian Trefftz - Learning about Julia, a new programming language for parallel processing, and the packages that have been written for it. I am interested in applications in Computational Geometry, in particular the Voronoi Diagram.
Guenter Tusch - I'm looking for a graduate or undergraduate student who can help with: 1. research on a usability or value-based care project in practice EHRs; 2. research on how quality initiatives like Lean or Six Sigma can improve patient outcomes; or 3. how NLP can be used in bioinformatics to analyze scientific articles.