Category: Student Research

Posted on

2026 Summer Research Scholars

The Summer Research Scholars (SRS) program provides support for students engaged in collaborative research under the guidance of W&L faculty. It is designed to foster the development of discipline-specific research skills, encourage active knowledge acquisition, and spark student interest in scholarly inquiry.

Here are the 2026 Computer Science SRS students, along with their faculty mentors and summaries of their research:

Professor Sana Habib:

This summer, Professor Habib had three SRS students: Saad Ahmed Khan Ghori ’27, Slsabil (Zazo) Hassan ’28 and Taeyun Kim ’29.

Research Synopsis:
This summer’s research projects explore critical challenges in cybersecurity, privacy, and trustworthy computing—from securing future 5G/6G network architectures and protecting user privacy in cloud-native systems to developing hands-on educational tools for teaching secure software development. Together, these projects contribute to creating more secure, resilient, and privacy-conscious digital technologies.

Saad Ahmed Khan Ghori ‘27

Saad has been working on Metadata Leakage in 5G-Based Service Architectures: A Cloud-Native Measurement and Analysis. His research examines how metadata generated within cloud-native 5G networks may inadvertently reveal sensitive information. By measuring and analyzing these potential information leaks, the project seeks to better understand privacy risks in modern telecommunications infrastructure and identify opportunities to strengthen user privacy.

Slsabil (Zazo) Hassan ‘28

Slsabil has been developing the Security & Privacy Dojo, an interactive educational platform that teaches secure programming through hands-on exercises based on core data structures. By identifying and fixing realistic vulnerabilities in code, students gain practical experience with secure software development while learning the security and privacy challenges that can arise from incorrect implementations.

Taeyun Kim ‘29

Taeyun has been conducting research on Border Gateway Protocol (BGP) at the Service Layer: Trust Graph Analysis for Federated FutureG Networks. The project explores trust relationships in next-generation mobile networks, investigating how service providers can securely communicate and collaborate in future federated 5G and 6G environments. The research aims to identify potential trust vulnerabilities and contribute to the design of more secure and resilient network architectures.

The students have made excellent progress on their projects so far, and it has been exciting to see their ideas develop over the course of the summer.

Professor Sara Sprenkle:

This summer, Professor Sprenkle mentored three SRS students: Alan Liu ’28, Takunda Mawere ’28 and Danilo Sindric ’29. These students worked on The Ancient Graffiti Project (AGP) which is a digital scholarly resource for searching, studying and analyzing ancient Roman inscriptions.

Alan Liu ‘28

Alan’s research investigates how to accurately and efficiently represent the archeological sites of Pompeii and Herculaneum on a digital map that grants access to 3500+ different types of graffiti. He worked on developing more features for AGP’s mapping such as seamless canvas rendering, permanent labels, map aesthetics, and numerous bug fixes and simplification of the development code. Effectively, the maps received a complete overhaul that significantly boosts the productivity of the user skimming through dozens of graffiti.

Takunda Mawere ’28

Takunda’s research project involves developing new features to continue improving the AGP website. His work this summer was mainly focused on improving the search functionality. He upgraded the system from Elasticsearch 7 to Elasticsearch 8/9 API. Takunda also leveraged the new API to improve the pipeline for searching and sorting results.

Danilo Sindric ‘29

Danilo’s research this summer began with improving the filtering system on the main AGP website. He then transitioned to the VESTA project, where he worked on a variety of development tasks. Danilo’s primary contributions included building an evaluation tool that enables comparisons with similar digital humanities projects, as well as developing several analysis tools.

Posted on

Computer Science Majors Publish Research on Video Game Behavior

Computer Science students Trey Custodio ’26 and Sanjog Basnet ’27 co-authored a paper with CS Professor Liz Matthews titled “Exploring User Demographics for Research on Video Games,”. Their work used a survey to study gaming preferences and identify patterns in player behavior, helping improve how researchers classify gamers.

Custodio (CS major; Creative Writing and German minor) and Basnet (double major in Cognitive and Behavioral Science and Computer Science; Japanese minor) conducted the research as Summer Scholars in 2025.

The research will be presented at the Gaming and Technology Conference, held July 25–27 in Valencia, Spain.

Congratulations to Trey and Sanjog on this exciting accomplishment!

You can read the full Columns article here: https://columns.wlu.edu/wl-students-accepted-for-publication-at-the-gaming-and-technology-conference/

Posted on

2026 Game Demo Day Showcases Student‑Built Games

On Saturday, April 11, the Great Hall hosted Game Demo Day, an exciting display of student innovation and design.

Students from Professor Liz Matthews’ Computer Science 319: Video Game Design course presented their final game projects, the culmination of a semester of hard work, problem‑solving, and imagination. 

Visitors were invited to do more than just watch—they were encouraged to play the games themselves, interact with the student developers, and learn about the design process behind each project. The event provided an interactive environment for students to present their work to the campus community.

Game Demo Day 2026 was a fun and successful celebration of student creativity and game design.

Posted on

Janeet Bajracharya ’26 Presents Honors Thesis on Learning‑Augmented Auctions


On Friday, April 10, Janeet Bajracharya ’26, a Computer Science and Mathematics major, presented his Honors Thesis, An Empirical Evaluation of Learning‑Augmented Combinatorial Auction Algorithms.  Janeet explored how machine learning can improve complex auctions used in areas like wireless spectrum sales and online advertising, sharing results that show how learning‑augmented algorithms can make these systems faster and more effective. The thesis was completed under the supervision of Professor Kefu Lu.

Congratulations to Janeet on an excellent Honors Thesis presentation and this impressive research achievement!

Posted on

Joe Holden ’26 Presents His Honors Thesis On Faster Computing and Financial Risk

On Thursday, April 9, Joe Holden ’26, an Accounting and Computer Science major, presented his Honors Thesis, Faster Risk Estimation for Bond Portfolios through Accelerated Computing. He explored how newer computing technologies can help financial institutions assess bond risk more quickly and efficiently. Using a common bond as a case study, Joe compared different hardware platforms and showed that specialized, accelerated systems can deliver faster results—underscoring their increasing role in modern financial analysis. The thesis was completed under the supervision of Professor Simon Levy.

Congratulations to Joe on an excellent Honors Thesis presentation and meaningful research at the intersection of computing and finance.

Posted on

Computer Science’s Gabriel Hogan Contributes to Research Presented at FOCI 2026

Gabriel Hogan ’26, a computer science and business administration major, co-authored a research paper with former Visiting Assistant Professor William Tolley (now an assistant professor at Hampden-Sydney College) at FOCI 2026 (Free and Open Communication on the Internet). Gabe was instrumental in collecting data and testing iOS devices—key components of the team’s broader exploration into internet freedom and communication technologies.

FOCI is recognized as a well‑respected workshop for cutting‑edge research in Internet Freedom, making Gabe’s involvement an impressive achievement and a clear reflection of his dedication and curiosity.

Well done, Gabe!

Posted on

Micah Tongen ’26 Publishes Research on AI-Powered Search for Ancient Graffiti

Washington and Lee University computer science major, Micah Tongen ’26, has published a cutting edge research article exploring how artificial intelligence can be used to search ancient Greek and Roman texts. His piece, titled “Semantic Search for Ancient Inscriptions,” appears in the Anthology of Computers and the Humanities.

Working with Professors Sara Sprenkle and Rebecca Benefiel, Tongen built a semantic search system that helps scholars find meaningful connections in Latin and Greek graffiti using AI to find similar themes, even when the words are different. The system turns epigraphs from the Ancient Graffiti Project into numbers that represent the meaning of the words. This helps researchers spot connections they might otherwise miss and could be useful in other fields that deal with large amounts of information.

A Johnson Scholar and CS Dept. teaching assistant, Tongen hopes to pursue a Ph.D. or research-focused career in information retrieval and human‑computer interaction.

Congratulations, Micah!

Posted on

2025 Summer Research Scholars

The Summer Research Scholars (SRS) program provides support for students engaged in collaborative research under the guidance of W&L faculty. It is designed to foster the development of discipline-specific research skills, encourage active knowledge acquisition, and spark student interest in scholarly inquiry.

Below are the 2025 Computer Science SRS students, along with their faculty mentors and summaries of their research:

Professor Kefu Lu:

Professor Lu had two SRS students over the summer – Janeet Bajracharya ’26 and Slsabil Hassan ‘28

Janeet Bajracharya ’26

Slsabil Hassan ‘28

Research Synopsis:

The research topic for Professor Lu’s students was algorithm design in online scheduling. Online scheduling is the study of designing the best order for a machine to run programs (commonly referred to as jobs or tasks) in order to provide the best possible service. The online in the name refers to the fact that the algorithm does not have knowledge of which programs might arrive in the future and must adapt on the fly. Online scheduling is a well-studied topic, and it is a major area of algorithm design. Often, different algorithms are necessary depending on the goal of the schedule. Specifically, we studied a problem where the jobs that arrive to the machine can be parallelized and each have a deadline, with the goal of determining a schedule that maximizes the number of jobs completed before their deadlines elapse.

Professor Liz Matthews:

This summer, Professor Matthews mentored two SRS students—Sanjog Basnet ’27 and Trey Custodio ’26—who gathered data related to video game enjoyment.

Sanjog Basnet ‘27

Trey Custodio ‘26

Research Synopsis:

In academic research involving video game factors, such as enjoyment, frequently participants are divided into demographic groups based on their skill level, e.g. an “Expert Gamer” versus not. While these demographic distinctions are important, the metrics used for this distinction is not standardized across research and limits the demographic to a linear scale of perceived “skill”. Sanjog Basnet and Trey Custodio are working with Dr. Matthews to develop a new demographic metric to determine nonlinear gaming demographic categories to further improve other academic research. The process involves collecting a large amount of multi-variate data and then performing clustering algorithms on the responses.

Professor Sara Sprenkle:

Professor Sprenkle had 3 SRS students this summer — Elias Dakhoul, ’26, Teddy Ross ’26 and Micah Tongen’26

Elias Dakhoul, ’26

Elias’s project:

Elias’s research project investigates anomaly detection in web applications by user sessions to identify anomalous behavior based on behavioral features. Working with datasets from real-world applications, the project examines how various feature combinations impact the performance of unsupervised clustering algorithms. The sessions are characterized by 19 hand-engineered features, and two data combinations are employed: vectors (created by generating feature vectors per session) and unions (combinations of decisions from individual features).  The key goals for this summer are to dive deeper into the literature and feature selection. The primary task is to compare a manual approach (selecting high-precision features) with an automated selection method. Preliminary results and subsequent analysis indicate that automating feature selection facilitates the identification of balanced combinations, which correctly identify anomalous behavior without excessive false positives.

“KMeans_Logic_Fall2010_divided_bots1”

SessionClassificationColorGraph”

Teddy Ross ’26

Teddy’s project:

This summer, Teddy investigated the use of metaheuristic algorithms—including genetic algorithms, hill climbing, and simulated annealing—to automatically generate test cases for web applications. His approach is designed to produce cost-effective test suites that achieve high coverage with minimal length. He further analyzed the effects of various genetic algorithm selection strategies, such as tournament and roulette wheel selection as well as probabilities for various mutation operators, on the effectiveness and efficiency of test suite generation. Experimental results on diverse web applications demonstrated that these evolutionary and heuristic techniques can successfully balance coverage and suite size, offering practical strategies for optimizing web application testing.

Micah Tongen’26

Micah’s project:

Micah wrote a script that creates a search system for ancient inscriptions by converting Latin and Greek texts into numerical representations capturing meaning. The system combines traditional keyword matching with this semantic understanding and uses a large language model to re-rank results, allowing researchers to discover conceptually connected ancient texts that would be missed by conventional search methods.​​​​​​​​​​​​​​​​ Micah then wrote a paper explaining my results and submitted it to the Computational Humanities Research conference. 

Congratulations to all the 2025 SRS students on their outstanding achievements!

Posted on

Q and A with Jenna Bernstein ’25

Jenna is a computer science major and a philosophy minor and is highly interested in all things coding!

Coding, the process of assigning a code to something for classification or identification, is also known as computer programming.  It’s how we communicate with computers and tell them what to do.

Since declaring as a computer science major and discovering a real passion for technology,  Jenna has actively pursued every opportunity to engage with tech on campus.

The Computer Science Department has played a key role in her academic journey.   Jenna is deeply appreciative of the support and guidance she’s received from her CS professors.  W&L has provided Jenna with a wide range of experiences that has allowed her to learn and develop skills she might not otherwise have gained.

Click on the link to read Jenna’s Columns article.

https://columns.wlu.edu/meet-jenna-bernstein-25/

Posted on

2024 Summer Research Scholars

The Summer Research Scholars (SRS) program supports students participating in collaborative research supervised by W&L faculty. The program aims to encourage the development of research techniques within a particular discipline, to promote the active acquisition of knowledge, and to stimulate student interest in inquiry.

Here are the 2024  Computer Science SRS students,  their faculty supervisors and descriptions of their projects:

Professor Taha Khan:

Professor Khan had 2 SRS students this summer — Allison Badeaux ’28 and Nabil Youssef, ’26.   The topic for their research was  “Internet Censorship:  A Self-Destructing Prophecy”.

The internet is a crucial medium for communication, information sharing, and freedom of expression. However, internet censorship poses significant challenges to these aspects. The study explores the multifaceted impacts of censorship on users’ behaviors, attitudes, and strategies to bypass restrictions. 

Allison and Nabil’s research examined the effectiveness of censorship and its potential counterproductive effects. While censorship aims to control information flow and maintain social order, it often leads to unintended consequences like increased efforts to circumvent restrictions and the spread of alternative information channels. By analyzing user reactions, the study seeks to determine whether censorship achieves its goals or inadvertently promotes greater resistance and innovation in information dissemination.

Allison Badeaux ’28

Nabil Youssef, ’26

Professor Simon Levy:

Tiffany Guo ’26 and James Xia ’26 worked with Prof. Simon Levy on a project entitled “Neuromorphic Control for Micro Aerial Vehicles”.  Tiffany and James’s primary responsibility was developing a quadcopter simulator in Python, to aid in testing of new control algorithms.  The eventual goal is to integrate this simulator (and an actual quadcopter) with the neuromorphic control algorithms that Prof. Levy is developing as a visiting professor this summer in the TeNNLab at the University of Tennessee, Knoxville.

Tiffany Guo ’26.

James Xia ’26

Professor Liz Matthews:

Professor Matthews had 2 SRS students this summer — Han Huynh ’25 and Hamza Zia, 26.   Both Han and Hamza collected data on video game enjoyment in games containing procedural generation. This involves recruiting participants to play an infinite running game and record their responses to an enjoyment questionnaire, then using statistical analysis to determine any impact the procedural generation may or may not have on enjoyment of the video game.

Han Huynh, ’25

Hamza Zia ’26

Professor William Tolley:

Professor Tolley had two projects with a total of four students this summer.  The objectives, goals and direction for each project, along with the student research students are listed here.

Project One:  “Cryptographic Signal Integrity via Information-Theoretic Constructs” – Janeet Bajracharya (2026), Mark Holden (2025)

Janeet Bajracharya ’26

Mark Holden ’25

Objective:
This research endeavors to establish a framework for the secure dissemination of radio signals, ensuring integrity verification by external entities without disclosing the underlying raw data. The approach integrates advanced cryptographic constructs with robust signal feature extraction methodologies, employing fuzzy hashing and locality-sensitive hashing (LSH) within an error-tolerant paradigm.
Research Goal:
The principal challenge addressed is the circumvention of legal constraints on signal sharing through the application of zero-knowledge proof analogs to continuous analog signals. By leveraging wavelet transform techniques, we aim to optimally decompose and isolate salient features of the signal, minimizing the impact of stochastic noise. These features are then encoded into a cryptographic hash, facilitating secure, non-invasive verification across different instances.
Future Directions:
Ongoing research will focus on refining transformation techniques to enable the derivation of a unique signal fingerprint from its hash, advancing towards a framework where the hash itself encapsulates sufficient information-theoretic properties to characterize the original signal with high fidelity. This includes the potential to identify specific types of traffic, such as VPN traffic, thereby broadening the applicability of the methodology in network security and traffic analysis.
Project two: “Machine Learning for Censorship and Surveillance Detection in Android Applications” – Ciel Morrill (2026), Medaly Cardenas Retamozo (2025)

Ciel Morrill ’26

Medaly Cardenas Retamozo ’25

Objective:
This project aims to adapt and apply advanced machine learning techniques, originally developed by Google for identifying vulnerable code and malicious executables in Android applications, to the detection of censorship and surveillance mechanisms. Given the impracticality of reverse engineering a vast number of apps, this approach leverages machine learning to automate the identification process.
Research Goal:
The initial phase involves identifying and analyzing a set of Android apps known to contain censorship features. These apps will serve as a baseline for training machine learning models. The goal is to extrapolate from this initial dataset, enabling the model to scan and categorize thousands of other apps to detect similar censorship or surveillance-related behaviors. By refining these techniques, the project seeks to uncover hidden information control mechanisms within a broad spectrum of apps, facilitating more efficient and large-scale analysis of potentially censored content or surveillance activity.
Future Directions:
The ongoing research will focus on refining the machine learning models to enhance their accuracy and scalability. This includes integrating more sophisticated techniques, such as deep learning and natural language processing, to detect increasingly subtle and complex censorship and surveillance mechanisms. Additionally, the scope of the project may expand to include other platforms and types of digital content beyond Android apps, broadening the impact of the research on uncovering information controls across diverse digital environments.