Student Projects
Recent Student Projects
Students have the opportunity and are encouraged to work with faculty members on research projects. Research interactions often stem from shared interests between students and faculty and may involve various types of engagement and expectations around the research work. Each fall semester the department faculty participate in a seminar series where they describe active research projects
Examples of recent projects that students have been involved in through formalized mechanisms are provided below; a significant number of additional opportunities exist outside of these formalized mechanisms.
Within the groupings by year, projects are separated by type, and then alphabetically by faculty member.
2024-25
These projects have been supported by the URECA Wake Forest Research Fellowship mechanism, Richter Scholars mechanism, or Computer Science Department funding.
- Parallel Structure-Preserving Tucker Decomposition with Dr. Grey Ballard
- Supervised Machine Learning for the Prediction of AML Relapse After Transplant with Dr. Natalia Khuri
- The Inherent Limitation on Interpretability of Large Language Models with Dr. Fan Yang
2023-24
These projects were undertaken by senior computer science majors invited to obtain departmental honors upon graduation.
- Adaptive Data Interface with Dr. William Turkett
- Rank-Adaptive Higher Order Orthogonal Iteration (HOOI) Of Tensors with Dr. Grey Ballard
- Investigating The Ethics Of AI And Proposing University-Wide Guidelines with Dr. William Cochran
- Communication-Avoiding Coordinate Descent for Elastic Net and Regularization Path LASSO with Dr. Aditya Devarakonda
- Indicators Of Change: Protecting Our Systems For The Future and Investigating The Temporal Aspects Of Indicators Of Change Publication with Dr. Errin Fulp
- Evolutionary Multi-Objective Coset Selection For Data-Centric AI with Dr. Natalia Khuri
- Reinforcement Learning Rubik’s Cube Solver with Dr. Paul Pauca
These projects have been supported by the URECA Wake Forest Research Fellowship mechanism, Richter Scholars mechanism, or Computer Science Department funding.
- Tensor Completion with Dr. Grey Ballard
- Investigating Turing Theory on Pathogenic Protein of Alzheimer’s Disease in Human Brain Network with Dr. Minghan Chen
- Scalable Coordinate Descent Methods for Kernel Regression and SVM with Dr. Aditya Devarakonda
- Natural Language Processing for Computational Analysis of Ancient Greek Texts with Dr. Natalia Khuri
- Android Mobile System Provenance with Dr. Michael Vanbastelaer
2022-23
These projects were undertaken by senior computer science majors invited to obtain departmental honors upon graduation.
- Weaponizing Actions in Multi-Agent Reinforcement Learning: Study on Security and Robustness with Dr. Sarra Alqahtani
- Market Research and Competitive Analysis of the Wake Forest University Computer Science Curriculum and Visual Simulation of Context Switching Utilizing an iOS Application Environment and Romper el Techo de Cristal: Breaking the Computer Science Tech Challenges Among Hispanic Students with Dr. Daniel Cañas
- Discovering Dominant Pathology Pathology in Alzheimer’s Disease using Physics-informed Neural Network with Dr. Minghan Chen
- Using Diversity to Evolve More Secure and Efficient VLANs with Dr. Errin Fulp
- Federated Learning for the Detection of Sex Differences in Cancer Transcriptomes and Improving Sonification Techniques Using Genetic Algorithms with Dr. Natalia Khuri
- WORDLE: An Investigation Into Optimizing Game Play with Dr. Pete Santago
These projects were undertaken by Masters students to complete the M.S. thesis track option.
- Fourier-Enhanced Neural Networks For Systems Biology Applications with Dr. Minghan Chen
These projects have been supported by the URECA Wake Forest Research Fellowship mechanism, Richter Scholars mechanism, or Computer Science Department funding. Abstracts from students’ work can be found in this 2022 Undergraduate Research Day program.
- Anomaly Detection Using Deep Reinforcement Learning with Dr. Sarra Alqahtani
- Avoiding Communication in High-Performance Kernel Logistic Regression with Dr. Aditya Devarakonda
- Using Evolutionary Algorithms and Pareto Rankings to Identify Secure Virtual Local Area Networks with Dr. Errin Fulp
- Evolutionary Multiobjective Clustering of Single-Cell RNA-Sequence Data with Dr. Natalia Khuri
- A Neural Network Approach to Road Segmentation in the Peruvian Amazon with Dr. Paúl Pauca
- Topic Modeling to Analyze Philosophers’ Evolving Ethical View of Computer Science Technology with Professor Sarah Parsons
2021-22
These projects were undertaken by senior computer science majors invited to obtain departmental honors upon graduation.
- Improving the Efficiency and Effectiveness of Reinforcement Learning Using Latent Space and Testing Algorithmic Fairness Via Machine Learning and Identifying and Explaining Regions of Sub-Optimality in Reinforcement Learning Agents with Dr. Sarra Alqahtani
- Randomized Algorithms for Tucker Approximations of Tensors with Dr. Grey Ballard
- Dynamic Sequential Neural Networks Using Basic Expansion Matrix and Developing a Systematic Model To Understand the Key Mechanisms Underlying Neurodegenerative Diseases with Dr. Minghan Chen
- High Performance Parallelization Strategies For Partitioned Local Depth (PaLD) Clustering with Dr. Sam Cho
- Managing Virtual Local Area Networks: Identifying Secure VLANs Using Evolutionary Algorithms and Using Evolutionary Algorithms and Pareto Rankings to Identify Secure Virtual Local Area Networks When Security Policies Are Changed and Software Code Coverage Through Dynamic Analysis in Black-Box Testing Environments with Dr. Errin Fulp
- Impact of General Data Protection Regulation on Machine Learning in Healthcare with Dr. Natalia Khuri
These projects were undertaken by Masters students to complete the M.S. thesis track option.
- Efficient Computation of Tucker Tensor Decomposition and Statistical Moment Tensor with Dr. Grey Ballard
- Empirically Measuring and Evolving Common Password Heuristics with Dr. Errin Fulp
These projects have been supported by the URECA Wake Forest Research Fellowship mechanism, Richter Scholars mechanism, or Computer Science Department funding.
- The Shaken Cybersecurity of Brazil, Robust MARL Algorithm Against Compromised Agent Attacks, and Multi-Agent Deep Reinforcement Learning for Adaptive Exploration of Unknown Environments with Dr. Sarra Alqahtani
- Generative Deep Learning for Pediatric Intensive Care Unit Patient Comfort with Dr. Grey Ballard
- Analysis and Generation of 15th to 17th Century Counterpoint Using Hidden Markov Models with Dr. Jennifer Burg
- Analyzing the Interaction and Propagation Pattern of Amyloid and Tau in Alzheimer’s Disease using Longitudinal Neuroimaging Data and Uncovering the Heterogeneity of Neurodegeneration Trajectories in Alzheimer’s Disease Using Deep Predictive Stratification Network with Dr. Minghan Chen
- Smart Spaces for the Visually Impaired with Dr. Paúl Pauca
2020-21
These projects were undertaken by senior computer science majors invited to obtain departmental honors upon graduation.
- Machine Learning Techniques to Detect Adversaries in Multi-Agent Reinforcement Learning Systems with Dr. Sarra Alqahtani
- Using Fast Matrix Multiplication to Speedup Neural Network Training with Dr. Grey Ballard
- Computational Model of the Regulatory Network and Protein Proteolysis in Caulobacter Crescentus with Dr. Minghan Chen
- Reverse Engineering Compilation and Execution Information of Binary Files with Machine Learning and Evaluating Performance of Deep Learning-Based
Content-Aware Image Restoration Methods with Dr. Sam Cho - Computing the Value of Data in Machine Learning Applications and Dimensionality Reduction of Single Cell RNA-seq Data and Segmentation of COVID-19 Lung Infection from CT Images with Dr. Natalia Khuri
- Image Emotion Recognition Model Based on Age and Gender using Deep Neural Networks with Dr. Paúl Pauca
These projects were undertaken by Masters students to complete the M.S. thesis track option.
- Parallel Algorithms for Low-Rank Approximations of Matrices and Tensors with Dr. Grey Ballard
- Classification of Heterogeneous Data Sets of Single Cell RNA Sequencing Experiments Using Deep Learning and Predicting Single Guide RNA Targets for Genome Editing Using Deep Learning with Dr. Natalia Khuri