Data Science
Data Science Blog
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Quantum Machine Learning and Variational Quantum Algorithms for Differential Equations
MTSU Computational and Data Science Ph.D. student, Yuan Chen, presents elements from his dissertation proposal on Quantum Algorithms for Differential Equations. This talk presents a collection of works on quantum and hybrid quantum–classical methods for differential equations, with emphasis on the two directions: learning-based quantum models for dynamical systems and lightweight quantum recurrent architectures. Differential
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2026-27 Data Science Student Steve and Kathy Anderson Scholarship Winners
We are excited to announce the recipients of the prestigious Steve and Kathy Anderson Scholarship for the 2026–2027 academic year! This highly competitive scholarship recognizes outstanding students in the MTSU Data Science program who have demonstrated exceptional academic achievement, passion for data science, and a commitment to making a meaningful impact here at MTSU. This year,
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TriAffect: Tri-Modal Conversational Emotion Recognition with Temporal State Tracking
Computational and Data Science Ph.D. student, Cayden Schalk, presents his research work on Emotion Recognition. Understanding emotion in conversation requires combining cues from language, vocal expression, and visual behavior while accounting for how emotion evolves across speakers and dialogue turns. This problem is important for multimodal interactive systems such as emotion-aware assistants, social robots, and
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Addressing Computational Challenges in Geospatial Applications using Graph Structures
Computational and Data Science Ph.D. student Abigail Kelly presents elements from her internship and research. Her research focuses on Geospatial Data and Graph Theory – specifically, how to extract patterns from this difficult type of data. Geospatial data science focuses on extracting patterns and knowledge from data containing a spatial or geographic component. This discipline is
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Faculty and Staff Spotlight – Lisa Eddy
Lisa Eddy is one of the advisors for the Data Science Program. Lisa advises students whose last names begin with A-K. What is your degree? B.S. in Liberal Studies with an emphasis in Administration and Education Advice for Students Don’t limit yourself by going it alone! Think of campus like a Data Science project. Gather information from
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Predictive Maintenance for heavy equipment with a classical and Quantum Support Vector Machine using novel data
Computational and Data Science Ph.D. student, Laurel Koenig, presents elements from their internship and research, Predictive Maintenance for heavy equipment with a classical and Quantum Support Vector Machine using novel data. This work shows the differences between quantum and classical machine learning on a real-world dataset Predictive maintenance is the blanket term for methods used
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Predictive and Representation Learning for fMRI-Based Brain Disorder Analysis
Computational and Data Science Ph.D. student, Haoyuan Wang, presents Predictive and Representational Learning for fMRI-Based Brain Disorder Analysis. Neural network–based predictive and representation learning approaches are developed to improve model reliability and representational capacity for complex fMRI data. The capability of neural networks to capture high-dimensional, nonlinear structures is first examined, and a custom loss
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Parallel Algorithms for Open-Locating Dominating Sets
Computational and Data Science Ph.D. student, Robert Dohner, presents an overview of algorithms for computing open-locating-dominating (OLD) sets, a graph-based framework for fault detection and sensor placement in networks. This seminar introduces Infrastructure as Code (IaC) and discusses its relevance to data science research. Using Terraform as an example, the talk demonstrates how computing environments and machine
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Faculty and Staff Spotlight – Dr. Ramchandra Rimal
Dr. Rimal is the advisor for the Graduate Certificate in Data Science and an Assistant Professor in Mathematical Sciences. Year joined MTSU: 2020 Data Science Classes Taught DATA 3550 Applied Predictive Modeling DATA 6990 Topics Seminar in Data Science Data Science Involvement at MTSU Developing data science courses, mentoring students, and participating/organizing events on machine learning and
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Infrastructure as Code for Data Science: Reproducible Machine Learning Workflows with Terraform
Computational and Data Science Ph.D student, Dongyu Liu, presents an overview of the open source Terraform framework. This system is a fascinating approach toward machine learning workflows, deployment, and provisioning of ML systems on both local and cloud resources. This seminar introduces Infrastructure as Code (IaC) and discusses its relevance to data science research. Using Terraform as an example,
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