Computational and Data Science, Ph.D.

Computational and Data Science

Interdisciplinary Ph.D. in Computational & Data Science. Research-intensive, programming, communication skills.

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Computational and Data Science, Ph.D.

The Computational and Data Science Ph.D. is an interdisciplinary program that includes faculty from Agriculture, Biology, Chemistry, Computer Science, Engineering Technology, Geosciences, Mathematical Sciences, and Physics and Astronomy.

The program is research-intensive and applied in nature, seeking to produce graduates with competency in the following three key areas:

  • Mastery of the mathematical methods of computation as applied to scientific research investigations coupled with a firm understanding of the underlying fundamental science in at least one disciplinary specialization.
  • Deep knowledge of programming languages, scientific programming, and computing technology so that graduates can adapt and grow as computing systems evolve
  • Effective written and oral communication skills so that graduates may assume leadership positions in academia, national labs, and industry.

The Computational and Data Science Ph.D. program is for students who are working toward their doctoral degrees. However, with a few extra courses and requirements, most students in the program can complete a Master's degree in Mathematics, Computer Science, or Data Science before they graduate.

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Careers
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Faculty
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News Briefs

Alum find success in field after graduation

Alum find success in field after graduation

Dr. Robert Michael began his graduate studies at MTSU in 2008 in the Department of Mathematics. In 2014, he completed his Ph.D. in Computational Science and his master’s degree in Computer Science. His dissertation focused on computational chemistry.

After graduating, he became an HPC specialist at St. Jude Children’s Research Hospital, after which he became Oak Ridge National Laboratory’s Chief Data Architect. He is currently an HPC System Architect at Roche Sequencing Solutions.

Michael, J. R. (2014). Analysis of Thermal Motion Effects on the Electron Density via Computational Simulations (Order No. 3668039). Available from Dissertations & Theses @ Middle Tennessee State University; ProQuest Dissertations & Theses Global. (1647473197).

Alum's research focuses on mathematical models of tumor growth

Alum's research focuses on mathematical models of tumor growth

Dr. Richard Ewool began his undergraduate studies in Ghana. After joining the Ph.D. program, his research and undergraduate studies focused on Mathematical models of tumor growth. After graduating, he became an Assistant Professor of Mathematics at Baptist Health Services University in Memphis.

Ewool, R. C. (2016). Mathematical modeling and simulation of a multiscale tumor induced angiogenesis model (Order No. 10146829). Available from Dissertations & Theses @ Middle Tennessee State University; ProQuest Dissertations & Theses Global. (1829637016).

News Briefs

Alum find success in field after graduation

Dr. Robert Michael began his graduate studies at MTSU in 2008 in the Department of Mathematics. In 2014, he completed his Ph.D. in Computational Science and his master’s degree in Computer Science. His dissertation focused on computational chemistry.

After graduating, he became an HPC specialist at St. Jude Children’s Research Hospital, after which he became Oak Ridge National Laboratory’s Chief Data Architect. He is currently an HPC System Architect at Roche Sequencing Solutions.

Michael, J. R. (2014). Analysis of Thermal Motion Effects on the Electron Density via Computational Simulations (Order No. 3668039). Available from Dissertations & Theses @ Middle Tennessee State University; ProQuest Dissertations & Theses Global. (1647473197).

Alum's research focuses on mathematical models of tumor growth

Dr. Richard Ewool began his undergraduate studies in Ghana. After joining the Ph.D. program, his research and undergraduate studies focused on Mathematical models of tumor growth. After graduating, he became an Assistant Professor of Mathematics at Baptist Health Services University in Memphis.

Ewool, R. C. (2016). Mathematical modeling and simulation of a multiscale tumor induced angiogenesis model (Order No. 10146829). Available from Dissertations & Theses @ Middle Tennessee State University; ProQuest Dissertations & Theses Global. (1829637016).

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CAREERS

Computational and Data Science, Ph.D.


Since computational and data science involves using computers to solve scientific problems, graduates can work as research scientists in almost any field of science or engineering in industry or government, or at a university. MTSU’s program has focus areas in bioinformatics, biological modeling, computational chemistry, computational graph theory, computational physics, engineering and differential equations, high performance computing, and machine learning and remote sensing. In each of these areas, MTSU faculty and students are working on cutting-edge research projects that cut across traditional departmental boundaries.

Employers of MTSU alumni include

Our graduates from the Computational and Data Science Ph.D. program have found jobs or received offers in companies and academic positions at universities including:

  • St. Jude's Children's Hospital
  • John Hopkin's University
  • Southern Arkansas State University
  • Texas A&M
  • Oak Ridge National Laboratory
  • Duke University
MTSU Career Development Center

MTSU’s Career Development Center

MTSU offers a comprehensive Career Development Center that serves students throughout the full student experience and beyond. They collaborate with faculty and staff to equip students with the tools to be marketable to the world of work and continuing education.  

Students can schedule an appointment or check online resources and job boards at mtsu.edu/career

Students can find current internship opportunities by talking to faculty and visiting the University job and internship board called Handshake

Wondering what you can do with your major? Check out our What Can I Do with A Major In guides. 

REQUIREMENTS

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Assistantships

Research and teaching assistantships, with stipends beginning at $20,100, are available on a competitive basis to full-time students in the COMS program. In addition to the stipend, the university also pays all tuition and most fees for assistantship holders. Non-Tennessee residents who are awarded a graduate assistantship are not required to pay out-of-state fees. To learn more about the types of graduate assistantships and to download an application, visit the Graduate Studies Assistantship page.

The College of Graduate Studies also awards a limited number of scholarships. For additional information and applications, visit the Graduate Studies Finance page.

In addition to assistantships and scholarships, MTSU's Office of Financial Aid assists graduate students seeking other forms of financial support while in school.

Student Forms

Research in Computational and Data Science

Computation is now regarded as an equal and indispensable partner, along with theory and experiment, in the advance of scientific knowledge. Numerical simulation enables the study of complex systems and natural phenomena that would be too expensive or dangerous, or even impossible, to study by direct experimentation. The quest for increasing levels of detail and realism in such simulations requires enormous computational capacity, and has provided the impetus for dramatic breakthroughs in computer algorithms and architectures. Due to these advances, computational scientists can now solve large-scale problems that were once thought intractable.

Computational Science is in a rapidly growing multidisciplinary area with connections to the sciences, mathematics, and computer science. The program focuses on the development of problem-solving methodologies and robust tools for the solution of scientific problems.

The Computational and Data Science (COMS) program is a broad multidisciplinary area that encompasses applications in science, applied mathematics, numerical analysis, and computer science. Computer models and computer simulations have become an important part of the research repertoire, supplementing (and in some cases replacing) experimentation. Going from application area to computational results requires domain expertise, mathematical modeling, numerical analysis, algorithm development, software implementation, program execution, analysis, validation, and visualization of results. The COMS program comprises all of the above.

MTSU’s program and research includes elements from computer science, applied mathematics, and science. The COMS program focuses on the integration of knowledge and methodologies from all of these disciplines, but is also distinct from the rest.

It is hard to capture how broad the program is without looking at some of the publications recently submitted. They are from across virtually every discipline. However, the common theme is the use of computers to solve cutting-edge scientific problems.

Publications

Publications of the Computational and Data Science Faculty 2018-Present

Bold indicates a faculty author. 

Al-Tobasei, Rafet, Ali Ali, Andre L.S. Garcia, Daniela Lourenco, Tim Leeds, and Mohamed Salem. 2021. “Genomic Predictions for Fillet Yield and Firmness in Rainbow Trout Using Reduced-Density SNP Panels.” BMC Genomics 22 (1). https://doi.org/10.1186/s12864-021-07404-9.

Ali, Ali, Rafet Al-Tobasei, Brett Kenney, Timothy D. Leeds, and Mohamed Salem. 2018. “Integrated Analysis of LncRNA and MRNA Expression in Rainbow Trout Families Showing Variation in Muscle Growth and Fillet Quality Traits.” Scientific Reports 8 (1). https://doi.org/10.1038/s41598-018-30655-8.

Ali, Ali, Rafet Al-Tobasei, Daniela Lourenco, Tim Leeds, Brett Kenney, and Mohamed Salem. 2019. “Genome-Wide Association Study Identifies Genomic Loci Affecting Filet Firmness and Protein Content in Rainbow Trout.” Frontiers in Genetics 10 (May). https://doi.org/10.3389/fgene.2019.00386.

———. 2020a. “Genome-Wide Scan for Common Variants Associated with Intramuscular Fat and Moisture Content in Rainbow Trout.” BMC Genomics 21 (1). https://doi.org/10.1186/s12864-020-06932-0.

———. 2020b. “Genome-Wide Identification of Loci Associated with Growth in Rainbow Trout.” BMC Genomics 21 (1). https://doi.org/10.1186/s12864-020-6617-x.

Alrammah, Huda, and Yi Gu. 2021. “Workflow Scheduling in Clouds Using Pareto Dominance for Makespan, Cost and Energy.” In ICC 2021 - IEEE International Conference on Communications. IEEE. https://doi.org/10.1109/ICC42927.2021.9500489.

Alrammah, Huda, Yi Gu, and Zhifeng Liu. 2020. “Tri-Objective Workflow Scheduling and Optimization in Heterogeneous Cloud Environments.” In 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE. https://doi.org/10.1109/IPDPSW50202.2020.00129.

Alshehri, Asma, John Ford, and Rachel Leander. 2020. “The Impact of Maturation Time Distributions on the Structure and Growth of Cellular Populations.” Mathematical Biosciences and Engineering 17 (2). https://doi.org/10.3934/mbe.2020098.

Alzahrani, S.S., and A.Q.M. Khaliq. 2019. “Fourier Spectral Exponential Time Differencing Methods for Multi-Dimensional Space-Fractional Reaction–Diffusion Equations.” Journal of Computational and Applied Mathematics 361 (December). https://doi.org/10.1016/j.cam.2019.04.001.

Bagheri, Minoo, Hemant K. Tiwari, Anarina L. Murillo, Rafet Al-Tobasei, Donna K. Arnett, Tobias Kind, Dinesh Kumar Barupal, et al. 2020. “A Lipidome-Wide Association Study of the Lipoprotein Insulin Resistance Index.” Lipids in Health and Disease 19 (1). https://doi.org/10.1186/s12944-020-01321-8.

Barlow, Angela T., Natasha E. Gerstenschlager, Jeremy F. Strayer, Alyson E. Lischka, D. Christopher Stephens, Kristin S. Hartland, and J. Christopher Willingham. 2018. “Scaffolding for Access to Productive Struggle.” Mathematics Teaching in the Middle School 23 (4). https://doi.org/10.5951/mathteacmiddscho.23.4.0202.

Barlow, Angela T., Alyson E. Lischka, James C. Willingham, Kristin Hartland, and D. Christopher Stephens. 2018. “The Relationship of Implicit Theories to Elementary Teachers’ Patterns of Engagement in a Mathematics-Focused Professional Development Setting. .” Mid-Western Educational Researcher 30 (3): 93–122.

Barron, Mace G., Ryan R. Otter, Kristin A. Connors, Aude Kienzler, and Michelle R. Embry. 2021. “Ecological Thresholds of Toxicological Concern: A Review.” Frontiers in Toxicology 3 (March). https://doi.org/10.3389/ftox.2021.640183.

Beaubien, Gale B., Connor I. Olson, and Ryan R. Otter. 2019. “The Role of Sexual Dimorphism and Tissue Selection in Ecotoxicological Studies Using the Riparian Spider Tetragnatha Elongata.” Bulletin of Environmental Contamination and Toxicology 103 (2). https://doi.org/10.1007/s00128-019-02632-y.

Beaubien, Gale B., Connor I. Olson, Andrew C. Todd, and Ryan R. Otter. 2020. “The Spider Exposure Pathway and the Potential Risk to Arachnivorous Birds.” Environmental Toxicology and Chemistry 39 (11). https://doi.org/10.1002/etc.4848.

Biala, T.A., and A.Q.M. Khaliq. 2021. “A Fractional-Order Compartmental Model for the Spread of the COVID-19 Pandemic.” Communications in Nonlinear Science and Numerical Simulation 98 (July). https://doi.org/10.1016/j.cnsns.2021.105764.

Bratsos, A.G., and A.Q.M. Khaliq. 2019. “An Exponential Time Differencing Method of Lines for Burgers–Fisher and Coupled Burgers Equations.” Journal of Computational and Applied Mathematics 356 (August). https://doi.org/10.1016/j.cam.2019.01.028.

Brown, Ei, Zackery D. Fleischman, Larry D. Merkle, Emmanuel Rowe, Arnold Burger, Stephen A. Payne, and Mark Dubinskii. 2018. “Optical Spectroscopy of Holmium Doped K2LaCl5.” Journal of Luminescence 196 (April). https://doi.org/10.1016/j.jlumin.2017.12.040.

Brown, Ei, Zackery D. Fleischman, Larry D. Merkle, Emmanuel Rowe, Arnold Burger, Stephen Payne, and Mark Dubinskiy. 2018. “Infrared Absorption and Fluorescence Properties of Holmium Doped Potassium Lanthanum Chloride (Conference Presentation).” In Laser Technology for Defense and Security XIV, edited by Mark Dubinskiy and Timothy C. Newell. SPIE. https://doi.org/10.1117/12.2309578.

Castillo, Carlos, Henrique G. Momm, Robert R. Wells, Ronald L. Bingner, and Rafael Pérez. 2021. “A GIS Focal Approach for Characterizing Gully Geometry.” Earth Surface Processes and Landforms 46 (9). https://doi.org/10.1002/esp.5122.

Chapagain, Pratima, Brock Arivett, Beth M. Cleveland, Donald M. Walker, and Mohamed Salem. 2019. “Analysis of the Fecal Microbiota of Fast- and Slow-Growing Rainbow Trout (Oncorhynchus Mykiss).” BMC Genomics 20 (1). https://doi.org/10.1186/s12864-019-6175-2.

Chapagain, Pratima, Donald Walker, Tim Leeds, Beth M. Cleveland, and Mohamed Salem. 2020. “Distinct Microbial Assemblages Associated with Genetic Selection for High- and Low- Muscle Yield in Rainbow Trout.” BMC Genomics 21 (1). https://doi.org/10.1186/s12864-020-07204-7.

Chen, Shanshan, Junping Shi, Zhisheng Shuai, and Yixiang Wu. 2019. “Spectral Monotonicity of Perturbed Quasi-Positive Matrices with Applications in Population Dynamics,” November.

———. 2020. “Asymptotic Profiles of the Steady States for an SIS Epidemic Patch Model with Asymmetric Connectivity Matrix.” Journal of Mathematical Biology 80 (7). https://doi.org/10.1007/s00285-020-01497-8.

Connors, Kristin A., Amy Beasley, Mace G. Barron, Scott E. Belanger, Mark Bonnell, Jessica L. Brill, Dick de Zwart, et al. 2019. “Creation of a Curated Aquatic Toxicology Database: EnviroTox.” Environmental Toxicology and Chemistry 38 (5). https://doi.org/10.1002/etc.4382.

Cui, Song, Qiang Wu, James West, and Jiangping Bai. 2019. “Machine Learning-Based Microarray Analyses Indicate Low-Expression Genes Might Collectively Influence PAH Disease.” PLOS Computational Biology 15 (8). https://doi.org/10.1371/journal.pcbi.1007264.

Cui, Xia, Thomas Goff, Song Cui, Dorothy Menefee, Qiang Wu, Nithya Rajan, Shyam Nair, Nate Phillips, and Forbes Walker. 2021. “Predicting Carbon and Water Vapor Fluxes Using Machine Learning and Novel Feature Ranking Algorithms.” Science of The Total Environment 775 (June). https://doi.org/10.1016/j.scitotenv.2021.145130.

Deng, Keng, Glenn F. Webb, and Yixiang Wu. 2020. “Analysis of Age and Spatially Dependent Population Model: Application to Forest Growth.” Nonlinear Analysis: Real World Applications 56 (December). https://doi.org/10.1016/j.nonrwa.2020.103164.

Ding, Wandi, Ryan Florida, Jeffery Summers, Puran Nepal, and Ben Burton. 2019. “Experience and Lessons Learned from Using SIMIODE Modeling Scenarios.” PRIMUS 29 (6). https://doi.org/10.1080/10511970.2018.1488318.

  1. Barbosa, Salvador. 2020. “Using Holographically Compressed Embeddings in Question Answering.” In Computer Science & Information Technology. AIRCC Publishing Corporation. https://doi.org/10.5121/csit.2020.100919.

Ellingham, M. N., Songling Shan, Dong Ye, and Xiaoya Zha. 2021. “Toughness and Spanning Trees in K4‐minor‐free Graphs.” Journal of Graph Theory 96 (3). https://doi.org/10.1002/jgt.22620.

Epifanovsky, Evgeny, Andrew T. B. Gilbert, Xintian Feng, Joonho Lee, Yuezhi Mao, Narbe Mardirossian, Pavel Pokhilko, et al. 2021. “Software for the Frontiers of Quantum Chemistry: An Overview of Developments in the Q-Chem 5 Package.” The Journal of Chemical Physics 155 (8). https://doi.org/10.1063/5.0055522.

Faezipour, Misagh, and Miad Faezipour. 2020. “Sustainable Smartphone-Based Healthcare Systems: A Systems Engineering Approach to Assess the Efficacy of Respiratory Monitoring Apps.” Sustainability 12 (12). https://doi.org/10.3390/su12125061.

———. 2021a. “Smart Healthcare Monitoring Apps with a Flavor of Systems Engineering.” In . https://doi.org/10.1007/978-3-030-71051-4_48.

———. 2021b. “Efficacy of Smart EEG Monitoring Amidst the COVID-19 Pandemic.” Electronics 10 (9). https://doi.org/10.3390/electronics10091001.

———. 2021c. “System Dynamics Modeling for Smartphone-Based Healthcare Tools: Case Study on ECG Monitoring.” IEEE Systems Journal 15 (2). https://doi.org/10.1109/JSYST.2020.3009187.

Faezipour, Misagh, and Susan Ferreira. 2018. “A System Dynamics Approach for Sustainable Water Management in Hospitals.” IEEE Systems Journal 12 (2). https://doi.org/10.1109/JSYST.2016.2573141.

Feng, Yunlong, and Qiang Wu. 2020. “Learning under (1 + ϵ)-Moment Conditions.” Applied and Computational Harmonic Analysis 49 (2). https://doi.org/10.1016/j.acha.2020.05.009.

———. 2021. “A Framework of Learning Through Empirical Gain Maximization.” Neural Computation 33 (6). https://doi.org/10.1162/neco_a_01384.

Fernando, Kushantha, and Vajira Manathunga. 2021. “An Alternative Approach to Evaluate American Options Price Using HJM Approach,” September.

Fitzgibbon, W. E., J. J. Morgan, G. F. Webb, And Y. Wu. 2020. “Analysis Of A Reaction–Diffusion Epidemic Model With Asymptomatic Transmission.” Journal of Biological Systems 28 (03). https://doi.org/10.1142/S0218339020500126.

Fitzgibbon, William E., Jeffery J. Morgan, Glenn F. Webb, and Yixiang Wu. 2019. “Spatial Models of Vector-Host Epidemics with Directed Movement of Vectors over Long Distances.” Mathematical Biosciences 312 (June). https://doi.org/10.1016/j.mbs.2019.04.003.

Fitzgibbon, William E., Jeffrey J. Morgan, Glenn F. Webb, and Yixiang Wu. 2020. “Modelling the Aqueous Transport of an Infectious Pathogen in Regional Communities: Application to the Cholera Outbreak in Haiti.” Journal of The Royal Society Interface 17 (169). https://doi.org/10.1098/rsif.2020.0429.

Fitzgibbon, William, Jeffrey Morgan, Glenn Webb, and Yixiang Wu. 2020. “Maritime Transport and the Threat of Bio Invasion and the Spread of Infectious Disease.” In Computational Methods in Applied Scienceshttps://doi.org/10.1007/978-3-030-37752-6_5.

Gerstenschlager, Natasha, Angela T. Barlow, Alyson Lischka, Lucy Watson, Jeremy Strayer, D. Christopher Stephens, Kristin S. Hartland, and James C. Willingham. 2021. “Double Demonstration Lessons: Authentically Participating in an Inquiry Stance.” Mathematics Teacher Educator 9 (2). https://doi.org/10.5951/MTE.2020.0048.

Grajal-Puche, Alejandro, Christopher M. Murray, Matthew Kearley, Mark Merchant, Christopher Nix, Jonathan K. Warner, and Donald M. Walker. 2020. “Microbial Assemblage Dynamics Within the American Alligator Nesting Ecosystem: A Comparative Approach Across Ecological Scales.” Microbial Ecology 80 (3). https://doi.org/10.1007/s00248-020-01522-9.

Grisnik, Matthew, Olivia Bowers, Andrew J Moore, Benjamin F Jones, Joshua R Campbell, and Donald M Walker. 2020. “The Cutaneous Microbiota of Bats Has in Vitro Antifungal Activity against the White Nose Pathogen.” FEMS Microbiology Ecology 96 (2). https://doi.org/10.1093/femsec/fiz193.

Grisnik, Matthew, Jacob Leys, Danny Bryan, Rebecca Hardman, Debra Miller, Vincent Cobb, Chris Ogle, et al. 2018. “Host and Geographic Range of Snake Fungal Disease in Tennessee, USA.” Herpetological Review 49 (October): 682–90.

Gu, Yi, and Chandu Budati. 2020. “Energy-Aware Workflow Scheduling and Optimization in Clouds Using Bat Algorithm.” Future Generation Computer Systems 113 (December). https://doi.org/10.1016/j.future.2020.06.031.

Gulizia, J. P., K. M. Downs, and S. Cui. 2019. “Kudzu ( Pueraria Montana Var. Lobata ) Age Variability Effects on Total and Nutrient-Specific in Situ Rumen Degradation.” Journal of Applied Animal Research 47 (1). https://doi.org/10.1080/09712119.2019.1652615.

Gulizia, Joseph, Kevin Downs, and Song Cui. 2019. “55 The Influence of Kudzu (Pueraria Montana Var. Lobata) Age on in Situ Rumen Degradation.” Journal of Animal Science 97 (Supplement_1). https://doi.org/10.1093/jas/skz053.194.

Guo, X., T Hu, and Q. Wu. 2020. “Distributed Minimum Error Entropy Algorithms.” Journal of Machine Learning Research 21 (126): 1–31.

Guo, Xin, Lexin Li, and Qiang Wu. 2020. “Modeling Interactive Components by Coordinate Kernel Polynomial Models.” Mathematical Foundations of Computing 3 (4). https://doi.org/10.3934/mfc.2020010.

Győri, Ervin, Michael D. Plummer, Dong Ye, and Xiaoya Zha. 2020. “Cycle Traversability for Claw-Free Graphs and Polyhedral Maps.” Combinatorica 40 (3). https://doi.org/10.1007/s00493-019-4042-z.

Haruna, Samuel I., Stephen H. Anderson, Ranjith P. Udawatta, Clark J. Gantzer, Nathan C. Phillips, Song Cui, and Ying Gao. 2020. “Improving Soil Physical Properties through the Use of Cover Crops: A Review.” Agrosystems, Geosciences & Environment 3 (1). https://doi.org/10.1002/agg2.20105.

He, Fangchao, and Qiang Wu. 2019. “Bias Corrected Regularization Kernel Method in Ranking.” Analysis and Applications 17 (01). https://doi.org/10.1142/S0219530518500161.

He, Jinghua, Erling Wei, Dong Ye, and Shaohui Zhai. 2019. “On Perfect Matchings in Matching Covered Graphs.” Journal of Graph Theory 90 (4). https://doi.org/10.1002/jgt.22411.

Hill, Aubree J., Jacob E. Leys, Danny Bryan, Fantasia M. Erdman, Katherine S. Malone, Gabrielle N. Russell, Roger D. Applegate, et al. 2018. “Common Cutaneous Bacteria Isolated from Snakes Inhibit Growth of Ophidiomyces Ophiodiicola.” EcoHealth 15 (1). https://doi.org/10.1007/s10393-017-1289-y.

Hong, Don. 2019. “On Scattered Data Representations Using Bivariate Splines. Handbook of Analytic-Computational Methods in Applied Mathematics.” In Handbook of Analytic-Computational Methods in Applied Mathematics, edited by George Anastassiou. Chapman and Hall/CRC. https://doi.org/10.1201/9780429123610.

Hu, Ting, Qiang Wu, and Ding-Xuan Zhou. 2020. “Distributed Kernel Gradient Descent Algorithm for Minimum Error Entropy Principle.” Applied and Computational Harmonic Analysis 49 (1). https://doi.org/10.1016/j.acha.2019.01.002.

———. 2021. “Kernel Gradient Descent Algorithm for Information Theoretic Learning.” Journal of Approximation Theory 263 (March). https://doi.org/10.1016/j.jat.2020.105518.

Huang, Shouyou, Yunlong Feng, and Qiang Wu. 2021. “Learning Theory of Minimum Error Entropy under Weak Moment Conditions.” Analysis and Applications, March. https://doi.org/10.1142/S0219530521500044.

Huang, Shouyou, and Qiang Wu. 2021. “Robust Pairwise Learning with Huber Loss.” Journal of Complexity 66 (October). https://doi.org/10.1016/j.jco.2021.101570.

Hunsaker, Aaron, William B. Goodwin, Emmanuel Rowe, Caleb Wheeler, Liviu Matei, Vladimir Buliga, and Arnold Burger. 2021. “Ceramic Cs 2 HfCl 6 : A Novel Scintillation Material for Use in Gamma Ray Spectroscopy.” Crystal Research and Technology 56 (9). https://doi.org/10.1002/crat.202000166.

Iskakov, Sergei, Hanna Terletska, and Emanuel Gull. 2018. “Momentum-Space Cluster Dual-Fermion Method.” Physical Review B 97 (12). https://doi.org/10.1103/PhysRevB.97.125114.

Jator, S.N., and V. Manathunga. 2018. “Block Nyström Type Integrator for Bratu’s Equation.” Journal of Computational and Applied Mathematics 327 (January). https://doi.org/10.1016/j.cam.2017.06.025.

Jones, R. Sky, and H.G. Momm. 2021. “An Index for Quantifying Geometric Point Disorder in Geospatial Applications.” Computers & Geosciences 151 (June). https://doi.org/10.1016/j.cageo.2021.104756.

Jovanovich, Michael, and Joshua Phillips. 2018. “N-Task Learning: Solving Multiple or Unknown Numbers of Reinforcement Learning Problems.” Cognitive Science.

Kang, Liying, Weihua Lu, Yezhou Wu, Dong Ye, and Cun-Quan Zhang. 2018. “Circuit Decompositions and Shortest Circuit Coverings of Hypergraphs.” Graphs and Combinatorics 34 (2). https://doi.org/10.1007/s00373-018-1881-0.

Kazmi, Kamran, and Abdul Q.M. Khaliq. 2020. “An Efficient Split-Step Method for Distributed-Order Space-Fractional Reaction-Diffusion Equations with Time-Dependent Boundary Conditions.” Applied Numerical Mathematics 147 (January). https://doi.org/10.1016/j.apnum.2019.08.019.

Khan, Nibraas, and Joshua Phillips. 2020. “Combined Model for Sensory-Based and Feedback-Based Task Switching: Solving Hierarchical Reinforcement Learning Problems Statically and Dynamically with Transfer Learning.” In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE. https://doi.org/10.1109/ICTAI50040.2020.00055.

Khiabani, Vahid H, Ahad S Nasab, and Vishwas Narayan Bedekar. 2018. “AN EXPERIMENTAL ADAPTIVE TEACHING PRACTICE.” Proceedings of the International Annual Conference of the American Society for Engineering Management. Huntsville: American Society for Engineering Management (ASEM). https://ezproxy.mtsu.edu/login?url=https://www.proquest.com/conference-papers-proceedings/experimental-adaptive-teaching-practice/docview/2193094250/se-2?accountid=4886.

Leander, R. N., Y. Wu, W. Ding, D. E. Nelson, and Z. Sinkala. 2021. “A Model of the Innate Immune Response to SARS-CoV-2 in the Alveolar Epithelium.” Royal Society Open Science 8 (8). https://doi.org/10.1098/rsos.210090.

Leander, Rachel, Wandi Ding, and René A. Salinas. 2018. “Dedication to Suzanne Lenhart.” Natural Resource Modeling 31 (4). https://doi.org/10.1111/nrm.12198.

Lewis, Conrad, Emil Proynov, Jianguo Yu, and Jing Kong. 2021. “Analyzing Cases of Significant Nondynamic Correlation with DFT Using the Atomic Populations of Effectively Localized Electrons,” September.

Li, Cen, Michael Hains, John Wallin, and Qiang Wu. 2019. “Applying Data Science Methods for Early Prediction of Undergraduate Student Retention.” In 2019 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE. https://doi.org/10.1109/CSCI49370.2019.00250.

Li, Cen, Ebosehon Imeokparia, Michael Ketzner, and Tsega Tsahai. 2019. “Teaching the NAO Robot to Play a Human-Robot Interactive Game.” In 2019 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE. https://doi.org/10.1109/CSCI49370.2019.00134.

Li, Qiuli, Wai Chee Shiu, Pak Kiu Sun, and Dong Ye. 2018. “On the Anti-Kekulé Problem of Cubic Graphs.” The Art of Discrete and Applied Mathematics 2 (1). https://doi.org/10.26493/2590-9770.1264.94b.

Li, Yuan, Song Cui, Scott X. Chang, and Qingping Zhang. 2019. “Liming Effects on Soil PH and Crop Yield Depend on Lime Material Type, Application Method and Rate, and Crop Species: A Global Meta-Analysis.” Journal of Soils and Sediments 19 (3). https://doi.org/10.1007/s11368-018-2120-2.

Li, Yuan, Zhou Li, Scott X. Chang, Song Cui, Sindhu Jagadamma, Qingping Zhang, and Yanjiang Cai. 2020. “Residue Retention Promotes Soil Carbon Accumulation in Minimum Tillage Systems: Implications for Conservation Agriculture.” Science of The Total Environment 740 (October). https://doi.org/10.1016/j.scitotenv.2020.140147.

Li, Yuan, Zhou Li, Song Cui, Scott X. Chang, Chunlin Jia, and Qingping Zhang. 2019. “A Global Synthesis of the Effect of Water and Nitrogen Input on Maize (Zea Mays) Yield, Water Productivity and Nitrogen Use Efficiency.” Agricultural and Forest Meteorology 268 (April). https://doi.org/10.1016/j.agrformet.2019.01.018.

Li, Yuan, Zhou Li, Song Cui, Sindhu Jagadamma, and Qingping Zhang. 2019. “Residue Retention and Minimum Tillage Improve Physical Environment of the Soil in Croplands: A Global Meta-Analysis.” Soil and Tillage Research 194 (November). https://doi.org/10.1016/j.still.2019.06.009.

Li, Yuan, Zhou Li, Song Cui, Guopeng Liang, and Qingping Zhang. 2021. “Microbial-Derived Carbon Components Are Critical for Enhancing Soil Organic Carbon in No-Tillage Croplands: A Global Perspective.” Soil and Tillage Research 205 (January). https://doi.org/10.1016/j.still.2020.104758.

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Li, Zhengzheng, Jiancheng Zou, Peizhou Yan, and Don Hong. 2021. “Non-Contact Real-Time Monitoring of Driver’s Physiological Parameters under Ambient Light Condition.” Intelligent Automation & Soft Computing 28 (3). https://doi.org/10.32604/iasc.2021.016516.

Li, Zhou, Xingfa Lai, Qian Yang, Xuan Yang, Song Cui, and Yuying Shen. 2018. “In Search of Long-Term Sustainable Tillage and Straw Mulching Practices for a Maize-Winter Wheat-Soybean Rotation System in the Loess Plateau of China.” Field Crops Research 217 (March). https://doi.org/10.1016/j.fcr.2017.08.021.

Li, Zhou, Xuan Yang, Song Cui, Qian Yang, Xianlong Yang, Juncheng Li, and Yuying Shen. 2018. “Developing Sustainable Cropping Systems by Integrating Crop Rotation with Conservation Tillage Practices on the Loess Plateau, a Long-Term Imperative.” Field Crops Research 222 (June). https://doi.org/10.1016/j.fcr.2018.03.027.

Li, Zhou, Qingping Zhang, Wanrong Wei, Song Cui, Wei Tang, and Yuan Li. 2020. “Determining Effects of Water and Nitrogen Inputs on Wheat Yield and Water Productivity and Nitrogen Use Efficiency in China: A Quantitative Synthesis.” Agricultural Water Management 242 (December). https://doi.org/10.1016/j.agwat.2020.106397.

Liang, Jingsai, Jiancheng Zou, and Don Hong. 2019. “Non-Gaussian Penalized PARAFAC Analysis for FMRI Data.” Frontiers in Applied Mathematics and Statistics 5 (August). https://doi.org/10.3389/fams.2019.00040.

Lischka, Alyson E., Natasha E. Gerstenschlager, D. Christopher Stephens, Jeremy F. Strayer, and Angela T. Barlow. 2018. “Making Room for Inspecting Mistakes.” The Mathematics Teacher 111 (6). https://doi.org/10.5951/mathteacher.111.6.0432.

Lischka, Alyson E., and D. Christopher Stephens. 2020. “The Area Model: Building Mathematical Connections.” Mathematics Teacher: Learning and Teaching PK-12 113 (3). https://doi.org/10.5951/MTLT.2019.0115.

Liu, Runrun, Martin Rolek, D. Christopher Stephens, Dong Ye, and Gexin Yu. 2021. “Connectivity for Kite-Linked Graphs.” SIAM Journal on Discrete Mathematics 35 (1). https://doi.org/10.1137/19M130282X.

Liu, Wenzhong, Serge Lawrencenko, Beifang Chen, M.N. Ellingham, Nora Hartsfield, Hui Yang, Dong Ye, and Xiaoya Zha. 2019. “Quadrangular Embeddings of Complete Graphs and the Even Map Color Theorem.” Journal of Combinatorial Theory, Series B 139 (November). https://doi.org/10.1016/j.jctb.2019.02.006.

Liu, Yeqian. 2019. “Data Augmentation and Bayesian Methods for Multicategory Support Vector Machines.” International Journal of Data Science and Analysis 5 (3). https://doi.org/10.11648/j.ijdsa.20190503.12.

Liu, Yeqian, and Junyu Chen. 2021. “Non-Parametric Analysis of Interval-Censored Survival Data with Application to a Phase III Metastatic Colorectal Cancer Clinical Trial.” Biomedical Statistics and Informatics 6 (1). https://doi.org/10.11648/j.bsi.20210601.13.

Liu, Yeqian, Tao Hu, and Jianguo Sun. 2020. “Regression Analysis of Interval-Censored Failure Time Data with Cured Subgroup and Mismeasured Covariates.” Communications in Statistics - Theory and Methods 49 (1). https://doi.org/10.1080/03610926.2018.1535075.

Liu, Yeqian, James Plott, and Yingxiao Huang. 2021. “Sieve Estimation for Mixture Cure Rate Model with Informatively Interval-Censored Failure Time Data.” American Journal of Theoretical and Applied Statistics 10 (3). https://doi.org/10.11648/j.ajtas.20211003.15.

Lui, Yeqian. 2020. “Extended Bayesian Framework for Multicategory Support Vector Machine.” Journal of Statistics Applications & Probability 9 (1). https://doi.org/10.18576/jsap/090101.

Lui, Yeqian, and Hanyi Li. 2021. “A Semiparametric Mixture Cure Model for Partly Interval Censored Failure Time Data.” Journal of Statistics Applications & Probability 10 (1). https://doi.org/10.18576/jsap/100101.

Luquin, Eduardo, Miguel A. Campo‐Bescós, Rafael Muñoz‐Carpena, Ronald L. Bingner, Richard M. Cruse, Henrique G. Momm, Robert R. Wells, and Javier Casalí. 2021. “Model Prediction Capacity of Ephemeral Gully Evolution in Conservation Tillage Systems.” Earth Surface Processes and Landforms 46 (10). https://doi.org/10.1002/esp.5134.

Madadian, Edris, Jan B. Haelssig, Mina Mohebbi, and Michael Pegg. 2021. “From Biorefinery Landfills towards a Sustainable Circular Bioeconomy: A Techno-Economic and Environmental Analysis in Atlantic Canada.” Journal of Cleaner Production 296 (May). https://doi.org/10.1016/j.jclepro.2021.126590.

Magal, P., G. F. Webb, and Yixiang Wu. 2019. “A Spatial Model of Honey Bee Colony Collapse Due to Pesticide Contamination of Foraging Bees.” Bulletin of Mathematical Biology 81: 4908–31.

Magal, Pierre, Glenn F. Webb, and Yixiang Wu. 2020. “Spatial Spread of Epidemic Diseases in Geographical Settings: Seasonal Influenza Epidemics in Puerto Rico.” Discrete & Continuous Dynamical Systems - B 25 (6). https://doi.org/10.3934/dcdsb.2019223.

Magal, Pierre, G. F. Webb, and Yixiang Wu. 2018. “On a Vector-Host Epidemic Model with Spatial Structure.” Nonlinearity 31 (February): 5589–5614. https://doi.org/10.1088/1361-6544/aae1e0.

Magal, Pierre, Glenn F. Webb, and Yixiang Wu. 2019. “On the Basic Reproduction Number of Reaction-Diffusion Epidemic Models.” SIAM Journal on Applied Mathematics 79 (1). https://doi.org/10.1137/18M1182243.

Malone, Eric W., Joshuah S. Perkin, Brian M. Leckie, Matthew A. Kulp, Carla R. Hurt, and Donald M. Walker. 2018. “Which Species, How Many, and from Where: Integrating Habitat Suitability, Population Genomics, and Abundance Estimates into Species Reintroduction Planning.” Global Change Biology 24 (8). https://doi.org/10.1111/gcb.14126.

Maynard, Daniel S., Mark A. Bradford, Kristofer R. Covey, Daniel Lindner, Jessie Glaeser, Douglas A. Talbert, Paul Joshua Tinker, Donald M. Walker, and Thomas W. Crowther. 2019. “Consistent Trade-Offs in Fungal Trait Expression across Broad Spatial Scales.” Nature Microbiology 4 (5). https://doi.org/10.1038/s41564-019-0361-5.

Menefee, Dorothy, Nithya Rajan, Song Cui, Muthukumar Bagavathiannan, Ronnie Schnell, and Jason West. 2020. “Carbon Exchange of a Dryland Cotton Field and Its Relationship with PlanetScope Remote Sensing Data.” Agricultural and Forest Meteorology 294 (November). https://doi.org/10.1016/j.agrformet.2020.108130.

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Miao, Fuhong, Yuan Li, Song Cui, Sindhu Jagadamma, Guofeng Yang, and Qingping Zhang. 2019. “Soil Extracellular Enzyme Activities under Long-Term Fertilization Management in the Croplands of China: A Meta-Analysis.” Nutrient Cycling in Agroecosystems 114 (2). https://doi.org/10.1007/s10705-019-09991-2.

Miao, Lei, and Dallas Leitner. 2021. “Adaptive Traffic Light Control With Quality-of-Service Provisioning for Connected and Automated Vehicles at Isolated Intersections.” IEEE Access 9. https://doi.org/10.1109/ACCESS.2021.3064310.

Minoshima, Ayaka, Donald M. Walker, Shuhei Takemoto, Tsuyoshi Hosoya, Allison K. Walker, Seiju Ishikawa, and Yuuri Hirooka. 2019. “Pathogenicity and Taxonomy of Tenuignomonia Styracis Gen. et Sp. Nov., a New Monotypic Genus of Gnomoniaceae on Styrax Obassia in Japan.” Mycoscience 60 (1). https://doi.org/10.1016/j.myc.2018.08.001.

Momm, H.G., R.L. Bingner, R.R. Wells, W.S. Porter, L. Yasarer, and S.M. Dabney. 2019. “Enhanced Field-Scale Characterization for Watershed Erosion Assessments.” Environmental Modelling & Software 117 (July). https://doi.org/10.1016/j.envsoft.2019.03.025.

Momm, H.G., W.S. Porter, L.M. Yasarer, R. ElKadiri, R.L. Bingner, and J.W. Aber. 2019. “Crop Conversion Impacts on Runoff and Sediment Loads in the Upper Sunflower River Watershed.” Agricultural Water Management 217 (May). https://doi.org/10.1016/j.agwat.2019.03.012.

Momm, Henrique, Ron Bingner, Robert Wells, Katy Moore, and Glenn Herring. 2021. “Integrated Technology for Evaluation and Assessment of Multi-Scale Hydrological Systems in Managing Nonpoint Source Pollution.” Water 13 (6). https://doi.org/10.3390/w13060842.

Momm, Henrique G., Racha ElKadiri, and Wesley Porter. 2020. “Crop-Type Classification for Long-Term Modeling: An Integrated Remote Sensing and Machine Learning Approach.” Remote Sensing 12 (3). https://doi.org/10.3390/rs12030449.

Momm, Henrique G., Robert R. Wells, and Sean J. Bennett. 2018. “Disaggregating Soil Erosion Processes within an Evolving Experimental Landscape.” Earth Surface Processes and Landforms 43 (2). https://doi.org/10.1002/esp.4268.

Momm, Henrique G., Lindsey M. W. Yasarer, Ronald L. Bingner, Robert R. Wells, and Roger A. Kunhle. 2019. “Evaluation of Sediment Load Reduction by Natural Riparian Vegetation in the Goodwin Creek Watershed.” Transactions of the ASABE 62 (5). https://doi.org/10.13031/trans.13492.

Morton, Scott P., Jonathan Howton, and Joshua L. Phillips. 2018. “Sub-Class Differences of PH-Dependent HIV GP120-CD4 Interactions.” In Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. New York, NY, USA: ACM. https://doi.org/10.1145/3233547.3233711.

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Nguyen, Daniel, Zbigniew Kisiel, and Anatoliy Volkov. 2018. “Fast Analytical Evaluation of Intermolecular Electrostatic Interaction Energies Using the Pseudoatom Representation of the Electron Density. I. The Löwdin α-Function Method.” Acta Crystallographica Section A Foundations and Advances 74 (5). https://doi.org/10.1107/S2053273318008690.

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Ogden, Matthew, Graham West, John Wallin, Zachariah Sinkala, and William Smith. 2020. “ The American Astronomical Society, Find out More     The Institute of Physics, Find out More    Optimizing Numerical Simulations of Colliding Galaxies. II. Comparing Simulations to Astronomical Observations.” Research Notes of the AAS 4 (138).

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Olson, Connor I., Gale B. Beaubien, Jaylen L. Sims, and Ryan R. Otter. 2019. “Mercury Accumulation in Millipedes (Narceus Spp.) Living Adjacent to a Southern Appalachian Mountain Stream (USA).” Bulletin of Environmental Contamination and Toxicology 103 (4). https://doi.org/10.1007/s00128-019-02664-4.

Omatu, Ngozi, and Joshua L. Phillips. 2021. “Benefits of Combining Dimensional Attention and Working Memory for Partially Observable Reinforcement Learning Problems.” In Proceedings of the 2021 ACM Southeast Conference. New York, NY, USA: ACM. https://doi.org/10.1145/3409334.3452072.

Östlin, A., Y. Zhang, H. Terletska, F. Beiuşeanu, V. Popescu, K. Byczuk, L. Vitos, M. Jarrell, D. Vollhardt, and L. Chioncel. 2020. “Ab Initio Typical Medium Theory of Substitutional Disorder.” Physical Review B 101 (1). https://doi.org/10.1103/PhysRevB.101.014210.

Otter, Ryan R., Gale B. Beaubien, Connor I. Olson, David M. Walters, and Marc A. Mills. 2020. “Practical Considerations for the Incorporation of Insect-Mediated Contaminant Flux into Ecological Risk Assessments.” In Contaminants and Ecological Subsidies. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-49480-3_9.

Paki, Joseph, Hanna Terletska, Sergei Iskakov, and Emanuel Gull. 2019. “Charge Order and Antiferromagnetism in the Extended Hubbard Model.” Physical Review B 99 (24). https://doi.org/10.1103/PhysRevB.99.245146.

Paneru, Bam, Ali Ali, Rafet Al-Tobasei, Brett Kenney, and Mohamed Salem. 2018. “Crosstalk among LncRNAs, MicroRNAs and MRNAs in the Muscle ‘Degradome’ of Rainbow Trout.” Scientific Reports 8 (1). https://doi.org/10.1038/s41598-018-26753-2.

Phillips, Joshua L., Michael E. Colvin, and Shawn Newsam. 2018. “Dimensionality Estimation of Protein Dynamics Using Polymer Models.” In Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. New York, NY, USA: ACM. https://doi.org/10.1145/3233547.3233713.

Pirtle, Todd, Lee Rumble, Michael Klug, Forbes Walker, Song Cui, and Nathan Phillips. 2019. “Impact of Biochar and Different Nitrogen Sources on Forage Radish Production in Middle Tennessee.” JOURNAL OF ADVANCES IN AGRICULTURE 10 (January). https://doi.org/10.24297/jaa.v10i0.8035.

Plummer, Michael D., Dong Ye, and Xiaoya Zha. 2020. “Dominating Maximal Outerplane Graphs and Hamiltonian Plane Triangulations.” Discrete Applied Mathematics 282 (August). https://doi.org/10.1016/j.dam.2019.12.003.

Poudel, Khem N., and William M. Robertson. 2019. “Bloch Surface Wave Excitation Using a Maximum Length Sequence Grating Structure.” In Optical Components and Materials XVI, edited by Michel J. Digonnet and Shibin Jiang. SPIE. https://doi.org/10.1117/12.2508184.

Proynov, Emil, and Jing Kong. 2021. “Correcting the Charge Delocalization Error of Density Functional Theory.” Journal of Chemical Theory and Computation 17 (8). https://doi.org/10.1021/acs.jctc.1c00197.

Qin, Chao, Robert R. Wells, Henrique G. Momm, Ximeng Xu, Glenn V. Wilson, and Fenli Zheng. 2019. “Photogrammetric Analysis Tools for Channel Widening Quantification under Laboratory Conditions.” Soil and Tillage Research 191 (August). https://doi.org/10.1016/j.still.2019.04.002.

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Reshniak, Viktor, Abdul Khaliq, and David Voss. 2019. “Slow-Scale Split-Step Tau-Leap Method for Stiff Stochastic Chemical Systems.” Journal of Computational and Applied Mathematics 361 (December). https://doi.org/10.1016/j.cam.2019.03.044.

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Robertson, William M., Isaac Shirk, and Elizabeth Campbell. 2019. “Acoustic Waveguide Impedance Matching via Helmholtz Resonator Mediated Extraordinary Acoustic Transmission.” AIP Advances 9 (3). https://doi.org/10.1063/1.5083906.

Robertson, William M., Stephen M. Wright, Andrienne Friedli, Jeffery Summers, and Alex Kaszynski. 2020. “Design and Characterization of an Ultra-Low-Cost 3D-Printed Optical Sensor Based on Bloch Surface Wave Resonance.” Biosensors and Bioelectronics: X 5 (September). https://doi.org/10.1016/j.biosx.2020.100049.

Rowe, E., W.B. Goodwin, P. Bhattacharya, G. Cooper, N. Schley, M. Groza, N.J. Cherepy, S.A. Payne, and A. Burger. 2019. “Preparation, Structure and Scintillation of Cesium Hafnium Chloride Bromide Crystals.” Journal of Crystal Growth 509 (March). https://doi.org/10.1016/j.jcrysgro.2018.08.033.

Salem, Mohamed, Rafet Al-Tobasei, Ali Ali, Daniela Lourenco, Guangtu Gao, Yniv Palti, Brett Kenney, and Timothy D. Leeds. 2018. “Genome-Wide Association Analysis With a 50K Transcribed Gene SNP-Chip Identifies QTL Affecting Muscle Yield in Rainbow Trout.” Frontiers in Genetics 9 (September). https://doi.org/10.3389/fgene.2018.00387.

Sarumi, Ibrahim O., Khaled M. Furati, and Abdul Q. M. Khaliq. 2020. “Highly Accurate Global Padé Approximations of Generalized Mittag–Leffler Function and Its Inverse.” Journal of Scientific Computing 82 (2). https://doi.org/10.1007/s10915-020-01150-y.

Schulman, Alan, and Salvador Barbosa. 2018. “Text Genre Classification Using Only Parts of Speech.” In 2018 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE. https://doi.org/10.1109/CSCI46756.2018.00236.

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Sharma, Sumit, Nithya Rajan, Song Cui, Stephen Maas, Kenneth Casey, Srinivasulu Ale, and Russel Jessup. 2019. “Carbon and Evapotranspiration Dynamics of a Non-Native Perennial Grass with Biofuel Potential in the Southern U.S. Great Plains.” Agricultural and Forest Meteorology 269–270 (May). https://doi.org/10.1016/j.agrformet.2019.01.037.

Shi, Junping, Yixiang Wu, and Xingfu Zou. 2020. “Coexistence of Competing Species for Intermediate Dispersal Rates in a Reaction–Diffusion Chemostat Model.” Journal of Dynamics and Differential Equations 32 (2). https://doi.org/10.1007/s10884-019-09763-0.

Shuttleworth, Lucas A., David I. Guest, and Donald M. Walker. 2018. “The Fungus, the Code and the Mysterious Publication Date: Why Gnomoniopsis Smithogilvyi Is Still the Correct Name for the Chestnut Rot Fungus.” IMA Fungus 9 (2). https://doi.org/10.1007/BF03449443.

Smith-Peavier, Emily, Grant E. Gardner, and Ryan Otter. 2019. “PowerPoint Use in the Undergraduate Biology Classroom: Perceptions and Impacts on Student Learning.” Journal of College Science Teaching 48 (n3): 74–83.

Snyder, Shawn D., William B. Sutton, and Donald M. Walker. 2020. “Prevalence of Ophidiomyces Ophiodiicola, the Causative Agent of Snake Fungal Disease, in the Interior Plateau Ecoregion of Tennessee, USA.” Journal of Wildlife Diseases 56 (4). https://doi.org/10.7589/2019-04-109.

Sun, Hongwei, and Qiang Wu. 2020. “Optimal Rates of Distributed Regression with Imperfect Kernels.” Journal of Machine Learning Research 22 (171): 1–34.

Sun, Yuyang, Peizhou Yan, Zhengzheng Li, Jiancheng Zou, and Don Hong. 2020. “Driver Fatigue Detection System Based on Colored and Infrared Eye Features Fusion.” Computers, Materials & Continua 63 (3). https://doi.org/10.32604/cmc.2020.09763.

Swindall, Matthew I., Gregory Croisdaile, Chase C. Hunter, Ben Keener, Alex C. Williams, James H. Brusuelas, Nita Krevens, Melissa Sellew, Lucy Fortson, and John F. Wallin. 2021. “Exploring Learning Approaches for Ancient Greek Character Recognition with Citizen Science Data.” In Exploring Learning Approaches for Ancient Greek Character Recognition with Citizen Science Data. IEEE 17th International Conference on eScience.

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Tanguay, P., M. Blais, A. Potvin, D. Stewart, D. Walker, N. Nadeau-Thibodeau, P. DesRochers, and D. Rioux. 2018. “QPCR Quantification of Ophiognomonia Clavigignenti-Juglandacearum from Infected Butternut Trees under Different Release Treatments.” Forest Pathology 48 (3). https://doi.org/10.1111/efp.12418.

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Terletska, Hanna, Yi Zhang, Ka-Ming Tam, Tom Berlijn, Liviu Chioncel, N. Vidhyadhiraja, and Mark Jarrell. 2018. “Systematic Quantum Cluster Typical Medium Method for the Study of Localization in Strongly Disordered Electronic Systems.” Applied Sciences 8 (12). https://doi.org/10.3390/app8122401.

Tong, Hongzhi, and Qiang Wu. 2020. “Moving Quantile Regression.” Journal of Statistical Planning and Inference 205 (March). https://doi.org/10.1016/j.jspi.2019.06.003.

Tzacheva, A., and R. Jaishree. 2018. “EMOTION MINING FROM STUDENT COMMENTS A LEXICON BASED APPROACH FOR PEDAGOGICAL INNOVATION ASSESSMENT.” The European Journal of Education and Applied Psychology, September. https://doi.org/10.29013/EJEAP-18-3-3-13.

Tzacheva, Angelina A., Jaishree Ranganathan, and Arunkumar Bagavathi. 2020. “Action Rules for Sentiment Analysis Using Twitter.” International Journal of Social Network Mining 3 (1). https://doi.org/10.1504/IJSNM.2020.105728.

Tzacheva, Angelina, Jaishree Ranganathan, and Rajendra Jadi. 2019. “Multi-Label Emotion Mining From Student Comments.” In Proceedings of the 2019 4th International Conference on Information and Education Innovations - ICIEI 2019. New York, New York, USA: ACM Press. https://doi.org/10.1145/3345094.3345112.

Tzacheva, Angelina, Jaishree Ranganathan, and Sai Yesawy Mylavarapu. 2020. “Actionable Pattern Discovery for Tweet Emotions.” In Advances in Intelligent Systems and Computing, 46–57. https://doi.org/10.1007/978-3-030-20454-9_5.

Varadwaj, Pradeep R., Arpita Varadwaj, Helder M. Marques, and Preston J. MacDougall. 2019. “The Chalcogen Bond: Can It Be Formed by Oxygen?” Physical Chemistry Chemical Physics 21 (36). https://doi.org/10.1039/C9CP03783G.

Walker, Donald M., Aubree J. Hill, Molly A. Albecker, Michael W. McCoy, Matthew Grisnik, Alexander Romer, Alejandro Grajal-Puche, et al. 2020. “Variation in the Slimy Salamander (Plethodon Spp.) Skin and Gut-Microbial Assemblages Is Explained by Geographic Distance and Host Affinity.” Microbial Ecology 79 (4). https://doi.org/10.1007/s00248-019-01456-x.

Walker, Donald M, Jacob E Leys, Matthew Grisnik, Alejandro Grajal-Puche, Christopher M Murray, and Matthew C Allender. 2019. “Variability in Snake Skin Microbial Assemblages across Spatial Scales and Disease States.” The ISME Journal 13 (9): 2209–22. https://doi.org/10.1038/s41396-019-0416-x.

Walker, Donald M, Christopher M Murray, Doug Talbert, Paul Tinker, Sean P Graham, and Thomas W Crowther. 2018. “A Salamander’s Top down Effect on Fungal Communities in a Detritivore Ecosystem.” FEMS Microbiology Ecology 94 (12). https://doi.org/10.1093/femsec/fiy168.

Wallerberger, Markus, Sergei Iskakov, Alexander Gaenko, Joseph Kleinhenz, Igor Krivenko, Ryan Levy, Jia Li, et al. 2018. “Updated Core Libraries of the ALPS Project,” November.

Wang, Donglin, Honglan Xu, and Qiang Wu. 2020. “Averaging versus Voting: A Comparative Study of Strategies for Distributed Classification.” Mathematical Foundations of Computing 3 (3). https://doi.org/10.3934/mfc.2020017.

Wang, Matthew, Dwayne John, Jianguo Yu, Emil Proynov, Fenglai Liu, Benjamin G. Janesko, and Jing Kong. 2019. “Performance of New Density Functionals of Nondynamic Correlation on Chemical Properties.” The Journal of Chemical Physics 150 (20). https://doi.org/10.1063/1.5082745.

Wang, Yiting, and Jing Kong. 2021. “Efficient Spherical Surface Integration of Gauss Functions in Three-Dimensional Spherical Coordinates and the Solution for the Modified Bessel Function of the First Kind.” Journal of Mathematical Chemistry 59 (2). https://doi.org/10.1007/s10910-020-01204-4.

Wang, Yiting, Emil Proynov, and Jing Kong. 2021. “Model DFT Exchange Holes and the Exact Exchange Hole: Similarities and Differences.” The Journal of Chemical Physics 154 (2). https://doi.org/10.1063/5.0031995.

Weatherly, Jessie, Piero Macchi, and Anatoliy Volkov. 2021. “On the Calculation of the Electrostatic Potential, Electric Field and Electric Field Gradient from the Aspherical Pseudoatom Model. II. Evaluation of the Properties in an Infinite Crystal.” Acta Crystallographica Section A Foundations and Advances 77 (5). https://doi.org/10.1107/S2053273321005532.

Weh, A., Y. Zhang, A. Östlin, H. Terletska, D. Bauernfeind, K.-M. Tam, H. G. Evertz, K. Byczuk, D. Vollhardt, and L. Chioncel. 2021. “Dynamical Mean-Field Theory of the Anderson-Hubbard Model with Local and Nonlocal Disorder in Tensor Formulation.” Physical Review B 104 (4). https://doi.org/10.1103/PhysRevB.104.045127.

West, Graham, Matthew Ogden, John Wallin, Zachariah Sinkala, and William Smith. 2020. “Optimizing Numerical Simulations of Colliding Galaxies. I. Fitness Functions and Optimization Algorithms.” Research Notes of the AAS 4 (136).

Williams, Arthur, and Joshua Phillips. 2020. “Transfer Reinforcement Learning Using Output-Gated Working Memory.” Proceedings of the AAAI Conference on Artificial Intelligence 34 (02). https://doi.org/10.1609/aaai.v34i02.5488.

Willingham, James C., Angela T. Barlow, D. Christopher Stephens, Alyson E. Lischka, and Kristin S. Hartland. 2021. “Mindset Regarding Mathematical Ability in K‐12 Teachers.” School Science and Mathematics 121 (4). https://doi.org/10.1111/ssm.12466.

Wu, Yezhou, Yujun Yang, and Dong Ye. 2018. “A Note on Median Eigenvalues of Bipartite Graphs.” MATCH Communications in Mathematical and in Computer Chemistry 80: 853–62.

Wu, Yezhou, and Dong Ye. 2018. “Circuit Covers of Cubic Signed Graphs.” Journal of Graph Theory 89 (1). https://doi.org/10.1002/jgt.22238.

———. 2020. “Minimum $T$-Joins and Signed-Circuit Covering.” SIAM Journal on Discrete Mathematics 34 (2). https://doi.org/10.1137/18M1226105.

Wu, Yixiang, and Xingfu Zou. 2018. “Dynamics and Profiles of a Diffusive Host–Pathogen System with Distinct Dispersal Rates.” Journal of Differential Equations 264 (8). https://doi.org/10.1016/j.jde.2017.12.027.

Xiong, Lu, and Don Hong. 2020. “Using Monte Carlo Simulation to Predict Captive Insurance Solvency.” In Proceedings of the 2020 the 4th International Conference on Compute and Data Analysis. New York, NY, USA: ACM. https://doi.org/10.1145/3388142.3388171.

Xu, Shuzhe, Salvador E. Barbosa, and Don Hong. 2020. “BERT Feature Based Model for Predicting the Helpfulness Scores of Online Customers Reviews.” In . https://doi.org/10.1007/978-3-030-39442-4_21.

Xu, Yi, and Yeqian Liu. 2021. “Bias Adjustment Methods for Analysis of a Non-Randomized Controlled Trials of Right Heart Catheterization for Patients in ICU.” Biomedical Statistics and Informatics 6 (2). https://doi.org/10.11648/j.bsi.20210602.12.

Yang, Xuan, Zhou Li, Song Cui, Quan Cao, Jianqiang Deng, Xingfa Lai, and Yuying Shen. 2020. “Cropping System Productivity and Evapotranspiration in the Semiarid Loess Plateau of China under Future Temperature and Precipitation Changes: An APSIM-Based Analysis of Rotational vs. Continuous Systems.” Agricultural Water Management 229 (February). https://doi.org/10.1016/j.agwat.2019.105959.

Yang, Xuan, Lina Zheng, Qian Yang, Zikui Wang, Song Cui, and Yuying Shen. 2018. “Modelling the Effects of Conservation Tillage on Crop Water Productivity, Soil Water Dynamics and Evapotranspiration of a Maize-Winter Wheat-Soybean Rotation System on the Loess Plateau of China Using APSIM.” Agricultural Systems 166 (October). https://doi.org/10.1016/j.agsy.2018.08.005.

Yang, Yujun, and Dong Ye. 2018. “Inverses of Bipartite Graphs.” Combinatorica 38 (5). https://doi.org/10.1007/s00493-016-3502-y.

Yasarer, Lindsey M. W., Ronald L. Bingner, and Henrique G. Momm. 2018. “Characterizing Ponds in a Watershed Simulation and Evaluating Their Influence on Streamflow in a Mississippi Watershed.” Hydrological Sciences Journal 63 (2). https://doi.org/10.1080/02626667.2018.1425954.

Ye, Dong. 2018. “Maximum Matchings in Regular Graphs.” Discrete Mathematics 341 (5). https://doi.org/10.1016/j.disc.2018.01.016.

Yeqian, Liu. 2019. “A Signal Detection Analysis of World Health Organization’s Pharmacovigilance Database.” International Journal of Clinical Biostatistics and Biometrics 5 (2). https://doi.org/10.23937/2469-5831/1510023.

Yeqian, Liu, and Yingxiao Huang. 2020. “Semiparametric Likelihood Estimation with Clayton-Oakes Model for Multivariate Current Status Data.” Journal of Biostatistics & Biometricshttps://doi.org/10.29011/JBSB-109.100009.

Zhai, Shaohui, Dalal Alrowaili, and Dong Ye. 2018. “Clar Structures vs Fries Structures in Hexagonal Systems.” Applied Mathematics and Computation 329 (July). https://doi.org/10.1016/j.amc.2018.02.014.

Zhai, Shaohui, Erling Wei, Jinghua He, and Dong Ye. 2019. “Homeomorphically Irreducible Spanning Trees in Hexangulations of Surfaces.” Discrete Mathematics 342 (10). https://doi.org/10.1016/j.disc.2019.01.032.

Zhang, Li, You Lu, Rong Luo, Dong Ye, and Shenggui Zhang. 2020. “Edge Coloring of Signed Graphs.” Discrete Applied Mathematics 282 (August). https://doi.org/10.1016/j.dam.2019.12.004.

Zhang, Ning, and Qiang Wu. 2019. “Online Learning for Supervised Dimension Reduction.” Mathematical Foundations of Computing 2 (2): 95–106. https://doi.org/10.3934/mfc.2019008.

Zhang, Ning, Zhou Yu, and Qiang Wu. 2018. “Overlapping Sliced Inverse Regression for Dimension Reduction.” Analysis and Applications 17 (5): 715–36.

Zhang, Yi, R. Nelson, K.-M. Tam, W. Ku, U. Yu, N. S. Vidhyadhiraja, H. Terletska, J. Moreno, M. Jarrell, and T. Berlijn. 2018. “Origin of Localization in Ti-Doped Si.” Physical Review B 98 (17). https://doi.org/10.1103/PhysRevB.98.174204.

Zhang, Yi, Hanna Terletska, Ka-Ming Tam, Yang Wang, Markus Eisenbach, Liviu Chioncel, and Mark Jarrell. 2019. “Locally Self-Consistent Embedding Approach for Disordered Electronic Systems.” Physical Review B 100 (5). https://doi.org/10.1103/PhysRevB.100.054205.

Zheng, Shao-Liang, Yu-Sheng Chen, Xiaoping Wang, Christina Hoffmann, and Anatoliy Volkov. 2018. “From the Source: Student-Centred Guest Lecturing in a Chemical Crystallography Class.” Journal of Applied Crystallography 51 (3). https://doi.org/10.1107/S1600576718004120.

Zheng, Xiaoqing, Hongwei Sun, and Qiang Wu. 2021. “Regularized Least Square Kernel Regression for Streaming Data.” Communications in Mathematical Sciences 19 (6). https://doi.org/10.4310/CMS.2021.v19.n6.a4.

Zou, Jiancheng, Zhengzheng Li, Zhijun Guo, and Don Hong. 2019. “Super-Resolution Reconstruction of Images Based on Microarray Camera.” Computers, Materials & Continua 60 (1). https://doi.org/10.32604/cmc.2019.05795.

Zou, Jiancheng, Na Zhu, Bailin Ge, and Don Hong. 2021. “Elderly Fall Detection Based on Improved SSD Algorithm.” Journal of New Media 3 (1). https://doi.org/10.32604/jnm.2021.017763.

 

Research Groups

The Faculty in the Computational Science Program at MTSU have a diverse set of research interests that cross between traditional departmental boundaries. The groups below outline some of the core research interests of our faculty. In some cases, faculty straddle two or more of the areas below. However, for simplicity, faculty are only associated with a single group on this page.

Bioinformatics
Joshua Phillips Asst. Prof. 615-898-2397 [email protected] Computer Science
Biological Modeling
R. Stephen Howard Professor 615-898-2044 [email protected] Biology
Wandi Ding Asst. Prof. 615-494-8936 [email protected] Mathematics
Rachel Leander Asst. Prof. 615-494-5422 [email protected] Mathematics
Computational Chemistry
Jing Kong Assoc. Professor 615-494-7623 [email protected] Chemistry
Anatoliy Volkov Assoc. Professor 615-494-8655 [email protected] Chemistry
Preston MacDougall 615-898-5265 [email protected] Chemistry
Computational Graph Theory
Suk Jai Seo Professor 615-904-8168 [email protected] Computer Science
D. Chris Stephens Chair of Mathematics and Professor 615-494-8957 [email protected] Mathematics
Dong Ye Asst. Prof. 615-494-8957 [email protected] Mathematics
Xiaoya Zha Professor 615-898-2494 [email protected] Mathematics
Computational Physics, Engineering And Differential Equations
Abdul Khaliq Professor 615-494-8889 [email protected] Mathematics
William Robertson Professor 615-898-5837 [email protected] Physics & Astronomy
Vishwas Bedekar Asst. Prof. 615-494-8741 [email protected] Engineering
High Performance Computing
Yi Gu Asst. Prof 615-904-8238 [email protected] Computer Science
Machine Learning And Remote Sensing
Cen Li Professor 615-904-8168 [email protected] Computer Science
Don Hong Professor 615-904-8339 [email protected] Mathematics
Song Cui Asst. Prof. 615-898-5833 [email protected] Agriculture
Henrique Momm Assoc. Prof. 615-904-8372 [email protected] Geosciences
John Wallin Professor & Director  615-494-7735 [email protected] Physics & Astronomy
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