Higgs A.L., White S.L., Madsen J.A., Kazyak D.C., Fox D.A., Pendleton R.M., Bonemery A., Smolinski T.G., Simmonds A., and Sullivan P.J., "Combining acoustic telemetry and side-scan sonar to estimate abundance of endangered shortnose sturgeon in the Hudson River, New York," Canadian Journal of Fisheries and Aquatic Sciences 82:1–12, 2025.
Smolinski T.G., "A Proposal for a Model Indigenous Intellectual Property Protection Tribal Code (MIIPPTC)," Tribal Law Journal 22, 2023.
Kerr C.C., Dura-Bernal S., Smolinski T.G., Chadderdon G.L., and Wilson D.P., "Optimization by Adaptive Stochastic Descent," PLoS ONE, 13(3):e0192944, 2018.
Fox D.M., Tseng Ha, Smolinski T.G., Rotstein H.G., and Nadim F., "Mechanisms of generation of membrane potential resonance in a neuron with multiple resonant ionic currents," PLoS Computational Biology, 13(6):e1005565, 2017.
Harrington M.A., Lloyd A., Smolinski T.G., and Shahin M., "Closing the Gap: First Year Success in College Mathematics at an HBCU," Journal of the Scholarship of Teaching and Learning 16(5), pp. 92--106, 2016.
Ayyappan V., Kalavacharla V., Thimmapuram J., Bhide K.P., Sripathi V.R., Smolinski T.G., Manoharan M., Thurston Y., Todd A., and Kingham B., "Genome-Wide Profiling of Histone Modifications (H3K9me2 and H4K12ac) and Gene Expression in Rust (Uromyces appendiculatus) Inoculated Common Bean (Phaseolus vulgaris L.)" PLoS ONE 10(7): e0132176, 2015.
Smolinski T.G., Lombardo J., and Harrington M.A., "Analyzing Adaptive Modulation in Spinal Motor Neurons using Multiobjective Evolutionary Algorithms [abstract]," BMC Neuroscience 2015, 16(Suppl 1):P94, 2015.
Malik A., Prinz A.A., and Smolinski T.G., "A system for Automated Analysis of Conductance Correlations Involved in Recovery of Electrical Activity After Neuromodulator Deprivation in Stomatogastric Neuron Models [abstract]," BMC Neuroscience, 15(Suppl 1):P41, 2014.
Smolinski T.G., Newell T., McDaniel S., and Pokrajac D., "Detection of unusual trajectories using multi-objective evolutionary algorithms and rough sets ," Proc. of SPIE Vol. 8857 (Signal and Data Processing of Small Targets):88570F, 2013.
Malik A., Shim K., Prinz A.A., and Smolinski T.G., "Multi-objective evolutionary algorithms for analysis of conductance correlations involved in recovery of bursting after neuromodulator deprivation in lobster stomatogastric neuron models [abstract]," BMC Neuroscience 14(Suppl 1):P370, 2013.
Patel P., Johnson-Gray M., Forren E., Malik A., and Smolinski T.G., "Hybridization of multi-objective evolutionary algorithms and fuzzy control for automated construction, tuning, and analysis of neuronal models [abstract]," BMC Neuroscience 14(Suppl 1):P369, 2013.
Forren E., Johnson-Gray M., Patel P., and Smolinski T.G., "NeRvolver: a computational intelligence-based system for automated construction, tuning, and analysis of neuronal models [abstract]," BMC Neuroscience 13(Suppl 1):P36, 2012.
Shim K., Prinz A.A., and Smolinski T.G., "Analyzing conductance correlations involved in recovery of bursting after neuromodulator deprivation in lobster stomatogastric neuron [abstract]," BMC Neuroscience 13(Suppl 1):P37, 2012.
McKee L., Prinz A.A., and Smolinski T.G., "Improving visualization and analysis of relationships between neuronal model parameters in discrete parameter spaces [abstract]," BMC Neuroscience 12(Suppl 1):P309, 2011.
Smolinski T.G., "Computer Literacy for Life Sciences: Helping the Digital-Era Biology Undergraduates Face Today's Research,"
CBE--Life Sciences Education, 9(3), pp. 357--363, 2010.
Smolinski T.G. and Prinz A.A., "Classifying functional and non-functional model neurons using the theory of rough sets [abstract],"
BMC Neuroscience 11(Suppl 1):P157, 2010.
Smolinski T.G. and Prinz A.A., "Rough Sets for Solving Classification Problems in Computational Neuroscience,"
Proc. of the 7th International Conference on Rough Sets and Current Trends in Computing (RSCTC 2010), Warsaw, Poland, June 2010,
Lecture Notes in Artificial Intelligence 6086, pp. 620--629.
Smolinski T.G. and Prinz A.A.,
"Multi-Objective Evolutionary Algorithms for Model Neuron Parameter Value Selection Matching Biological Behavior Under Different Simulation Scenarios [abstract],"
BMC Neuroscience 10(Suppl 1):P260, 2009.
Smolinski T.G. and Prinz A.A.,
"Computational Intelligence in Modeling of Biological Neurons: A Case Study of an Invertebrate Pacemaker Neuron,"
Proc. of the International Joint Conference on Neural Networks (IJCNN 2009), Atlanta, Georgia, June 2009, pp. 2964--2970.
Smolinski T.G., Soto-Treviño C., Rabbah P., Nadim F., and Prinz A.A.,
"Systematic Selection of Model Parameter Values Matching Biological Behavior Under Different Simulation Scenarios [abstract],"
BMC Neuroscience 9(Suppl 1):P53, 2008.
Smolinski T.G., Soto-Treviño C., Rabbah P., Nadim F., and Prinz A.A.,
"Systematic Computational Exploration of the Parameter Space of the Multi-Compartment Model of the Lobster Pyloric Pacemaker Kernel Suggests that
the Kernel Can Achieve Functional Activity Under Various Parameter Configurations [abstract],"
BMC Neuroscience 8(Suppl 2):P164, 2007.
Smolinski T.G., Buchanan R., Boratyn G.M., Milanova M.G., and Prinz A.A.,
"Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials,"
BMC Bioinformatics 7(Suppl 2):S8, 2006.
Smolinski T.G., Soto-Treviño C., Rabbah P., Nadim F., and Prinz A.A.,
"Analysis of Biological Neurons via Modeling and Rule Mining,"
International Journal of Information Technology and Intelligent Computing 1(2), pp. 293--302, 2006.
Smolinski T.G., Boratyn G.M., Milanova M.G., Buchanan R., and Prinz A.A.,
"Hybridization of Independent Component Analysis, Rough Sets, and Multi-Objective Evolutionary Algorithms for Classificatory Decomposition of Cortical Evoked Potentials,"
Proc. of the 2006 Workshop on Pattern Recognition in Bioinformatics 2006 (PRIB 2006), Hong Kong, China, August 2006,
Lecture Notes in Bioinformatics 4146, pp. 174--183.
Smolinski T.G., Milanova M.G., Boratyn G.M., Buchanan R., and Prinz A.A.,
"Multi-Objective Evolutionary Algorithms and Rough Sets for Decomposition and Analysis of Cortical Evoked Potentials,"
Proc. of the IEEE International Conference on Granular Computing (GrC 2006), Atlanta, Georgia, May 2006, pp. 635--638.
Smolinski T.G., Chenoweth D.L., and Zurada J.M.,
"Application of Rough Sets and Neural Networks to Forecasting University Facility and Administrative Cost Recovery,"
Proc. of the 7th International Conference on Artificial Intelligence and Soft Computing (ICAISC 2004), Zakopane, Poland, June 2004,
Lecture Notes in Artificial Intelligence 3070, pp. 538--543.
Boratyn G.M., Smolinski T.G., Zurada J.M., Milanova M.G., Bhattacharyya S., and Suva L.J.,
"Hybridization of Blind Source Separation and Rough Sets for Proteomic Biomarker Identification,"
Proc. of the 7th International Conference on Artificial Intelligence and Soft Computing (ICAISC 2004), Zakopane, Poland, June 2004,
Lecture Notes in Artificial Intelligence 3070, pp. 486--491.
Boratyn G.M., Smolinski T.G., Milanova M.G., Zurada J.M., Bhattacharyya S., and Suva L.J.,
"Bayesian Approach to Analysis of Protein Patterns for Identification of Myeloma Cancer,"
Proc. of the 2nd International Conference on Machine Learning and Cybernetics (ICMLC 2003), Xi'an, China, November 2003, pp. 1217--1121.
Boratyn G.M., Smolinski T.G., Milanova M.G., Zurada J.M., Bhattacharyya S., and Suva L.J.,
"Scoring-based Analysis of Protein Patterns for Identification of Myeloma Cancer,"
Proc. of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS 2003), Las Vegas, Nevada, June 2003, pp. 60--65.
Smolinski T.G., Chenoweth D.L., and Zurada J.M.,
"Time Series Prediction Using Rough Sets and Neural Networks Hybrid Approach,"
Proc. of the IASTED International Conference on Neural Networks and Computational Intelligence (NCI 2003),
The International Association of Science and Technology for Development, Cancun, Mexico, May 2003, pp. 108--111.
Boratyn G.M., Smolinski T.G., Milanova M.G., and Wróbel A.,
"Sparse Coding and Rough Set Theory-based Hybrid Approach to the Classificatory Decomposition of Cortical Evoked Potentials,"
Proc. of the 9th International Conference on Neural Information Processing (ICONIP 2002), Singapore, November 2002, pp. 2264--2268.
Smolinski T.G., Boratyn G.M., Milanova M.G., Zurada J.M., and Wróbel A.,
"Evolutionary Algorithms and Rough Sets-based Hybrid Approach to Classificatory Decomposition of Cortical Evoked Potentials,"
Proc. of the 3rd International Conference on Rough Sets and Current Trends in Computing (RSCTC 2002), Malvern, Pennsylvania, October 2002,
Lecture Notes in Artificial Intelligence 2475, pp. 621--628.
Milanova M.G., Smolinski T.G., Boratyn G.M., Zurada J.M., and Wróbel A.,
"Sparse Correlation Kernel Analysis and Evolutionary Algorithm-based Modeling of the Sensory Activity within the Rat’s Barrel Cortex,"
Proc. of the International Workshop on Pattern Recognition with Support Vector Machines (SVM 2002), Niagara Falls, Canada, August 2002,
Lecture Notes in Computer Science 2388, pp. 198--212.
Min H., Smolinski T.G., and Boratyn G.M.,
"A Genetic Algorithm-based Data Mining Approach to Profiling the Adopters and Non-Adopters of E-Purchasing,"
Proc. of the 3rd International Conference on Information Reuse and Integration (IRI 2001),
The International Society for Computers and their Applications, Las Vegas, Nevada, November 2001, pp. 1--6.
Odya P. and Smolinski T.,
"Investigation of the Influence of Video Context on Perception of Surround Sound Using Genetic Algorithms [in Polish],"
Proc. of the 9th International Symposium on Sound Engineering and Tonmeistering (ISSET 2001),
Fryderyk Chopin Academy of Music in Warsaw, Poland, October 2001, pp. 204--209.
Czyżewski A., Kostek B., Odya P., Smolinski T., and Tchórzewski T.,
"Discovering the Influence of Visual Stimuli on the Perception of Surround Sound Using Genetic Algorithms,"
Proc. of the AES 19th International Conference on Surround Sound - Techniques, Technology, and Perception,
Schloss Elmau, Germany, June 2001, pp. 287--294.
Odya P., Czyżewski A., Kostek B., and Smolinski T.,
"Determining the Influence of Visual Stimuli on the Perception of Surround Sound Using Data Mining Algorithms [abstract],"
The Journal of the Acoustical Society of America, Vol. 110, No. 5, p. 2679.
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