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Scholarly Publications Facilitated by Boise State Research Computing Resources

The following lists scholarly publications, dissertations, and theses facilitated by Boise State Research Computing services. NOTE: This list is always incomplete and out of date. Click here for instructions on how to acknowledge use of Boise State Research Computing resources and/or personnel in publications.

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  1. Bendixsen DP, Collet J, Østman B, Hayden EJ, “Genotype network intersections promote evolutionary innovation,” PLOS Biology 17(5):e3000300, 2019.


  1. Thiago H. da Silva, Eric B. Nelson†, Izaak Williamson, Corey M. Efaw, Erik Sapper, Michael F. Hurley, Lan Li*, “First-Principles Surface Interaction Studies of Aluminum-Copper and Aluminum-Copper-Magnesium Secondary Phases in Aluminum Alloys,” Applied Surface Science, accepted, 2018.
  2. Eddie C. Davis, Michelle Mills Strout, and Catherine Olschanowsky (Boise State University, USA; University of Arizona, USA) Transforming Loop Chains via Macro Dataflow Graphs. 2018 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), February 24–28, 2018, Vienna, Austria.
  3. Michael D. Ekstrand. 2018. The LKPY Package for Recommender Systems Experiments: Next-Generation Tools and Lessons Learned from the LensKit Project. Computer Science Faculty Publications and Presentations 147. Boise State University. Presented at the REVEAL 2018 Workshop on Offline Evaluation for Recommender Systems, a workshop at RecSys 2018. DOI 10.18122/cs_facpubs/147/boisestate. arXiv:1809.03125 [cs.IR].
  4. Michael D. Ekstrand, Mucun Tian, Mohammed R. Imran Kazi, Hoda Mehrpouyan, and Daniel Kluver. 2018. Exploring Author Gender in Book Rating and Recommendation. In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys ’18). ACM. DOI 10.1145/3240323.3240373. arXiv:1808.07586v1 [cs.IR]
  5. Michael D. Ekstrand, Mucun Tian, Ion Madrazo Azpiazu, Jennifer D. Ekstrand, Oghenemaro Anuyah, David McNeill, and Maria Soledad Pera. 2018. All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency (FAT* 2018). pmlr, Proceedings of Machine Learning Research 81:172–186.
  6. Miller, E.D.; Jones, M.L.; Henry, M.M.; Chery, P.; Miller, K.; Jankowski, E. Optimization and Validation of Efficient Models for Predicting Polythiophene Self-Assembly. Polymers 2018, 10, 1305.
  7. Mucun Tian and Michael D. Ekstrand. 2018. Monte Carlo Estimates of Evaluation Metric Error and Bias. Computer Science Faculty Publications and Presentations 148. Boise State University. Presented at the REVEAL 2018 Workshop on Offline Evaluation for Recommender Systems, a workshop at RecSys 2018. DOI 10.18122/cs_facpubs/148/boisestate. NSF PAR 10074452.
  8. Thomas, Stephen, “New Methods for Understanding and Controlling the Self-Assembly of Reacting Systems Using Coarse-Grained Molecular Dynamics” (2018). Boise State University Theses and Dissertations. 1448.10.18122/td/1448/boisestate
  9. Bendixsen, Devin P, “EMPIRICAL INVESTIGATIONS OF RNA FITNESS LANDSCAPES: Harnessing the power of high-throughput sequencing and evolutionary simulations,” Boise State University Theses and Dissertations, 2018.


  1. Michael D. Ekstrand and Maria Soledad Pera. 2017. The Demographics of Cool: Popularity and Recommender Performance for Different Groups of Users. In RecSys 2017 Poster Proceedings. CEUR, Workshop Proceedings 1905.
  2. S. C, Pandey, X. Xu, I. Williamson, E. B. Nelson, L. Li, “Electronic and vibrational properties of transition metal-oxides: Comparison of GGA, GGA+U, and hybrid approaches,” Chemical Physics Letters, 669, 1-8, 2017.
  3. K. Tolman, R. Ubic, B. Liu, I. Williamson, K. Bedke, E.B. Nelson, L. Li, and X.M. Chen, “Empirical Evidence for A-site Order in Perovskites,” Journal of the American Ceramic Society, 100, 429-442, 2017.
  4. I. Williamson, S. Li, A. C. Hernandez, M. Lawson, Y. Chen, L. Li, “Structural, electrical, phonon, and optical properties of Ti- and V-doped two-dimensional MoS2,” Chemical Physics Letters, 674, 157-163, 2017.
  5. W. Wong-Ng, G. Liu, I. Levin, I. Williamson, A. Correa Hernandez, J.A. Kaduk, L. Li, “Crystallographic studies of Ba12Nb8-xTaxCo4O36 (x=1,3,4,5,7),” Solid State Sciences, 71, 3-7, 2017.


  1. Pauli, B.P., Spaul, R.J. and J.A. Heath. 2016. Forecasting disturbance effects on wildlife: tolerance does not mitigate effects of increased recreation on wildlands. Animal Conservation 20:251–260. DOI: 10.1111/acv.12308
  2. I. Williamson, A. Correa Hernandez, W. Wong-Ng, and L. Li, “High-throughput computational screening of electrical and phonon properties of two-dimensional transition metal dichalcogenides,” TMS JOM, 68, 2666-2672, 2016.
  3. I. Williamson, L. J.-Y. Her, X. Su, Y. Yan, W. Wong-Ng, L. Li, “Improved thermoelectric performance of (Fe,Co)Sb3-type skutterudites from first-principles,” Journal of Applied Physics 119, 055101 (8pp), 2016.
  4. W Wong-Ng, G Liu, I Levin, I Williamson, P Ackerman, KR Talley, J Martin, K AlHamdan, W Badegaish, JA Kaduk, L Li, “X-ray diffraction and density functional theory studies of R (Fe0.5Co0.5) O3 (R= Pr, Nd, Sm, Eu, Gd)”, Power Diffraction 31, 259-266, 2016.


  1. Williamson, E. B. Nelson, and L. Li, “Carbon dioxide sorption in a nanoporous octahedral molecular sieve,” Journal of Physics D: Applied Physics 48, 335304 (7pp), 2015.
  2. Wong-Ng, J.A. Kaduk, D. L. Siderius, A. L. Allen, L. Espinal, B. M. Boyerinas, I. Levin, M.R. Suchomel, J. Ilavsky, L. Li, I. Williamson, E. Cockayne, and H. Wu, “Reference Diffraction Patterns, Microstructure, and Pore Size Distribution for the Copper (II) benzene-1,3,5-tricarboxylate Metal Organic Framework (Cu-BTC) Compounds”, Powder Diffraction 30, 2-13, 2015.


  1. L Li, E. Cockayne, I. Williamson, L. Espinal, and W. Wong-Ng, “First-Principles Studies of Carbon Dioxide Adsorption in Cryptomelane/Hollandite-Type Manganese Dioxide”, Chemical Physics Letters, 580, 120-125, 2013.