Yanyan He

Previous Scheduled Teaching

Published Intellectual Contributions

Conference Proceeding

• Upadhyay, K., Dantu, R., He, Y., Badruddoja, S., Salulu, A. (2022). Auditing Metaverse Requires Multimodal Deep Learning. Atlanta, GA, 2022 IEEE 4th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA).
• Salau, A., Dantu, R., Morozov, K., Badruddoja, S., Upadhayay, K. (2022). Making Blockchain Validators Honest. 267-273. San Antanio, Texas, 2022 Fourth International Conference on Blockchain Computing and Applications (BCCA).
• Badruddoja, S., Dantu, R., He, Y., Thompson, M., Salau, A., Upadyaya, K. (2022). Making Smart Contracts Predict and Scale. 127-134. San Antanio, Texas, 2022 Fourth International Conference on Blockchain Computing and Applications (BCCA).
• Badruddoja, S., Dantu, R., He, Y., Salau, A., Upadyaya, K. (2022). Scalable Smart Contracts for Linear Regression Algorithm. 19-31. 2022 International Conference on Blockchain Technology and Emerging Applications.
• Badruddoja, S., Dantu, R., He, Y., Thompson, M., Salau, A., Upadyaya, K. (2022). Smarter Contracts to Predict using Deep-Learning Algorithms. 280-288. San Antanio, Texas, 2022 Fourth International Conference on Blockchain Computing and Applications (BCCA).
• Badruddoja, S., Dantu, R., He, Y., Thompson, M., Salau, A., Upadyaya, K. (2022). Trusted AI with Blockchain to Empower Metaverse. 237-244. San Antanio, Texas, 2022 Fourth International Conference on Blockchain Computing and Applications (BCCA).
• Upadhyaya, K., Dantu, R., He, Y., Badruddoja, S., Salau, A. (2021). Can't Understand SLAs? Use the Smart Contract. New York, 2021 Third IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA).
• Upadhyay, K., Dantu, R., He, Y., Salulu, A., Badruddoja, S. (2021). Make Consumers Happy by Defuzzifying the Service Level Agreements,. New York, 2021 Third IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA).
• Upadhyaya, K., Dantu, R., He, Y., Badruddoja, S., Salau, A. (2021). Paradigm Shift from Paper Contracts to Smart Contracts,. New York, 2021 Third IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA).
• Badruddoja, S., Dantu, R., He, Y., Upadhyay, K., Thompson, M.A. (2021). Making Smart Contracts Smarter. 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC).
• He, Y., Hussaini, M.Y. (2020). Constructing Belief Functions Using the Principle of Minimum Uncertainty. 6. Virtual, IEEE FUZZY, July 19-24, 2020.
• Mirzargar, M., He, Y., Kirby, R.M. (2015). Application of uncertainty modeling frameworks to uncertain isosurface extraction. 336-349. Cham, Springer.
• He, Y., Hussaini, M.Y. (2014). An optimal unified combination rule. 39-48. Cham, Springer.

Journal Article

• He, Y., Battista, N., Waldrop, L. Mixed Uncertainty Analysis on Pumping by Peristaltic Hearts using Dempster-Shafer Theory. Journal of Mathematical Biology.
• He, Y., Hussaini, Y. (2023). Mixed Aleatory and Epistemic Uncertainty Propagation using Dempster-Shafer Theory. Journal of Computational and Applied Mathematics. 429 115234. Journal of Computational and Applied Mathematics.
• Chilleri, J., He, Y., Bedrov, D., Kirby, R.M. (2021). Optimal allocation of computational resources based on Gaussian process: Application to molecular dynamics simulations. Computational Materials Science. 188 110178. Elsevier.
• He, Y., Chilleri, J., O'Leary, S.K., Shur, M.S., Kirby, R.M. (2020). Sensitivity analysis for an electron transport system: application to the case of wurtzite gallium nitride. Journal of Computational Electronics. 19 103-110. https://doi.org/10.1007/s10825-019-01424-1
• Waldrop, L.D., He, Y., Hedrick, T.L., Rader, J.A. (2020). Functional Morphology of Gliding Flight I: Modeling Reveals Distinct Performance Landscapes Based on Soaring Strategies. Integrative and Comparative Biology. 60 (5) 1283-1296. https://api.elsevier.com/content/abstract/scopus_id/85096814648
• Rader, J.A., Hedrick, T.L., He, Y., Waldrop, L.D. (2020). Functional Morphology of Gliding Flight II. Morphology Follows Predictions of Gliding Performance. Integrative and Comparative Biology. 60 (5) 1297-1308. https://api.elsevier.com/content/abstract/scopus_id/85096814520
• Waldrop, L.D., He, Y., Battista, N.A., Neary Peterman, T., Miller, L.A. (2020). Uncertainty quantification reveals the physical constraints on pumping by peristaltic hearts.. Other. 17 (170) 20200232.
• Razi, M., Wang, R., He, Y., Kirby, R.M., Dal Negro, Luca. (2019). Optimization of Large-Scale Vogel Spiral Arrays of Plasmonic Nanoparticles. Plasmonics. 14 (1) 253-261.
• Waldrop, L.D., He, Y., Khatri, S. (2018). What Can Computational Modeling Tell Us about the Diversity of Odor-Capture Structures in the Pancrustacea?. Other. 44 (12) 1084-1100.
• Bhaduri, A., He, Y., Shields, M.D., Graham-Brady, L., Kirby, R.M. (2018). Stochastic collocation approach with adaptive mesh refinement for parametric uncertainty analysis. Journal of Computational Physics. 371 732-750. https://api.elsevier.com/content/abstract/scopus_id/85044111499
• He, Y., Razi, M., Forestiere, C., Dal Negro, L., Kirby, R.M. (2018). Uncertainty quantification guided robust design for nanoparticles’ morphology. Computer Methods in Applied Mechanics and Engineering. 336 578-593. https://api.elsevier.com/content/abstract/scopus_id/85056362031
• Forestiere, C., He, Y., Wang, R., Kirby, R.M., Dal Negro, Luca. (2016). Inverse Design of Metal Nanoparticles' Morphology. Other. 3 (1) 68-78.
• He, Y., Xiu, D. (2016). Numerical strategy for model correction using physical constraints. Journal of Computational Physics. 313 617-634.
• He, Y., Hussaini, M.Y., Gong, Y.U., Xiao, Y. (2016). Optimal unified combination rule in application of Dempster-Shafer theory to lung cancer radiotherapy dose response outcome analysis.. Other. 17 (1) 4-11.
• Chen, X., He, Y., Xiu, D. (2015). AN EFFICIENT METHOD FOR UNCERTAINTY PROPAGATION USING FUZZY SETS. SIAM Journal on Scientific Computing. 37 (6) A2488-A2507.
• He, Y., Mirzargar, M., Hudson, S., Kirby, R.M., Whitaker, R.T. (2015). AN UNCERTAINTY VISUALIZATION TECHNIQUE USING POSSIBILITY THEORY: POSSIBILISTIC MARCHING CUBES. Other. 5 (5) 433-451.
• Wang, C., Qiu, Z., He, Y. (2015). Fuzzy interval perturbation method for uncertain heat conduction problem with interval and fuzzy parameters. International Journal for Numerical Methods in Engineering. 104 (5) 330-346.
• Wang, C., Qiu, Z., He, Y. (2015). Fuzzy stochastic finite element method for the hybrid uncertain temperature field prediction. International Journal of Heat and Mass Transfer. 91 512-519.
• He, Y., Mirzargar, M., Kirby, R.M. (2015). Mixed aleatory and epistemic uncertainty quantification using fuzzy set theory. Other. 66 1-15.
• He, Y., Hussaini, M.Y., Ma, J., Shafei, B., Steidl, G. (2012). A new fuzzy c-means method with total variation regularization for segmentation of images with noisy and incomplete data. Pattern Recognition. 45 (9) 3463-3471.
• Chen, W., Cui, Y., He, Y., Yu, Y., Galvin, J., Hussaini, M.Y., Xiao, Y. (2012). Application of Dempster-Shafer theory in dose response outcome analysis. 57 (17) 5575.

Reprinted Article

• Hebdon, N., He, Y., Waldrop, L. Getting the best performance out of functional performance landscapes. Authorea.

Contracts, Grants and Sponsored Research

Grant - Research

• He, Y. (Principal), Cain, J. (Co-Principal), "Collaborative Research: Using uncertainty quantification and validated computational models to analyze pumping performance of valveless, tubular hearts," sponsored by National Science Foundation, Federal, $249453 Funded. (2022 - 2025).
• He, Y. (Principal), Waldrop, L. (Co-Principal), "Using uncertainty quantification and machine learning techniques to study the evolution of odor capture.," sponsored by Army Research Office, Federal, $247995 Funded. (2022 - 2025).
• Waldrop, L. (Principal), He, Y. (Co-Principal), "Investigation of the role of head morphology on odor detection using computational modeling," sponsored by Office of Naval Research, Federal, $474679 Funded. (2021 - 2024).
• He, Y. (Principal), "Material Design under Uncertainty (Funded to UNT)," sponsored by Army Research Laboratory, Federal, $59727 Funded. (2020 - 2020).
• He, Y. (Principal), "Material Design Under Uncertainty (Funded to New Mexico Tech)," sponsored by Army Research Laboratory, Federal, $276111 Funded. (2016 - 2020).
• He, Y. (Principal), "ALLIANCE FOR MULTISCALE MODELING OF ELECTRONIC MATERIALS," sponsored by The University of Utah, NFP, Funded. (2020 - 2020).
• He, Y. (Principal), "Material Design under Uncertainty (Funded to UNT)," sponsored by Army Research Laboratory, Federal, Funded. (2020 - 2020).
• He, Y. (Principal), "Material Design Under Uncertainty (Funded to New Mexico Tech)," sponsored by Army Research Laboratory, Federal, Funded. (2016 - 2020).