CV

Education

• Ph.D. Applied Mathematics, University of Colorado, Boulder. 2025.

• B.S. Mathematics, University of Minnesota, Twin Cities. 2020.

Publications

• O. A. Malik, Y. Xu, N. Cheng, S. Becker, A. Doostan, A. Narayan. 2026.
  “Fast algorithms for monotone lower subsets of Kronecker least squares problems”.[DOI]
  Journal of Scientific Computing.

• N. Cheng and A. Doostan. 2026.
  “Langevin Bi-fidelity Importance Sampling for Failure Probability Estimation”.[DOI]
  Journal of Mechanical Design.

• N. Cheng, A. Doostan, S. Becker. 2025.
  “Stochastic Subspace Descent Accelerated via Bi-fidelity Line Search”.[OpenReview]
  Transactions on Machine Learning Research.

• N. Cheng, L. Papenmeier, S. Becker, L. Nardi. 2025.
  “A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization”.[OpenReview]
  ICML 2025 Oral.

• L. Papenmeier, N. Cheng, S. Becker, L. Nardi. 2025.
  “Explore Explorations in Bayesian Optimization”.[OpenReview]
  UAI 2025.

• N. Cheng, O. A. Malik, Y. Xu, S. Becker, A. Doostan, A. Narayan. 2024.
  “Subsampling of parametric models with bi-fidelity boosting”.[DOI]
  SIAM/ASA Journal on Uncertainty Quantification.

• N. Cheng, O. A. Malik, S. De, S. Becker, A. Doostan. 2024.
  “Bi-fidelity variational auto-encoder for uncertainty quantification”.[DOI]
  Computer Methods in Applied Mechanics and Engineering.

• J. H. Kim, et al. 2024.
  “Hemangiosarcoma cells promote conserved host-derived hematopoietic expansion”.[DOI]
  Cancer research communications.

• N. Cheng, A. J. Schulte, F. Santosa, J. H. Kim. 2021.
  “Machine learning application identifies novel gene signatures from transcriptomic data of spontaneous canine hemangiosarcoma”.[DOI]
  Briefings in Bioinformatics.

• J. H. Kim, et al. 2021.
  “Genomically complex human angiosarcoma and canine hemangiosarcoma establish convergent angiogenic transcriptional programs driven by novel gene fusions”.[DOI]
  Molecular Cancer Research.

Presentations

• Google TPU and JAX Coding. Northeast University Guest Talk, Seattle, WA. 2025 Oct.
• Bi-fidelity Variational Auto-encoder. SIAM CSE 2025 Symposium talk, Fort Worth, TX. 2025 Mar.
• Stochastic Subspace Descent with Surrogate-adjusted Line Search. MORe2024, La Jolla, CA. 2024 Sep
• Variational Auto-encoder for Uncertainty Quantification. ASEN 6412 Guest Talk, Boulder, CO. 2024 Apr.
• Multi-fidelity Methods for Uncertainty Quantification. Comprehensive exam, Boulder, CO. 2023 Nov.
• Bi-fidelity Boosting Method. Invited talk, remote. 2023 Oct.
• Robust Explainable AI for Images. Internship presentation, Houston, TX. 2023 Aug.
• Bi-fidelity Variational Auto-encoder. USNCCM17 Symposium talk, Albuquerque, NM. 2023 Jul.

Teaching

• 2021 Spring (CU Boulder): Introduction to Differential Equations with Linear Algebra, Teaching Assistant
• 2020 Fall (CU Boulder): Calculus 1 for Engineers, Teaching Assistant
• 2019 Fall (UMN): Pre-Calculus I, Teaching Assistant

Review Service

• UAI
• ICML
• AISTATS
• NeurIPS
• ICLR
• CIKM
• Briefings in Bioinformatics
• Journal of Computational Physics
• Technometrics