A. Hamaker, E. Leistenschneider, R. Jain, G. Bollen, S. A. Giuliani, K. Lund, W. Nazarewicz, L. Neufcourt, C. R. Nicoloff, D. Puentes, R. Ringle, C. S. Sumithrarachchi & I. T. Yandow (2021). "Precision mass measurement of lightweight self-conjugate nucleus 80Zr." Nature Physics. [journal] [arxiv]
CV
Professional experience
| 2019 - 2020 | Research Assistant Professor | |
| Michigan State University, Department of Statistics & Probability and FRIB | East Lansing | |
| 2017 - 2019 | Research Associate | |
| Michigan State University, Department of Statistics & Probability and FRIB | East Lansing | |
| 2013 - 2017 | Teaching Assistant | |
| Columbia University, Department of Statistics | New York |
Education
- Columbia University, Ph.D in Statistics (2017), M.A. in Statistics (2014)
- École Polytechnique, M.Sc. (2014), Ingénieur (2013), B.Sc. (2011)
- Lycée Sainte Geneviève, 2008-2010
Publications
V. Kejzlar, L. N., W. Nazarewicz & P.-G. Reinhard (2020). "Statistical aspects of nuclear mass models." J. Phys. G. [journal] [arxiv]
L. N., Y. Cao, S.A. Giuliani, W. Nazarewicz, Erik Olsen & O.B. Tarasov (2020). "Quantified limits of the nuclear landscape." Phys. Rev. C 101(3), 044307. [journal] [arxiv]
L. N., Y. Cao, S.A. Giuliani, W. Nazarewicz, E. Olsen & O.B. Tarasov (2020). "Beyond the proton drip line: Bayesian analysis of proton-emitting nuclei." Phys. Rev. C 101(1), 014319. [journal] [arxiv]
J. Arnetz, L.N., S. Sudan, T. Maiti, B. Arnetz & F. Viens (2020). "Nurse-reported bullying is associated with documented adverse patient events: an exploratory study in a U.S. hospital." J. Nurs. Care Qual. 35(3). [journal]
Y. Hao & L. N. (2019). "Application of Bayesian inference in accelerator commissioning of FRIB." Proceedings of the 10th Int. Particle Accelerator Conf. [journal]
Y. Hao, Y. Li, M. Balcewicz, L. N. & W. Cheng (2019). "Application of Bayesian inference in accelerator commissioning of FRIB." Preprint. [arxiv]
G. King, A. Lovell, L. N. & F. Nunes (2019). "Direct comparison between Bayesian and frequentist uncertainty quantification for nuclear reactions." Phys. Rev. Lett. 122(23), 232502. [journal] [arxiv]
V. Kejzlar, L. N., T. Maiti & F. Viens (2019). "Bayesian mixing of computer models: a nuclear physics perspective." Preprint. [arxiv]
L. N. & P. Protter (2019). "Expansion of a filtration with a stochastic process: the information drift." Preprint. [arxiv]
L. N., Y. Cao, W. Nazarewicz, E. Olsen & F. Viens (2019). "Neutron dripline in the Ca region from Bayesian model averaging." Phys. Rev. Lett. 122(6), 062502. [journal] [arxiv]
L. N., Y. Cao, W. Nazarewicz & F. Viens (2018). "Bayesian approach to model-based extrapolation of nuclear observables." Phys. Rev. C 98(3), 034318. [journal] [arxiv]
L. N. (2017). "Expansion of a filtration with a stochastic process: a high-frequency trading perspective." PhD Thesis, Columbia University. [journal]
G. Guo, A. Jacquier, C. Martini & L. N. (2016). "Generalized arbitrage free SVI volatility surfaces." SIAM J. Finan. Math. 7(1). [journal] [arxiv]
L. N. & F. Viens. (2016). "A third-moment theorem and precise asymptotics for variations of stationary Gaussian sequences." ALEA, Lat. Am. J. Probab. Math. Stat. 13(1). [journal] [arxiv]