CV
Computational applied mathematician working on coastal flooding, storm surge, and geophysical hazards, with expertise in finite-volume methods, adaptive mesh refinement (AMR), uncertainty quantification, and high-performance scientific computing.
- Now: Scientist IV, NSF NCAR
- Location: Brooklyn, NY
- PhD: Applied Mathematics (University of Washington)
- GitHub: mandli
Research highlights
- Develops numerical methods and scientific software for nonlinear hyperbolic PDEs, with emphasis on adaptive finite-volume schemes and transport-dominated systems.
- Leads and contributes to widely used open-source software for geophysical and hazard modeling, including Clawpack, GeoClaw, and PyClaw, supporting applications across academia, government, and industry.
- Conducts interdisciplinary research at the interface of applied mathematics, climate science, and coastal risk, with applications to storm surge, compound flooding, and infrastructure resilience.
- Collaborates with national laboratories, federal agencies, and international partners on decision-relevant modeling for climate and hazard impacts.
Selected metrics: 2,100+ citations · h-index 24 · i10-index 36 · Google Scholar
Appointments
- NSF National Center for Atmospheric Research (NCAR) — Scientist IV, CGD Lab (2025–present)
- Flatiron Institute, Center for Computational Mathematics — Research Scientist (2023–2024)
- Columbia University, Applied Physics & Applied Mathematics
Assistant Professor (2014–2019) · Associate Professor (2019–2023) · Research Scientist (2023) - University of Texas at Austin, ICES — Postdoctoral Research Fellow / Research Associate (2011–2014)
Open-source software (selected)
GeoClaw — Core developer & maintainer
Adaptive mesh refinement modeling of storm surge, tsunami, and coastal flooding.
PyClaw — Core developer & maintainer
Python framework for solving hyperbolic PDEs with modern, reproducible workflows.
Clawpack Suite — Contributor & maintainer
(Conservation Laws Package) Open-source ecosystem for wave propagation and finite-volume methods.
Numerical Methods Course Notes — Author
Jupyter notebook-based course materials for an introduction to numerical methods.
Jupyter notebook materials for teaching numerical methods for PDEs.
Teaching & mentoring (at a glance)
- Teaching areas: numerical analysis, finite-volume methods, hyperbolic PDEs, uncertainty quantification, computational science.
- Courses taught (selected): Uncertainty Quantification; Finite Volume Methods for Hyperbolic PDEs; Numerical Methods for PDEs; Introduction to Numerical Methods.
- Doctoral mentoring: Advising and co-advising PhD students in applied mathematics, civil engineering, and climate science, with dissertations spanning adaptive methods, coastal flooding, and optimization of protective strategies.
- Postdoctoral mentoring: Mentored postdoctoral and early-career researchers now in research scientist and tenure-track faculty positions.
Service (selected)
- Organizer and leadership roles in SIAM and applied mathematics communities, including SIAM New York-New Jersey-Pennsylvania Section conferences.
- Program and organizing committee member for international conferences in computational science and high-performance computing.
- Panelist and contributor to national discussions on climate risk, hazard modeling, and convergent research.
- Extensive editorial and peer-review service for journals in applied mathematics, computational science, and geophysics.
Full details: Download CV (PDF)