North American High Order Methods Conference (NAHOMCon) 2024, June 17-19, 2024

New England Numerical Analysis Day (NENAD) 2024, June 18, 2024

General Information

The third North American High Order Methods Conference (NAHOMCon) will be held at Dartmouth College in Hanover New Hampshire. NAHOMCon aims to provide a North American forum for computational scientists, mathematicians, scientists and engineers to share ideas and techniques on, and further the state of the art of, high order methods for the solution of partial differential equations with applications to a broad range of scientific and engineering applications.

The conference will feature six invited talks over a three day period with parallel sections of shorter lectures grouped by topics. We encourage students to register to present research in our planned poster session on June 18. All lectures will be in Kemeny Hall at Dartmouth College (campus maps).

New England Numerical Analysis Day (NENAD) will be held on June 18, 2024, in conjunction with NAHOMCon 2024. A separate registration is required for NENAD participants who are not also attending NAHOMCon 2024. A poster session will take place on June 18, 2024, in the afternoon. NENAD participants are strongly encouraged to present posters.

NAHOMCon 2024 is generously supported by the National Science Foundation and by Dartmouth College.

New Conference Updates

  1. Conference photos (right click to download the full size images)
  2. Downloadable detailed campus map.
  3. Conference Program PDF file (last update: June 17, 2024).
  4. Downloadable list of local restaurants.

Organization of the Conferences

Local organizers:

Anne Gelb (Dartmouth College)

Yoonsang Lee (Dartmouth College)

Yanlai Chen (UMass Dartmouth)


Scientific Committee:

Sigal Gottlieb (UMass Dartmouth)

Thomas Hagstrom (Southern Methodist University)

Gustaaf Jacobs (San Diego State University)

David Kopriva (Florida State University)

Chunlei Liang (Clarkson University)

Catherine Mavriplis (University of Ottawa)

Per-Olof Persson (University of California, Berkeley)

Anders Petersson (Lawrence Livermore National Laboratory)

Tim Warburton (Virginia Tech)

Schedule of the Conference

Download program (last update: June 17, 2024)

Day 1, Sunday June 16

4:30 PM Dorms check-in (Receive Key at Kemeny 300)
5:00 PM Welcome Reception Kemeny 300

Day 2, Monday June 17

8:00 AM (outside Kemeny 008) Registration. Pastries and coffee are available
8:30 AM (Kemeny 008) Convening of Conference (Phil Hanlon, Past President Dartmouth College)
8:40 AM Invited talk: Frank Giraldo, Naval Postgraduate School
9:40AM - 11:10AM (Kemeny 006) MS01: Summation-by-parts: building stable discretizations since 1974 1/2 (Organizers: Jason Hicken of Rensselaer Polytechnic Institute, Jesse Chan of Rice University) (Kemeny 007) MS02: Scientific Machine Learning for Partial Differential Equations 1/2 (Organizers: Zhongqiang Zhang and Qiao Zhuang of Worcester Polytechnic Institute)  
  Implicit dual time-stepping positivity-preserving entropy stable schemes for the compressible Navier-Stokes equations (M Sayyari and Nail Yamaleev, Old Dominion University) GPT-PINN and TGPT-PINN: Linear and nonlinear model order reduction toward non-intrusive Meta-learning of parametric PDEs via Physics-Informed Neural Networks (Yanlai Chen, UMass Dartmouth)  
  Beyond polynomials: SBP operators for general approximation spaces (Jan Glaubitz, Massachusetts Institute of Technology) Tensor neural networks for high-dimensional Fokker-Planck equations (Zhongqiang Zhang, Worcester Polytechnic Institute)  
  Injected boundary conditions for the compressible Navier-Stokes equations (Anita Gjesteland, University of Waterloo) Randomized Forward mode of automatic differentiation for optimization algorithms (Khemraj Shukla, Brown University)  
  Positivity-preserving and entropy-bounded discontinuous Galerkin method for the multicomponent, chemically reacting Navier-Stokes equations (Eric Ching, US Naval Research Laboratory) Two-scale neural networks for partial differential equations with small parameters (Qiao Zhuang, Worcester Polytechnic Institute)  
11:10 AM Break
11:25AM - 12:55PM (Kemeny 006) MS03: Summation-by-parts: building stable discretizations since 1974 2/2 (Organizers: Jason Hicken of Rensselaer Polytechnic Institute, Jesse Chan of Rice) (Kemeny 007) MS04: Scientific Machine Learning for Partial Differential Equations 2/2 (Organizers: Zhongqiang Zhang and Qiao Zhuang of Worcester Polytechnic Institute) (Kemeny 008) Contributed Talks: Session 1
  Shock Capturing Schemes in Discontinuous Galerkin Spectral Element Formulation for Euler and Navier-Stokes Equations (Yulia Peet, Arizona State University) An artificial viscosity method augmented physics informed neural networks for incompressible flow at high Reynolds number (Zhicheng Wang, Dalian University of Technology) Spectrally convergent local algorithms for nonlocal problems (Tom Hagstrom*, Southern Methodist University)
  High order entropy stable discontinuous Galerkin spectral element methods through subcell limiting (Yimin Lin, Rice University) tLaSDI: Thermodynamics-informed latent space dynamics identification (Yeonjong Shin, North Carolina State University) A Hermite Method for Nonlinear Dispersive Maxwell’s Equations (Yann-Meing Law, California State University Long Beach)
  An Assessment of Fully-Discrete Entropy Stable Flux Reconstruction for Turbulent Flows (Carolyn Pethrick, McGill University) Efficient Data-Driven Modeling of PDEs (Victor Churchill, Trinity College ) Graph-theoretic preconditioners for centre-based tissue models (Andreas Buttenschoen, UMass Amherst)
  Energy-stable and structure-preserving schemes for the stochastic shallow water equations (Akil Narayan, University of Utah) One-shot learning for solution operators of partial differential equations (Anran Jiao, Yale University) Simple quadrature for near-singular integral operators (Bowei Wu, UMass Lowell)
12:55 PM Lunch (on your own)
2:10 PM Kemeny 008 Invited talk: Lise-Marie Imbert-Gerard, University of Arizona
3:10PM - 4:40PM (Kemeny 006) MS05: Advances in the Construction and Use of Summation-by-Parts Operators for Time-Dependent PDEs (Organizers: Jan Glaubitz of Massachusetts Institute of Technology, Jan Nordström of Linköping University) (Kemeny 007) MS06: Design and analysis of machine learning algorithms inspired by traditional numerical methods 1/2 (Organizer: Yanlai Chen of UMass Dartmouth) (Kemney 008) Contributed Talks: Session 2
  On the Stability of the DGSEM for Overset Grid Problems (David Kopriva, Florida State University) Adaptive reduced-order models for high-speed flow via optimal transport (Robert Loek Van Heyningen, Massachusetts Institute of Technology) Federated Machine Learning for Experimental Facilities (Rick Archibald*, ORNL)
  Constructing diagonal-norm summation-by-parts operators on point clouds (Jason E. Hicken, Rensselaer Polytechnic Institute) Efficient Hybrid Spatio-Temporal Operator Learning (Shuhao Cao, University of Missouri-Kansas City) Structure-preserving matrix-free finite element method (Svetlana Tokareva, Los Alamos National Laboratory)
  Sparse subcell limiting for multi-dimensional SBP operators on general elements (Jesse Chan, Rice University) Robust and fast differentiation for Sinkhorn optimal transport (Felix Ye, University of Albany) Can High-Order Convergence Be Obtained for Practical Problems in Engineering? (Brian Helenbrook, Clarkson University)
  Generative Reduced Order Modeling for Parametrized Partial Differential Equations (Ngoc Cuong Nguyen, MIT) Nonlinear scientific computing in machine learning (Wenrui Hao, Pennsylvania State University) Implementing Immersed Boundaries in Continuous and Discontinuous Spectral Element Methods with hp-Adaptivity (Catherine Mavriplis (and Amik Nayak), University of Ottawa)
6:00 PM Pizza dinner (please confirm your attendance at registration table)

Day 3, Tuesday June 18

8:00 AM (Outside Kemeny 008) Registration (NENAD)
8:40 AM (Kemeny 008) Invited talk: Noel Chalmers, AMD Research
9:40 AM (Kemeny 008) NENAD Plenary talk: Gil Strang, Massachusetts Institute of Technology
9:40 AM (Introduction: Peter Mucha, Jack Byrne Distinguished Professor in Mathematics)
10:30AM - 12:00PM (Kemeny 006) MS07: Advances in Bayesian scientific computing and its applications (Organizers: Tongtong Li of Dartmouth College, Jan Glaubitz of Massachusetts Institute of Technology) (Kemeny 007) MS08: Next-generation solvers using fast and high-order accurate integral equation methods (Organizer: Thomas G. Anderson of Rice University) (Kemeny 008) Contributed Talks: Session 3
  Bayesian and Deterministic Methods with Edge-Preserving Priors for Spatio- Temporal Large-Scale Inverse Problems (Mirjeta Pasha, Tufts University) Accurate approximation of layer potentials evaluated near axisymmetric surfaces (David Krantz, KTH) Policy iteration method for inverse mean field games (Shanyin Tong, Columbia University)
  Preserving linear invariants in ensemble filtering methods (Mathieu Le Provost, Massachusetts Institute of Technology) Frequency- and Time-domain Green function methods for electromagnetic simulation, optimization, and design (Oscar Bruno, Caltech) High-order time integration for nonlinearly partitioned multiphysics (Ben Southworth*, Los Alamos National Lab)
  A regularity criterion for the 3D Navier-Stokes equations based on finitely many observations (Abhishek Balakrishna, University of Southern California) Fast algorithms for Stokesian rigid body suspensions (Eduardo Corona, CU Boulder) A structurally informed data assimilation approach for discontinuous state variables (Tongtong Li, Dartmouth College)
  Bayesian inference of biological dynamics (Chenyi Fei, Massachusetts Institute of Technology) Fast, provably high-order accurate methods for volume integral operators (Thomas G Anderson, Rice University) New Analysis of Overlapping Schwarz Methods for Vector Field Problems in Three Dimensions with Generally Shaped Domains (Duk-Soon Oh, Chungnam National University)
12:00 PM Lunch (Dartmouth Dining Hall)
1:20 PM (Kemeny 008) Invited talk: Scott Field, Umass Dartmouth
2:20PM - 3:50PM (Kemeny 006) MS09: Matrix-free Methods for Advanced High-Fidelity Simulations (Organizer: Yohann Dudouit of Lawrence Livermore National Laboratory) (Kemeny 007) MS10: Design and analysis of machine learning algorithms inspired by traditional numerical methods 2/2 (Organizer: Yanlai Chen of Umass Dartmouth) (Kemeny 008) Career Panel: Professionals working in academia, national labs, and industry will discuss various aspects of their work environment, and answer questions about what steps are needed to pursue careers in these different areas.
  Overcoming the Curse of Dimensionality: Matrix-Free, High-Order Discon- tinuous Galerkin Methods for Advection-Diffusion in Phase Space (Yohann Dudouit, Lawrence Livermore National Laboratory) Low Rank Neural Representation (LRNR) for model reduction of nonlinear conservation laws (Donsub Rim, Washington University in St. Louis) Sigal Gottlieb*, Andrew Christlieb Catherine Macriplis, Svetlana Tokareva, Carol Woodward, and Noel Chalmers
  GPU optimization of an implicitly time-stepped high-order finite element wave solver (Tim Warburton, Virginia Tech) Projection method for causal discovery (Yue Yu, Lehigh University)  
  Low-Order Preconditioning for SEM-Based Advection-Diffusion Problems (Yu-Hsiang Lan, University of Illinois) Approximation Rates for Shallow ReLU$^k$ Neural Networks on Sobolev and Besov Spaces (Jonathan Siegel, Texas A&M University)  
  A stochastic approach for solving PDEs: multiscale problems and perforated domain problems (Jihun Han, Dartmouth College) Multifidelity Scientific Machine Learning (Panos Stinis, Pacific Northwest National Laboratory)  
3:50 PM Poster Session with Snacks (First Floor, Kemeny)
6:00 PM Conference Banquet (Patio outside Kemeny)

Day 4, Wednesday June 19

8:00 AM  
8:30 AM  
8:40 AM (Kemeny 008) Invited talk: Carol Woodward, Lawrence Livermore National Laboratory
9:40AM - 11:10AM (Kemeny 006) MS11 Recent Advances in Finite Element Methods for Flow Problems (Organizers: Zheng Sun of University of Alabama, Ziyao Xu of University of Notre Dame) (Kemeny 007) MS12: High-order methods for computational relativity (Organizer: Vijay Varma of UMass Dartmouth) (Kemeny 008) Contributed Talks: Session 4
  A reinterpreted discrete fracture model for Darcy-Forchheimer flow in fractured porous media (Yang Yang, Michigan Technology University) Simulating binary black holes with higher order methods using SpECTRE (Geoffrey Lovelace, California State University, Fullerton) High-order Lagrangian algorithms for Liouville models (Gustaaf Jacobs*, San Diego State University)
  An interior penalty discontinuous Galerkin (IDPG) method for an interface model of flows in fractured media (Ziyao Xu, University of Alabama) Extracting physics from black hole simulations with Cauchy-characteristic evolution (Keefe Mitman, California Institute of Technology) A Parallel hp-Adaptive Discontinuous Galerkin Spectral Element Method Solver for Acoustic Problems in Curvilinear Geometries with Dynamic Load Balancing (Catherine Mavriplis, University of Ottawa)
  High order entropy stable methods for blood flow simulations (Raven Johnson, Rice University) Higher-order boundary conditions in numerical relativity through Cauchy-characteristic matching (Sizheng Ma, Perimeter Institute) Local Adaptivity in Kernel Methods (Jonah A Reeger, Air Force Institute of Technology)
  An energy-based discontinuous Galerkin method for stochastic wave equations in second order form (Lu Zhang, Rice University) Simulating binary neutron star mergers with mixed Discon- tinuous Galerkin - Finite Volume methods (Francois Foucart, University of New Hampshire) Discontinuous Galerkin Methods for Hypersonic flows (Ngoc Cuong  Nguyen, Massachusetts Institute of Technology)
11:10 AM Break
11:25AM - 12:55PM (Kemeny 006) Contributed Talks: Session 5 (Kemeny 007) MS13: Highly Accurate Machine Learning Methods for Solving PDEs (Organizers: Keenan Eikenberry, Lizuo Liu, Tongtong Li of Dartmouth College)  
  The Runge-Kutta discontinuous Galerkin method with stage-dependent polynomial spaces for hyperbolic conservation laws (Zheng Sun*, University of Alabama) Data-driven discovery of independent conservation laws through neural deflation (Wei Zhu, University of Massachusetts Amherst)  
  Enhanced data assimilation based on the energy spectrum of nonlinear chaotic dynamics (Bosu Choi, Dartmouth College) A Finite Expression Method for Solving High-Dimensional Committor Problems (Zezheng Song, University of Maryland)  
  Stencils and Representations that Promote High-Order Accuracy (Phil Roe, University of Michigan (emeritus)) Solving High Frequency and Multi-Scale PDEs with Gaussian Processes (Shikai Fang, University of Utah)  
  Fifth-order Active Flux Methods for Wave Propagation (Iman Samani, University of Michigan) DeepPropNet - A Recursive Deep Neural Network Propagator for Learning Evolutionary PDE Operators (Lizuo Liu, Dartmouth College)  
12:55 PM Lunch (Dartmouth Dining Hall)
2:10 PM (Kemeny 008) Invited talk: Andrew Christlieb, Michigan State University
3:10 PM Conference End

Financial Support

Students, postdoctoral fellows, and early career professionals may request college dormitory (single) rooms and meal plans when registering. Priority will be given to those who are speaking or presenting a poster. Please click on the "Registration, abstract submission and deadlines" link and fill out the travel support request form. The deadline has now passed, and notification of support has gone out.

Invited Speakers


Registration: Deadline May 10, 2024
The deadline has now passed. Questions regarding onsite registration can be sent to Anne Gelb ().

Support: Some financial support for students, postdoctoral fellows, and early career faculty will be available in the form of local dormitory housing and meal plans. Please submit your request for travel support when you submit your talk/minisymposium abtract. Minisymposium participants must separately submit travel support requests for each participant. Decisions regarding both acceptance of abstract submissions and awards for travel support (dormitory housing) will be made in March 2024. Travel support awards have all been made.

Spam email: Unfortunately there is a phishing email circulating that pretends to be from a travel agency and offers to make travel arrangements to conferences, including NahomCON24. Please do not reply to such emails if you receive them. Any administrative emails pertaining to NahomCON24 will only be sent from a local organizing committee member or a Dartmouth College mathematics department administrator with a email address.

Abstract submission

The deadlines for abstract submissions and requests for travel support have passed. Notifications regarding travel awards and acceptance for contributed talks, posters, and mini-symposia have been sent out.

Directions, Air Travel and Shuttle, Accommodations:

Air travel

There is a very small regional airport in Lebanon, NH. If you fly into Boston, there is a bus called the Dartmouth Coach that takes you right into Hanover, across the street from campus. There is also a stop at Lebanon (see accommodations below). Other local airports include Manchester, NH, and Burlington, VT. You will need to rent a car from either location to get to Hanover.

Driving Directions to Dartmouth

Nearby accommodations and local transportation

·       Advance Transit (Free transit for the Upper Valley) : Phone # (802) 295-1824. This very convenient free bus service has stops near several hotels throughout the Upper Valley, and includes the towns of White River Junction, Lebanon, and West Lebanon.

·       Hanover Inn : Phone # 603-643-4300. The Dartmouth Coach (from Boston-Logan airport) drops passengers in front of the hotel. It is across the street from campus, and a five minute walk to Kemeny Hall.

·       Residence Inn Hanover Lebanon: Phone # 603-643-4511. The DHMC shuttle has transportation to campus.

·       Hilton Garden Inn Lebanon, NH: Phone # 603-448-3300. The Dartmouth Coach (from Boston-Logan airport) has a stop within walking distance. There is currently no shuttle to Dartmouth. It is a conevenient 10 minute drive for those with cars, and free parking at Dartmouth for conference participants is available.


Please contact Anne Gelb ().