Biography
Eitan Tadmor is a Distinguished University Professor at the University of Maryland (UMd), College Park and the Director of the university Center for Scientific Computation and Mathematical Modeling (CSCAMM).
Tadmor received his Ph.D. in Mathematics from Tel Aviv University in 1979, and he began his scientific career as a Bateman Research Instructor in CalTech, 19801982. He held professorship positions at TelAviv University, 19831998, where he chaired the Department of Applied Mathematics from 19911993, and at UCLA, 19952004, where he was the founding codirector of the NSF Institute for Pure and Applied Mathematics (IPAM) from 19992001. Since 2002, he has served on the faculty of the Department of Mathematics and the Institute for Physical Sciences and Technology at UMd. In 2012 he was awarded as the PI of the NSF Research network Kinetic Description of Emerging Challenges in Natural Sciences(KiNet).
Tadmor has held visiting positions in the universities of Michigan, Paris VI, and Brown, the Courant Institute and at the Weizmann Institute, and he is currently a Senior Fellow at the Institute for Theoretical Studies at ETHZürich (20162017). He serves on the editorial boards of more than a dozen leading international journals and has given numerous invited lectures, including plenary addresses in the international conferences on hyperbolic problems in 1990 and 1998 and an invited lecture in the 2002 International Congress of Mathematicians. In 2015 Tadmor was awarded the SIAMETH Peter Henrici prize for " original, broad, and fundamental contributions to the applied and numerical analysis". Tadmor is an AMS Fellow who was listed on the ISI most cited researchers in mathematics. He has published more than one hundred and fifty research papers, mostly in Numerical Analysis and Applied Partial Differential Equations.

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Research accomplishments
Eitan Tadmor
is well known for ...
Eitan Tadmor is well known for his contributions to the theory and computation of Partial Differential Equations with diverse applications to shock waves, kinetic transport, incompressible flows, image processing, and selforganized collective dynamics.
The signature of Professor Tadmor work is the interplay between analytical theories and computational algorithms for such equations. In particular, he has made a series of fundamental contributions to the development of highresolution methods for nonlinear conservation laws, including those associated with the notions of central schemes, entropy stability, spectral viscosity methods, constraint transport, edge detection, and more.
Tadmor has carried out influential work on the rigorous derivation of transport models and their relation to kinetic theories, and on critical thresholds phenomena in such models.
He introduced novel ideas of multiscale descriptions of images, and in recent years, leads an interdisciplinary research program in modeling and analysis of collective dynamics with applications to flocking and opinion dynamics.

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Professional profile ( selected items) ...
Pofessional profile (selected items)
Selected professional Appointments
• Senior Fellow, Institute for Theoretical Studies (ITS), ETHZurich, 20162017
• Director, Center for Scientific Computation and Math. Modeling (CSCAMM), Univ. of Maryland, 20022016
• Founding CoDirector, NSF Institute for Pure and Applied Math. (IPAM), UCLA, 1999
• Director, The Sackler Institute of Scientific Computation, TelAviv University, 19931996
• Chair, Department of Applied Mathematics, TelAviv University, 19911993
Selected synergistic activities
• Director, NSF Research Network, Kinetic description of emerging challenges in ... natural sciences (KINet), 20122017
• PI, NSF Focus Research Group: Kinetic Description of Multiscale Phenomena, 20082012
• Scientific Committee, Abel Symposium on “Nonlinear PDEs”, Oslo, Sep. 2010
• CoChair, The International conference on Hyperbolic Problems,
U. of Maryland, Hyp2008, and CalTech, Hyp2002
Selected invited talks
• SIAM invited address, Joint Math. Meeting, Baltimore, Maryland, January 2014
• Plenary lectures 
 The 13th int’l conference on Hyperbolic Problems (Hyp2010) Beijing, June, 2010
 Foundations of Computational Mathematics (FoCM2008) HongKong, June, 2008
 SIAM Conference of Analysis of PDEs, Boston, MA, July 2006
• Invited speaker, International Congress of Mathematicians (ICM), Beijing Aug. 2002
Selected editorial boards
Acta Numerica, 2009—present
SIAM Journal on Math. Analysis (SIMA), 2004present
Journal of Foundations of Computational Mathematics (JFoCM), 2004present
SIAM Journal on Numerical Analysis (SINUM), 1990—2013
Selected recognitions
SIAMETHZ Henrici Prize for original contributions to applied analysis and numerical analysis, 2015
Member, Cosmos Club, Washington DC, 2013
AMS Fellow, 2012 inaugural class of Fellows of the American Mathematical Society
Listed, Most cited researchers in mathematics (ISIHighlyCited.com), 2003
Rothschild Fellowship, Mathematics, 1980

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Key words (with selected references) ...
Significant publications
Other lists of publications:
[by subject classification]
[by chronological order]
[selected publications]

Highresolution approximations of nonlinear conservation laws
1 Nonoscillatory central differencing for hyperbolic conservation laws
H. Nessyahu and E. Tadmor, J. of Computational Physics 87 (1990) 408–463.
This paper introduced the NessyahuTadmor (NT) scheme  the forerunner for the class of highresolution "central schemes", which offer "blackbox" solvers for a wide variety of problems governed by multidimensional systems of nonlinear conservation laws and related PDEs, consult CentPack.
Related followup work can be found in the 1990 JCP work with A. Kurganov on New high resolution central schemes for nonlinear conservation laws and convectiondiffusion equations.
2 Local error estimates for discontinuous solutions of nonlinear hyperbolic equations
E. Tadmor, SIAM J. Numerical Analysis 28 (1991) 891906.
This paper introduced a novel L^{1}convergence rate theory for nonlinear conservation laws and related HamiltonJacobi equations. The theory, based on onesided stability estimates, provides an alternative to the standard KrushkovKuznetzov theory and led to optimal L^{1}convergence rates. A large body of related works, including the 2001 Numerische Mathematik work with C.T Lin on L^{1}stability and error estimates for approximate HamiltonJacobi solutions can be found here.
3 ENO reconstruction and ENO interpolation are stable (+errata)
U. Fjordholm, S. Mishra and E. Tadmor, Foundations of Computational Mathematicas 13(2) (2012), 139159.
The ENO reconstruction procedure was introduced in 1987 by Harten et. al. in the context of accurate simulations for piecewise smooth solutions of nonlinear conservation laws. Despite the extensive literature on the construction and implementation of ENO method and its variants, the question of its stability remained open during the last 25 years.
Here we prove that the ENO reconstruction and ENO interpolation procedures are stable in the sense that the size of the of the jumps after ENO reconstruction relative to the jump of the underlying cell averages is bounded. These estimates, which are shown to hold for ENO reconstruction and interpolation of arbitrary order of accuracy and on nonuniform meshes, indicate a remarkable rigidity of the piecewisepolynomial ENO procedure.
Kinetic formulation and regularizing effects in nonlinear conservation laws and
related problems
4 A kinetic formulation of multidimensional scalar conservation laws and related equations
P.L. Lions, B. Perthame and E. Tadmor, J. American Math. Society 7 (1994) 169–191.
This paper provides a systematic treatment of kinetic formulation of entropic solutions for nonlinear conservation laws and related convectiondiffusion equations and the first derivation of regularizing effects using the averaging lemma.
It was followed by a large body of works which utilized the kinetic formulation and their new regularizing effects for conservation laws, related degenerate equations and their numerical approximations.
In particular, a followup 1994 CMP work with P.L. Lions and B. Perthame on Kinetic formulation of the isentropic gas dynamics and psystems.
5 Velocity averaging, kinetic formulations and regularizing effects in quasilinear PDEs
E. Tadmor and Terence Tao, Communications Pure & Applied Mathematics 60 (2007), 1488–1521.
The present paper provides the first quantitative velocity averaging result for second order equations, thus paving the way for a full family of new results for regularizing effects in secondorder degenerate nonlinear parabolic equations, in particular in the anisotropic cases where relatively little was known prior to this contribution. The method of proof is based on a delicate multipliers techniques, dyadic decomposition and refined estimates on LittlewoodPaley blocks to verify the socalled "truncation property".
Spectral approximations – the spectral viscosity method and computation of the
Gibbs phenomenon
6 Recovering pointwise values of discontinuous data within spectral accuracy
D. Gottlieb and E. Tadmor, in “Progress and Supercomputing in Computational Fluid Dynamics”,
Proc. 1984 U.S.Israel Workshop on Progress in Scientific Computing, Vol. 6 (E. M. Murman and S. S.
Abarbanel, eds.), Birkhauser, Boston (1985) 357375 [SIAM Rev 28(4) 1986].
Here we show how the pointvalues of a piecewise smooth function can be recovered from its spectral content, so that the accuracy depend solely on the local smoothness. This paper was the forerunner for large body of work which followed on the 90s and 00s, on computation of the Gibbs phenomenon (Gottlieb, Shu, Gelb, Tanner and others). In particular, these GottliebTadmor mollifiers were subsequently improved to (root) exponential accuracy (with J. Tanner) and motivated the development of effective spectral edge detectors (with A. Gelb).
7 Convergence of spectral methods for nonlinear conservation laws
E. Tadmor, SIAM J. Numerical Analysis 26 (1989) 30–44.
The Spectral Viscosity (SV) method was developed in 1989 as a systematic approach for treating shock discontinuities in spectral calculations, by adding a spectrally small amount of highfrequencies diffusion. The resulting SVapproximation is stable without sacrificing spectral accuracy, recovering a spectrally accurate approximation of (the projection of the) entropy solution. Subsequently, the SV method was implemented by many practitioners in highly accurate spectral computations of nonlinear equations; consult here.
8 Filters, mollifiers and the computation of the Gibbs phenomenon
E. Tadmor, Acta Numerica 16 (2007) 305378.
This 2007 Acta Numerica review contains a summary of the developments during 19852007 on detection of edges in pieciewise smooth spectral data and the high resolution reconstriction of the data between those edges.
Critical thresholds in Eulerian dynamics
9 Spectral dynamics of the velocity gradient field in restricted flows
H. Liu and E. Tadmor, Communications in Mathematical Physics 228 (2002), 435–466.
In this paper we initiate a systematic study of global regularity vs. finite time blowup gradients of the fundamental Eulerian equation,
u_{t}+ u·∇_{x}u= F, which shows up in different contexts dictated by the different modeling of F's. The analysis is based on the spectral dynamics tracing the eigenvalues of the velocity gradient which determine the boundaries of the critical threshold surfaces in configuration space.
It led to a large body of work which demonstrated \emph{a generic scenario of critical threshold phenomena}, where global regularity depends on the initial configurations of density, velocity divergence and the spectral gap of the 2×2 velocity gradient. This includes showing that rotational forcing prolongs the lifespan of subcritical 2D shallowwater solutions, global regularity results for subcritical 2D restricted EulerPoisson and for 3D radial EulerPoisson equations, and a surprising global existence result for a large set of subcritical initial data in the 4D restricted Euler eqs. Additional refrences can be found here
Entropy stability for difference approximations of nonlinear conservation laws
10 Entropy stability theory for difference approximations of nonlinear conservation laws
and related time dependent problems
E. Tadmor, Acta Numerica 12 (2003), 451512.
Entropy stability plays an important role in the dynamics of nonlinear systems of conservation laws and related convectiondiffusion equations.
The paper provides a stateoftheart summary for the a body of works during 19872007 on the topic of entropy stability (beginning with the 1987 Math. Comp. work The numerical viscosity of entropy stable schemes for systems of conservation laws. I.
Here, we developed a general theory of entropy stability for difference approximations for nonlinear equations, which
provides precise characterization of entropy stability using comparison principles. In particular, we construct a new family of entropy stable schemes which retain the precise entropy decay of the NavierStokes equations. They contain no artificial numerical viscosity. The theory can be found in the followup developments here.
11 Construction of approximate entropy measurevalued solutions for hyperbolic systems of conservation laws
U. Fjordholm, R. Kappeli S. Mishra and E. Tadmor, Foundations of Computational Mathematics (2015).
Entropy solutions have been widely accepted as the suitable solution framework for systems of conservation laws in several space dimensions. However, recent results of De Lellis and Székelyhidi have demonstrated that entropy solutions may not be unique. In this paper, we present numerical evidence that demonstrates that state of the art numerical schemes may not necessarily converge to an entropy solution of systems of conservation laws as the mesh is refined. Combining these two facts, we argue that entropy solutions may not be suitable as a solution framework for systems of conservation laws, particularly in several space dimensions.
We advocate a more general notion due to Diperna  that of entropy measure valued solutions, as an appropriate solution paradigm for systems of conservation laws. To this end, we present the first detailed numerical procedure which constructs stable approximations to entropy measure valued solutions and provide sufficient conditions that guarantee these approximations converge to an entropy measure valued solution as the mesh is refined, thus providing a viable numerical framework for systems of conservation laws in several space dimensions. A large number of numerical experiments that illustrate the proposed schemes are presented and are utilized to examine several interesting properties of the computed entropy measure valued solutions.
A broader view of our paradigm for the computation of measurevalued solutions of both  compressible and incompressible Euler equations, is surveyed in this 2016
Acta Numerica article.
Numerical methods for PDEs: translatory boundary conditions, SSP timediscretization, BAMS review
12 Schemeindependent stability criteria for difference approximations of hyperbolic
initialboundary value problems. II
M. Goldberg and E. Tadmor, Mathematics of Computation 36 (1981) 603–626.
The development of easily checkable stability criteria for finitedifference approximations of initial boundary value systems with translatory boundary conditions. This led a series of works in the eighties, and it became a standard tool in the stability theory for approximations of initialboundary value problem of hyperbolic type.
13 High order time discretization methods with the strong stability property
S. Gottlieb, C.W. Shu and E. Tadmor, SIAM Review 43 (2001) 89–112.
We construct, analyze and implement the class of strong stabilitypreserving (SSP) highorder time discretizations for semidiscrete method of lines approximations of PDEs. These highorder methods preserve the strong stability properties of firstorder Euler time stepping and have proved very useful, especially in solving hyperbolic PDEs. Since its publication in 2001, this work has become a standard reference on SSP solvers.
14 A review of numerical methods for nonlinear partial differential equations
E. Tadmor, Bulletin of the AMS 49(4) (2012) 507554.
The interplay between computation, theory, and experiments was envisioned by John von Neumann, who in 1949 wrote that "the entire computing machine is merely one component of a greater whole, namely, of the unity formed by the computing machine, the mathematical problems that go with it, and the type of planning which is called by both." This "greater whole" is viewed today as scientific computation, and numerical methods for solving PDEs are at the heart of many of today's advanced scientific computations, from financial models on Wall Street to traffic models on Main Street. Here we provide a bird's eye view on the development of these numerical methods during the last sixty years, with a particular emphasis on nonlinear PDEs.
Hierarchical decompositions with applications in image processing and PDEs
15 A multiscale image representation using hierarchical (BV, L2) decompositions
E. Tadmor, S. Nezzar and L. Vese, Multiscale Modeling & Simulation 2 (2004) 554–579.
The paper introduces a novel hierarchical decomposition of images, the forerunner of recently developed iteration methods in image processing. Questions of convergence, energy decomposition, localization and adaptivity are discussed. Subsequently, our approach was used in applications to synthetic and real images. The approach developed here was pursued in a series of works, including the 2011 SIAM J. Imaging Sciences paper with P. Athavale on Integrodifferential equations based on (BV, L^{1}) image decomposition. Additional refrences can be found here.
Selforganized dynamics
16 Heterophilious dynamics enhances consensus
S. Motsch and E. Tadmor, SIAM Review 56(4) (2014) 577–621 (with Introduction by D. J. Higham).
Nature and human societies offer many examples of selforganized behavior.
Ants form colonies, birds fly in flocks, mobile networks coordinate a rendezvous, and human opinions evolve into parties.
These are simple examples of collective dynamics that tend to selforganize into largescale clusters of colonies, flocks, parties, etc.
We review a general class of models for selforganized dynamics based on alignment.
Prototypical examples are the local HegselmannKrause model for opinion dynamics,
and the Vicsek model for flocking, the global CuckerSmale model for flocking, and its local version version
advocated here.
A natural question which arises in this context is to ask when
and how clusters emerge through the selfalignment of agents, and what types of “rules
of engagement” influence the formation of such clusters. Of particular interest to us are
cases in which the selforganized behavior tends to concentrate into one cluster, reflecting
a consensus of opinions.
Standard models for selforganized dynamics assume that the intensity of alignment increases as agents get closer, reflecting
a common tendency to align with those who think or act alike. “Similarity
breeds connection” reflects our intuition that increasing the intensity of alignment as the
difference of positions decreases is more likely to lead to a consensus. We argue here that
the converse is true: when the dynamics is driven by local interactions, it is more likely
to approach a consensus when the interactions among agents increase as a function of
their difference in position. Heterophily  the tendency to bond more with those who are
different rather than with those who are similar, plays a decisive role in the process of
clustering. We point out that the number of clusters in heterophilious dynamics decreases
as the heterophily dependence among agents increases. In particular, sufficiently strong
heterophilious interactions enhance consensus.
What is the qualitative behavior of selforganized dynamics for very large groups (N → ∞)?
Agentbased models lend themselves to standard kinetic descriptions and hydrodynamics descriptions. The latter govern "social hydrodynamics" and their critical threshold phenomena are studied here.
[Acknowledgement]

