PW

Research

My research spans evolutionary computation, data theory, and the physics of correlated materials. I created a completely new type of AI, Genetic AI, based on evolutionary game theory. It is a complementary AI with respect to machine learning in the sense that it learns from logical connections in data by applying evolutionary paradigms like selfishness and altruism. My earlier work connects first-principles methods with correlated approaches such as DMFT.

Research timeline

2007

Numerical analysis & adaptive methods

Diploma thesis on a space-time adaptive algorithm for linear parabolic problems at the Institute for Analysis and Scientific Computing, TU Vienna.

2008–2010

First-principles methods for correlated materials

Work on Wien2wannier and LDA+DMFT analysis of sodium cobaltate thermopower — bridging band-structure methods with many-body correlation effects.

2011–2012

Transport properties of correlated materials

PhD thesis on transport from first principles, including the dipole-matrix versus Peierls-approximation debate for optical conductivity.

2025

Genetic AI

Introduced Genetic AI: evolutionary games for ab initio dynamic multi-objective optimization, a new approach to learning from logical connections in data.

2025

Feature weighting via evolutionary simulation

Collaboration showing how evolutionary simulation can be used to weight features for data analysis.

2026

Evolutionary Data Theory

Unified framework connecting data problems to evolutionary games, formalizing the similarities between data analysis and evolutionary dynamics.

Selected publications

Dipole matrix element approach versus Peierls approximation for optical conductivity

P. Wissgott, J. Kuneš, A. Toschi, K. Held

Phys. Rev. B 85, 205133 (2012)

Transport Properties of Correlated Materials from First Principles

P. Wissgott

PhD thesis, Professor: Karsten Held, Assistant supervisor: Alessandro Toschi, Institute for Solid State Physics, TU Vienna, 2012

Efficient Implementation of FEM in Matlab

S. Funken, D. Praetorius, P. Wissgott

Computational Methods in Applied Mathematics 11, 460 (2011)

Enhancement of the Na_xCoO_2 thermopower due to electronic correlations

P. Wissgott, A. Toschi, H. Usui, K. Kuroki, K. Held

Phys. Rev. B 82, 201106(R) (2010)

Wien2wannier: From linearized augmented plane waves to maximally localized Wannier functions

J. Kuneš, R. Arita, P. Wissgott, A. Toschi, H. Ikeda, K. Held

Comp. Phys. Commun. 181, 1888 (2010)

Thermopower of Sodium Cobaltate: LDA+DMFT Analysis

P. Wissgott

Diploma thesis, Professor: Karsten Held, Assistant supervisor: Alessandro Toschi, Institute for Solid State Physics, TU Vienna, 2010

A Space-Time Adaptive Algorithm for Linear Parabolic Problems

P. Wissgott

Diploma thesis, Professor: Dirk Praetorius, Institute for Analysis and Scientific Computing, TU Vienna, 2007

Research themes

Genetic AI & evolutionary optimization

Ab initio dynamic multi-objective optimization based on evolutionary games — a complementary approach to machine learning that learns from logical connections in data.

Evolutionary Data Theory

Formalizing the structural parallels between data problems and evolutionary games, including feature weighting via evolutionary simulation.

Correlated electron systems & DMFT

Transport, optical conductivity, and thermopower of correlated materials such as Na_xCoO_2, combining LDA+DMFT with dipole matrix element methods.

First-principles methods & numerical analysis

Wannier functions from linearized augmented plane waves (Wien2wannier) and adaptive finite element methods for parabolic problems.

Collaborators