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Publications

To the HZDR publication and research data repository

Pre-prints

  • 2023

    Maxim Eingorn, Ezgi Yilmaz, A. Emrah Yükselci, Alexander Zhuk, Mass density vs. energy density at cosmological scales. arXiv

    Chethan Krishnamurthy Ramanaik, Juan-Esteban Suarez Cardona, Anna Willmann, Pia Hanfeld, Nico Hoffmann, Michael Hecht, Ensuring Toplogical Data-Structure Preservation under Autoencoder Compression due to Latent Space Regularization in Gauss–Legendre nodes. arXiv

    Janina Schreiber, Damar Wicaksono, Michael Hecht, Polynomial-Model-Based Optimization for Blackbox Objectives. arXiv

    Justin M Calabrese, Lennart Schueler, Xiaoming Fu, Erik Gawel, Heinrich Zozmann, Jan Bumberger, Martin Quaas, Gerome Wolf, Sabine Attinger A novel, scenario-based approach to comparing non-pharmaceutical intervention strategies across nations. medrxiv

    Z. Moldabekov, S.Schwalbe, M. Böhme, J. Vorberger, X. Shao, M. Pavanello, F. Graziani, T. Dornheim Bound state breaking and the importance of thermal exchange-correlation effects in warm dense hydrogen. arXiv

    T. Dornheim, P. Tolias, S. Groth, Z. Moldabekov, J. Vorberger, B. Hirshberg, Fermionic physics from ab initio path integral Monte Carlo simulations of fictitious identical particles. arXiv

    Sruthil Lal S.B, Lokamani, Kushal Ramakrishna, Attila Cangi, D Murali, Matthias Posselt, Assa Aravindh Sasikala Devi, Alok Sharan Ab initio insights on the ultrafast strong-field dynamics of anatase TiO2, arXiv

    I. Silva, C. H. Fleming, M. J. Noonan, W. F. Fagan, J. M. Calabrese, movedesign: Shiny R app to evaluate sampling design for animal tracking movement studies. bioRxiv

    E. Ser-Giacomi, R. Martinez-Garcia, S. Dutkiewicz, M. J. Follows, A Lagrangian model for drifting ecosystems reveals heterogeneity-driven enhancement of marine plankton blooms. arXiv

    T. W. Hentschel, A. Kononov, A. Olmstead, A. Cangi, A. D. Baczewski, S. B. Hansen, Improving dynamic collision frequencies: impacts on dynamic structure factors and stopping powers in warm dense matter. arXiv

    D. Konar, S. Bhattacharyya, T. K. Gandhi, B. K. Panigrahi, R. Jiang, 3D Quantum-inspired Self-supervised Tensor Network for Volumetric Segmentation of Medical Images. techrXiv

    T. Dornheim, D. C. Wicaksono, J. E. Suarez-Cardona, P. Tolias, M. Böhme, Z. Moldabekov, M. Hecht, J. Vorberger, Extraction of the frequency moments of spectral densities from imaginary-time correlation function data. arXiv

    R. Li, M. Kudryashev, A. Yakimovich, A weak-labelling and deep learning approach for infocus object segmentation in 3D widefield microscopy. ResearchSquare

    M. Eingorn, B. O’Briant, A. Diouf, A. Zhuk, Backreaction in cosmic screening approach. arXiv

    R. Tripathi, A. Reza, G. Su, A. Mertel, J. M. Calabrese, A network based approach to identifying correlations between phylogeny, morphological traits and occurrence information of fish Species in US river basins. bioRxiv

    J. E. Suarez-Cardona, P. A. Hofmann, M. Hecht, Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces. arXiv

    M. Davoodi, A. Batista, A. Senapati, J. M. Calabrese, Personnel Scheduling and Testing Strategy during Pandemics: The case of COVID-19. arXiv

    R. Martinez-Garcia, J. M. Calabrese, C. H. Fleming, et al., The search behavior of terrestrial mammals. bioRxiv

  • 2022

    J. E. Suarez-Cardona, M. Hecht, Replacing Automatic Differentiation by Sobolev Cubatures fastens Physics Informed Neural Nets and strengthens their Approximation Power. arXiv

    S. K. Thekke Veettil, Y. Zheng, U. Hernandez Acosta, D. Wicaksono, M. Hecht, Multivariate Polynomial Regression of Euclidean Degree Extends the Stability for Fast Approximations of Trefethen Functions. arXiv

    S. Thekke Veettil, G. Zavalani, U. Hernandez Acosta, I. F. Sbalzarini, M. Hecht, Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces, in review, arXiv

    T. Dornheim, M. Böhme, D. Chapman, D. Kraus, T. R. Preston, Z. Moldabekov, N. Schlünzen, A. Cangi, T. Döppner, J. Vorberger, Temperature analysis of X-ray Thomson scattering data. arXiv

    T. Dornheim, Z. Moldabekov, K. Ramakrishna, P. Tolias, A. D. Baczewski, D. Kraus, T. R. Preston, D. A. Chapman, M. Böhme, T. Döppner, F. Graziani, M. Bonitz, A. Cangi, J. Vorberger, Electronic Density Response of Warm Dense Matter. arXiv

    S. Darapu, S. Ghosh, A. Senapati, C. Hens, S. Nannuru, Identifying influential pandemic regions using graph signal variation. arXiv

    L. Hyman, I. F. Sbalzarini, S. Quake, U. Günther, Corvo: Visualizing CellxGene Single-Cell Datasets in Virtual Reality. arXiv

    Z. A. Moldabekov, M. Lokamani, J. Vorberger, A. Cangi, T. Dornheim, Non-empirical mixing coefficient for hybrid XC functionals from analysis of the XC kernel. arXiv

    A. C. Batista German, A. Senapati, M. Davoodi, J. M. Calabrese, Personnel Staffing and Scheduling During Disease Outbreaks: A Contact Network-Based Analysis. SSRN

    Z. A. Moldabekov, M. Lokamani, J. Vorberger, A. Cangi, T. Dornheim, Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm dense electrons. arXiv

    P. Svensson, T. Campbell, F. Graziani, Z. Moldabekov, N. Lyu, S. Richardson, S. M. Vinko, G. Gregori, Development of a new quantum trajectory molecular dynamics framework. arXiv

    A. Senapati, A. Mertel, W. Schlechte-Welnicz, J. M. Calabrese, Estimating cross-border mobility from the difference in peak-timing: A case study in Poland-Germany border regions. arXiv

    J. Demers, W. F. Fagan, S. Potluri, J. M. Calabrese, The relationship between controllability, optimal testing resource allocation, and incubation-latent period mismatch as revealed by COVID-19. arXiv

    T. Dornheim, J. Vorberger, Z. Moldabekov, M. Böhme, Analyzing X-ray Thomson scattering experiments of warm dense matter in the imaginary-time domain: theoretical models and simulations. arXiv

    L. Fiedler, N. A. Modine, S. Schmerler, D. J. Vogel, G. A. Popoola, A. P. Thompson, S. Rajamanickam, A. Cangi, Predicting the Electronic Structure of Matter on Ultra-Large Scales. arXiv

    K. Ramakrishna, M. Lokamani, A. Baczewski, J. Vorberger, A. Cangi, Electrical and Thermal Conductivity of High-Pressure Solid Iron. arXiv

    K. Shah, P. Stiller, N. Hoffmann, A. Cangi, Physics-Informed Neural Networks as Solvers for the Time-Dependent Schrödinger Equation. arXiv

    S. Bhattacharyya, S. De, L. Mrsic, I. Pan, K. Muhammad, A. Mukherjee, D. Konar, A Quantitative Assessment of Rubrics Using a Soft Computing Approach. Preprints

    J. M. Alston, I. Silva, J. M. Calabrese, et al. Clarifying space use concepts in ecology: range vs. occurrence distributions. bioRxiv

    W. Elwasif, S. Bastrakov, S. H. Bryngelson, M. Bussmann, S. Chandrasekaran, J. Stephan, et al. Early Application Experiences on a Modern GPU-Accelerated Arm-based HPC Platform. arXiv

    T. Dornheim, Z. A. Moldabekov, P. Tolias, M. Böhme, J. Vorberger, Physical insights from imaginary-time density–density correlation functions. arXiv

    Z. A. Moldabekov, M. Böhme, J. Vorberger, D. Blaschke, T. Dornheim, Ab initio Computation of the Static Exchange–Correlation Kernel of Real Materials: From Ambient Conditions to Warm Dense Matter. arXiv

    W. Abdussalam, A. Mertel, K. Fan, L. Schüler, W. Schlechte-Wełnicz, J. M. Calabrese, A scalable pipeline for COVID-19: the case study of Germany, Czechia and Poland. arXiv

    M. Böhme, Z. A. Moldabekov, J. Vorberger, T. Dornheim, Ab initio path integral Monte Carlo simulations of hydrogen snapshots at warm dense matter conditions. arXiv

    A. Gupta, P. Incardona, P. Hunt, G. Reina, S. Frey, S. Gumhold, U. Günther, I. F. Sbalzarini, Content-adaptive generation and parallel compositing of volumetric depth images for responsive visualization of large volume data. arXiv

    T. Dornheim, M. Böhme, D. Kraus, T. Döppner, T. Preston, Z. Moldabekov, J. Vorberger, Accurate Temperature Diagnostics for Matter under Extreme Conditions. arXiv

    A. Gupta, U. Günther, P. Incardona, G. Reina, S. Frey, S. Gumhold, I. F. Sbalzarini, Efficient Raycasting of View-Dependent Piecewise Constant Representations of Volumetric Data. arXiv

    L. Fiedler, Z. A. Moldabekov, X. Shao, K. Jiang, T. Dornheim, M. Pavanello, A. Cangi, Accelerating Equilibration in First-Principles Molecular Dynamics with Orbital-Free Density Functional Theory. arXiv

    T. Callow, D. Kotik, E. Kraisler, A. Cangi, AtoMEC: an open-source average-atom Python code. arXiv

    M. Schörner, B. B. L. Witte, A. D. Baczewski, A. Cangi, R. Redmer, An \textit{ab initio} study of shock-compressed copper. arXiv

    T. Dornheim, J. Vorberger, Z. Moldabekov, P. Tolias, Spin-resolved density response of the warm dense electron gas. arXiv

    T. Dornheim, P. Tolias, Z. Moldabekov, A. Cangi, J. Vorberger, Effective electronic forces and potentials from ab initio path integral Monte Carlo simulations. arXiv

    D. R. Vemula, D. Konar, S. Satheesan, S. M. Kalidasu, A. Cangi, A Scalable 5,6-Qubit Grover’s Quantum Search Algorithm. arXiv

    J. M. Alston, C. H. Fleming,  R. Kays,  J. P. Streicher,  C. T. Downs,  T. Ramesh,  J. M. Calabrese, Mitigating pseudoreplication and bias in resource selection functions with autocorrelation-informed weighting. bioRxiv

    M. Davoodi, A. Batista, A. Senapati, W. Schlechte-Welnicz, B. Wagner, J. M. Calabrese, Modeling COVID-19 optimal testing strategies in long-term care facilities: An optimization-based approach. arXiv

    M. Davoodi, A. Senapati, A. Mertel, W. Schlechte-Welnicz, J. M. Calabrese, Optimal Workplace Occupancy Strategies during the COVID-19 Pandemic. arXiv

    T. Dornheim, Z. Moldabekov, J. Vorberger, H. Kählert, M. Bonitz, Electronic pair alignment and roton feature in the warm dense electron gas. arXiv

    K. Ramakrishna, M. Lokamani, A. Baczewski, J. Vorberger, A. Cangi, Electrical Conductivity of Iron in Earth’s Core from Microscopic Ohm’s Law. arXiv

    T. Callow, E. Kraisler, A. Cangi, Accurate and efficient computation of mean ionization states with an average-atom Kubo-Greenwood approach. arXiv

    G. Su, A. Mertel, S. Brosse, J. M. Calabrese, Species invasiveness and community invasibility of US freshwater fish fauna revealed via trait-based analysis. bioRxiv

    M. Böhme, Z. Moldabekov, J. Vorberger, T. Dornheim, Electronic Density Response of Warm Dense Hydrogen: Ab initio Path Integral Monte Carlo Simulations. arXiv

    D. Konar, E. Gelenbe, S. Bhandary, A. Das Sarma, A. Cangi, Random Quantum Neural Networks (RQNN) for Noisy Image Recognition. arXiv

    A. Mertel, J. Vyskočil, L. Schüler, W. Schlechte-Wełnicz, J. M. Calabrese, Fine-scale variation in the effect of national border on COVID-19 spread: A case study of the Saxon-Czech border region. medRxiv

    T. Dornheim, J. Vorberger, Z. Moldabekov, G. Röpke, W. Kraeft, The uniform electron gas at high temperatures: \emph{ab initio} path integral Monte Carlo simulations and analytical theory. arXiv

    Z. Moldabekov, J. Vorberger, T. Dornheim, Density-Functional-Theory Perspective on the Non-Linear Response of Correlated Electrons Across Temperature Regimes. arXiv

    T. Dornheim, Abnormal superfluid fraction and structural properties of electrons in 2D and 3D quantum dots: an ab initio path-integral Monte Carlo study. arXiv

  • 2021

    T. Dornheim, P. Tolias, S. Groth, Z. Moldabekov, J. Vorberger, B. Hirshberg, Fermionic physics from ab initio path integral Monte Carlo simulations of fictitious identical particles. arXiv

    T. Dornheim, J. Vorberger, Z. A. Moldabekov, M. Bonitz, Nonlinear electronic density response of the warm dense electron gas: multiple perturbations and mode coupling. arXiv

    S. Müller, L. Schüler, A. Zech, F. Heße, GSTools v1.3: A toolbox for geostatistical modelling in Python. gmd

    M. Roy, A. Senapati, S. Poria, A. Mishra, C. Hens, Role of assortativity in predicting burst synchronization using echo state network. arXiv

    I. Silva, J. M. Calabrese, Emerging opportunities for wildlife with sustainable autonomous transportation. EcoEvoRxiv

    A.I. Titov, U. Hernandez Acosta, B. Kampfer, Positron energy distribution in factorized trident process. arXiv

    Y. Montano, B. M. Marshall, M. Ward, I. Silva, T. Artchawakom, S. Waengsothorn, C. Strine, A stable home: Autocorrelated Kernel Density Estimated home ranges of the critically endangered Elongated Tortoise. OSF

    J. M. Alston, D. A. Keinath, C. K. R. Willis, C.L. Lausen, J. M. O’Keefe, J. D. Tyburec, H. G. Broders, P. R. Moosman, T. C. Carter, C. L. Chambers, E. H. Gillam, K. Geluso, T. J. Weller, D. W. Burles, Q. E. Fletcher, K. J. O. Norquay, J. R. Goheen, Environmental drivers of body size in North American bats. arXiv

    F. Pöschel, J. E, W. F. Godoy, N. Podhorszki, S. Klasky, G. Eisenhauer, P. E. Davis, L. Wan, A. Gainaru, J. Gu, F. Koller, R. Widera, M. Bussmann, A. Huebl, Transitioning from file-based HPC workflows to streaming data pipelines with openPMD and ADIOS2. arXiv

    N. Kumar, P. Hanfeld, M. Hecht, M. Bussmann, S. Gumhold, N. Hoffmannn, InFlow: Robust outlier detection utilizing Normalizing Flows. arXiv

    B. M. Gruber, G. Amadio, J. Blomer, A. Matthes, R. Widera, M. Bussmann, LLAMA: The Low Level Abstraction For Memory Access. arXiv

    Z. Moldabekov, T. Dornheim, G. Gregori, F. Graziani, M. Bonitz, A. Cangi, The Quantum Bohm Potential for Many-Fermion Systems. arXiv

    J. L. Brunner, J. M. Calabrese, Modelling the probability of detecting mass mortality events. bioRxiv

    R. Martinez-Garcia, C. Cabal, J. A. Bonachela, J. M. Calabrese, E. Hernández-García, C. López, C. E. Tarnita: Spatial self-organization of vegetation in water-limited systems: mechanistic causes, empirical tests, and ecosystem-level consequences. arXiv

    Z. Moldabekov, T. Dornheim, M. Bonitz: Screening of a test charge in a free-electron gas at warm dense matter and dense non-ideal plasma conditions. arXiv

    C. H. Fleming, J. Drescher-Lehman, M. J. Noonan, T. S. B. Akre, D. J. Brown, M. M. Cochrane, N. Dejid, V. DeNicola, C. S. DePerno, J. N. Dunlop, N. P. Gould, J. Hollins, H. Ishii, Y. Kaneko, R. Kays, S. S. Killen, B. Koeck, S. A. Lambertucci, S. D. LaPoint, E. P. Medici, B.-U. Meyburg, T. A. Miller, R. A. Moen, T. Mueller, T. Pfeiffer, K. N. Pike, A. Roulin, K. Safi, R. Séchaud, A. K. Scharf, J. M. Shephard, J. A. Stabach, K. Stein, C. M. Tonra, K. Yamazaki, W. F. Fagan, J. M. Calabrese: A comprehensive framework for handling location error in animal tracking data. DOI: 10.1101/2020.06.12.130195 / bioRxiv

Scientific and public talks

  • 2023

    W. Elwasif, W. Godoy, N. Hagerty, J. Austin Harris, O. Hernandez, B. Joo, P. Kent, D. Lebrun-Grandie, E. Maccarthy, V. Melesse Vergara, B. Messer, R. Miller, S. Oral, S. Bastrakov, M. Bussmann, A. Debus, K. Steiniger, J. Stephan, R. Widera, S. Bryngelson, H. Le Berre, A. Radhakrishnan, J. Young, S. Chandrasekaran, F. Ciorba, O. Simsek, K. Clark, F. Spiga, J. Hammond, S. John, D. Hardy, S. Keller, J.-G. Piccinali, C. Trott. Application Experiences on a GPU-Accelerated Arm-based HPC Testbed. In Proceedings of the HPC Asia 2023 Workshops (HPC Asia ’23 Workshops). Association for Computing Machinery, New York, NY, USA, 35–49. (2023)

  • 2022
    • R. Tripathi, A. Reza, J. M. Calabrese, Role of Network Topology in Between-Community Beta Diversity on River Networks, Complex Networks and Their Applications XI. COMPLEX NETWORKS 2016 2022. Studies in Computational Intelligence, vol 1078.
    • M. Hecht, Z. Shao, S. B. Jain, Adversarial attacks for machine learning denoisers and how to resist them, Emerging Topics in Artificial Intelligence (ETAI), 21.-25.08.2022, San Diego, USA
    • M. Hecht, Multivariate Interpolation in Non-Tensorial Nodes May Lift the Curse of Dimensionality for Trefethen functions, CCM Colloquium, Simons Foundation, Flatiron Institute, New York City, USA, 2022
    • M. Hecht, Multivariate Interpolation in Non-Tensorial Nodes May Lift the Curse of Dimensionality for Trefethen functions, BSC Life Science Seminar, Barcelona Supercomputing Center (BSC), Barcelona, Spain, 2022
    • D. Konar, Hybrid Classical-Quantum Machine Learning Algorithms for Large Scale Applications, 11th IEEE International Conference on CSNT, 23-24.04.2022
    • K. Ramakrishna, J. Vorberger, A. D. Baczewski, M. Lokamani, A. Cangi, Electrical Conductivity of Iron under Earth-Core Conditions from Time-Dependent Density Functional Theory, APS March Meeting 2022, 14.03.2022
    • S. Nikolov, J. Tranchida, A. Cangi, K. Ramakrishna, M. A. Wood, Probing Structural and Magnetic Phase Changes in the Shock Response of Iron with Molecular Dynamics, APS March Meeting 2022, 15.03.2022
    • T. J. Callow, N. E. Rahat, E. Kraisler, A. Cangi, Comparisons of density-functional average-atom models and measures of the mean ionization state, APS March Meeting 2022, 15.03.2022
    • L. Fiedler, G. A. Popoola, N. A. Modine, A. P. Thompson, A. Cangi, Size transferability of machine-learning based density functional theory surrogates, APS March Meeting 2022, 15.03.2022
    • K. Shah, A. Cangi, Accelerating Time-Dependent Density Functional Theory with Physics-Informed Neural Networks, APS March Meeting 2022, 16.03.2022
    • T. Hentschel, A. Kononov, A. D. Baczewski, A. Cangi, S. B. Hansen, Effects of electron-ion collisions on stopping powers in warm dense matter, APS March Meeting 2022, 16.03.2022
  • 2021
    • A. Cangi, Data-driven and physics-informed modeling of matter under extreme conditions, CFEL-DESY, 15.12.2021
    • A. Mertel, J. Calabrese, Modeling the effect of the national borders in the spread of COVID-19: A case study of the Saxony-Czechia border region, International Symposium on Geospatial Approaches to Combating Covid-19, 13.12.2021
    • A. Mertel, Geographical data analysis in the historical research, LINDAT CLARIAH-CZ Talk, 12.11.2021
    • F. Poeschel, A. Huebl, Towards loosely-coupled scientific I/O pipelines with openPMD-api and ADIOS2, SMC2021, 22.07.2021
    • T. Callow, Density-functional average-atom model for first-principles simulations of warm dense matter, AMCP-Seminar, Universität Rostock, 01.06.2021
    • D. Zbíral, A. Mertel, R. Shaw, T. Hampejs, An ontology for modelling the social, spatial, and semantic relations in pre-modern written sources: Takeaways from data model development in the Dissident Networks Project (DISSINET), Data for History. Modelling Time, Places, Agents, 19.05.-30.06.2021
    • K. Ramakrishna, J. Vorberger, A. Cangi, Electrical conductivity of materials under extreme conditions using TDDFT, APS March Meeting 2021, 19.03.2021
    • T. J. Callow, E. Kraisler, S. B. Hansen, E. K. Gross, A. Cangi, First-principles derivation of an average-atom model from the many-body Hamiltonian of coupled electrons and ions, APS March Meeting 2021, 19.03.2021
    • T. Dornheim, A. Cangi, K. Ramakrishna, M. Boehme, J. Vorberger, Effective Static Approximation: A fast and reliable tool for Warm Dense Matter Theory, APS March Meeting 2021, 19.03.2021
    • A. Kononov, T. Hentschel, A. Cangi, A. D. Baczewski, S. B. Hansen, Comparison of DFT-based methods for electronic stopping in warm dense aluminum, APS March Meeting 2021, 17.03.2021
    • A. Cangi, J. A. Ellis, N. A. Modine, J. Adam Stephens, A. P. Thompson, S. Rajamanickam, Accelerating Finite-Temperature Kohn-Sham Density Functional Theory with Deep Neural Networks, APS March Meeting 2021, 15.03.2021
  • 2020
  • 2019
    • M. Bussmann, Invited Talk Semestereröffnung IHI Zittau 2019
    • U. Günther et al., Das beste aus beiden Welten, bei: CAPTCHA! Maschinen lernen Handeln von Menschen, die nicht verstehen, was sie wissen, Schwarzmarkt für nützliches Wissen und Nicht-Wissen Nr. 23, Deutsches Hygiene-Museum Dresden, 06.12.2019
    • T. Dornheim et al., Seminar Talk National University of Defense Technology, Changsha, China
    • T. Dornheim et al., Invited Talk Division of Plasma Physics meeting of the AAPPS, Hefei, China, November 2019
    • M. Bussmann et al., Warum kompliziert wenn es auch komplex geht? Wie digitale Systemforschung aus Daten Wissen macht, Invited Talk Senckenberg Museum für Naturkunde Görlitz, 19.11.2019
    • S. Chandrasekaran et al., Running PIConGPU on Summit, CAAR: Preparing PIConGPU for Frontier @ ORNL, Supercomputing 19, Denver, Colorado
    • M. Bussmann et al., Data Management & Analysis: The challenge of complexity and how to attack it, Invited Talk 1st Annual Meeting of the Photon and Neutron Open Science Cloud, Trieste, 05.11.2019
    • U. Günther et al., Virtual Reality for Bioimage Informatics, Chan-Zuckerberg Biohub, San Francisco, 01.11.2019
    • U. Günther et al., Scenery: Flexible Virtual Reality Visualisation on the Java VM, IEEE VIS 2019, Vancouver, 24.10.2019
    • T. Dornheim et al., Vortrag 9th Joint Workshop on High Pressure, Planetary and Plasma Physics (HP4), Dresden, Germany, Oktober 2019
    • M. Bussmann et al., Data-intensive methods for complex systems analysis, Invited Talk S3 Seminar, WUST, Wroclaw, 17.10.2019
    • M. Bussmann et al., Data intensive Systems Science, Invited Talk Hugo Steinhaus Seminar, WUST, Wroclaw, 16.10.2019
    • M. Bussmann et al., Write once, run everywhere: ALPAKA for single-source many-core programming in C++, Invited Talk CMS week, CERN, 25.09.2019
    • M. Bussmann et al., Interactive, data-intensive HPC, Eingeladener Vortrag CERN EP-IT Data Science Seminar, 25.09.2019
    • U. Günther et al., Fortbildung Virtual & Augmented Reality für Gymnasiallehrer, CSBD Dresden, 30.08.2019
    • M. Bussmann, Öffentlicher Abendvortrag Senckenberg Museum für Naturkunde Görlitz, 27.08.2019
    • T. Dornheim et al., Vortrag 10th International Workshop on Warm-Dense-Matter 2019, Travemünde, Germany, Mai 2019
    • T. Dornheim et al., Vortrag International Conference on High Energy Density (ICHED), Oxford, United Kingdom, April 2019