DTU DRIVEN publication track record

1. MORADI SHAHMANSOURI, P. (2025). Asymptotics and Sustainability in Operations Management [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/67188

2. DIDIER, J. (2025). Machine learning-based Identification of Biomarkers in Clinical Cohort and Cancer Cell Line Data [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/67777

3. SALEHIAN GHAMSARI, S. (2025). BRIDGING REMOTE SENSING AND HYDROGEOLOGY: STOCHASTIC MODELING OF ANISOTROPIC HYDRAULIC CONDUCTIVITY FOR AQUIFER CHARACTERIZATION USING INSAR [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/65882

4. NAVARRO BUENDÍA, R. (2025). Precision Altimetry Using Dual-Frequency Grazing Angle GNSS-R [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/64646

5. HURTADO CATHALIFAUD, D. R. (2025). Optimization solvers and machine learning to enhance quasi-static unilateral contact simulations [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/64458

6. MONTORSI, C. (2024). Empirical Essays on Well-Being [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/62916

7. MINGO NDIWAGO, D. (2024). BAYESIAN MODEL SELECTION AND PRIOR IMPACT ASSESSMENT WITH A FOCUS ON DYNAMICAL SYSTEMS [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/64536

8. INFANTI, A. (2024). The use of machine learning to improve the identification and assessment of internet-related disorders [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/61507

9. DALLE LUCCA TOSI, M. (2024). Online Learning Using Distributed Neural Networks [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/60837

10. GOGER, S. (2023). Development of Practical Non-Local Many-Body Polarization Functionals [Doctoral thesis, Unilu - Université du Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/57536

11. KALAITZIDOU, C. (2023). Unveiling the Hidden Language of Extracellular Matrix Deformations: A tale of cellular whispers and unstable fibers [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/57328

12. CHÂU, M. V. (2023). Constitutive Modelling of Non-Linear Isotropic Elasticity Using Deep Regression Neural Networks [Doctoral thesis, Unilu - Université du Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/60071

13. USLU, S. (2023). Exploring personalized approaches for neurofeedback optimization [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/57133

14. DARLIK, F. (2023). PHYSICALLY INFORMED NEURAL NETWORKS TO REPRESENT MOTION OF GRANULAR MATERIAL [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/60405

15. CHEN, N. (2023). Decoding the Real World: Tackling Virtual Ethnographic Challenges through Data-Driven Methods [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55503

16. KOZLOWSKI, D. (2023). Topics and institutions in the reproduction of intersectional inequalities in science [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55491

17. VITELLO, P. (2023). CROWDSOURCED DATA FOR MOBILITY ANALYSIS [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55175

18. TAYE, A. D. (2023). Essays on the Prediction and Measurement of Individual Well-being [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55174

19. SHANG, L. (2022). MODELING, SIMULATION, AND ELECTRODE OPTIMIZATION OF FLOW-DRIVEN PIEZOELECTRIC ENERGY HARVESTERS [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52953

20. GENTILE, N. (2022). Essays on the Economics of Wellbeing and Machine Learning [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52442

21. FARINA, S. (2022). Modelling astrocytic metabolism in actual cell morphologies [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52460

22. AMELI, C. (2022). Dissecting Complex Microglia Heterogeneity in Neurodegeneration [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/50428

23. MINGO NDIWAGO, D., HALE, J., & LEY, C. (01 March 2026). Bayesian prior impact assessment for dynamical systems described by ordinary differential equations. Heliyon, 12 (4), 44634. doi:10.1016/j.heliyon.2026.e44634

24. SALEHIAN GHAMSARI, S., Van Dam, T., & HALE, J. (01 June 2025). Can the anisotropic hydraulic conductivity of an aquifer be determined using surface displacement data? A case study. Applied Computing and Geosciences, 26, 100242. doi:10.1016/j.acags.2025.100242

25. MINGO NDIWAGO, D., Nijzink, R., LEY, C., & HALE, J. (12 March 2025). Selecting a conceptual hydrological model using Bayes' factors computed with replica exchange Hamiltonian Monte Carlo and thermodynamic integration. Geoscientific Model Development, 18 (5), 1709-1736. doi:10.5194/gmd-18-1709-2025

26. VITELLO, P., FIANDRINO, C., CONNORS, R., & VITI, F. (13 April 2024). TransitCrowd: Estimating Subway Stations Demand with Mobile Crowdsensing Data. Data Science for Transportation, 6 (2). doi:10.1007/s42421-024-00091-4

27. CHEN, N., CHEN, X., ZHONG, Z., & PANG, J. (05 January 2024). Bridging Performance of X (formerly known as Twitter) Users: A Predictor of Subjective Well-Being During the Pandemic. ACM Transactions on the Web, 18 (1), 1-23. doi:10.1145/3635033

28. CHEN, N., CHEN, X., ZHONG, Z., & PANG, J. (2024). A tale of two roles: exploring topic-specific susceptibility and influence in cascade prediction. Data Mining and Knowledge Discovery, 38 (1), 79 - 109. doi:10.1007/s10618-023-00953-5

29. VITELLO, P., CONNORS, R., & VITI, F. (2024). Leveraging Crowdsourced Activity Information for Transit Stations Flow Estimation. IEEE Access, 12, 167518 - 167529. doi:10.1109/ACCESS.2024.3494012

30. Montorsi, C., FUSCO, A., VAN KERM, P., & BORDAS, S. (November 2023). Predicting depression in old age: Combining life course data with machine learning. Economics and Human Biology, 52, 101331. doi:10.1016/j.ehb.2023.101331

31. Buendía, R. N., TABIBI, S., Talpe, M., & Otosaka, I. (November 2023). Ice sheet height retrievals from Spire grazing angle GNSS-R. Remote Sensing of Environment, 297, 113757. doi:10.1016/j.rse.2023.113757

32. TKATCHENKO, A., GOGER, S., KHABIBRAKHMANOV, A., VACCARELLI, O., & FEDOROV, D. (2023). Optimized Quantum Drude Oscillators for Atomic and Molecular Response Properties. Journal of Physical Chemistry Letters. doi:10.1021/acs.jpclett.3c01221

33. USLU, S., & Vögele, C. (2023). The more, the better? Learning rate and self-pacing in neurofeedback enhance cognitive performance in healthy adults. Frontiers in Human Neuroscience. doi:10.3389/fnhum.2023.1077039

34. SHANG, L., Hoareau, C., & ZILIAN, A. (2023). Optimal electrode coverage based on a new criterion for piezoelectric energy harvesters. Energy Conversion and Management, 284, 116982. doi:10.1016/j.enconman.2023.116982

35. DARLIK, F., & PETERS, B. (2023). Reconstruct the biomass particles fields in the particle-fluid problem using continuum methods by applying the physics-informed neural network. Results in Engineering, 17, 100917. doi:10.1016/j.rineng.2023.100917

36. DEHGHANI, H., & ZILIAN, A. (2023). Finite strain poro-hyperelasticity: an asymptotic multi-scale ALE-FSI approach supported by ANNs. Computational Mechanics. doi:10.1007/s00466-022-02262-y

37. CHEN, N., CHEN, X., & PANG, J. (October 2022). A multilingual dataset of COVID-19 vaccination attitudes on Twitter. Data in Brief, 44, 108503. doi:10.1016/j.dib.2022.108503

38. KOZLOWSKI, D., Lozano, G., Fletcher, C. M., Gonzalez, F., & Altszyler, E. (2022). Large-scale computational content analysis on magazines targeting men and women: the case of Argentina 2008-2018. Feminist Media Studies. doi:10.1080/14680777.2022.2047090

39. KOZLOWSKI, D., Murray, D. S., Bell, A., Husley, W., Larivière, V., & Sugmioto, C. R. (01 March 2022). Avoiding bias when inferring race using name-based approaches. PLoS ONE, 3 (17), 0264270. doi:10.1371/journal.pone.0264270

40. SZABO, P., GOGER, S., CHARRY MARTINEZ, J. A., KARIMPOUR, M. R., FEDOROV, D., & TKATCHENKO, A. (2022). Four-Dimensional Scaling of Dipole Polarizability in Quantum Systems. Physical Review Letters. doi:10.1103/PhysRevLett.128.070602

41. KOZLOWSKI, D., Larivière, V., Sugimoto, C. R., & Monroe-White, T. (11 January 2022). Intersectional Inequalities in Science. Proceedings of the National Academy of Sciences of the United States of America, 119 (2), 2113067119. doi:10.1073/pnas.2113067119

42. DARLIK, F., ADHAV, P., & PETERS, B. (2022). Prediction of the biomass particles through the physics informed neural network. ECCOMAS Congress 2022 - 8th European Congress on Computational Methods in Applied Sciences and Engineering. doi:10.23967/eccomas.2022.223

43. CHEN, N., CHEN, X., ZHONG, Z., & PANG, J. (2022). Exploring Spillover Effects for COVID-19 Cascade Prediction. Entropy, 24 (2). doi:10.3390/e24020222

44. SHANG, L., Hoareau, C., & ZILIAN, A. (2022). Modeling and simulation of thin-walled piezoelectric energy harvesters immersed in flow using monolithic fluid–structure interaction. Finite Elements in Analysis and Design, 206, 103761. doi:10.1016/j.finel.2022.103761

45. KOZLOWSKI, D., DUSDAL, J., PANG, J., & ZILIAN, A. (2021). Semantic and Relational Spaces in Science of Science: Deep Learning Models for Article Vectorisation. Scientometrics. doi:10.1007/s11192-021-03984-1

46. DEHGHANI, H., & ZILIAN, A. (2021). ANN-aided incremental multiscale-remodelling-based finite strain poroelasticity. Computational Mechanics. doi:10.1007/s00466-021-02023-3

47. VITELLO, P., CONNORS, R., & VITI, F. (2021). The Impact of SARS-COVID-19 Outbreak on European Cities Urban Mobility. Frontiers in Future Transportation. doi:10.3389/ffutr.2021.666212

48. FARINA, S., Claus, S., HALE, J., SKUPIN, A., & BORDAS, S. (22 March 2021). A cut finite element method for spatially resolved energy metabolism models in complex neuro-cell morphologies with minimal remeshing. Advanced Modeling and Simulation in Engineering Sciences, 8, 5. doi:10.1186/s40323-021-00191-8

49. KOZLOWSKI, D., Semeshenko, V., & Molinari, A. (04 February 2021). Latent Dirichlet Allocation Models for World Trade Analysis. PLoS ONE, 16 (2), 0245393. doi:10.1371/journal.pone.0245393

50. VITELLO, P., CAPPONI, A., FIANDRINO, C., CANTELMO, G., & KLIAZOVICH, D. (2021). Mobility-Driven and Energy-Efficient Deployment of Edge Data Centers in Urban Environments. IEEE Transactions on Sustainable Computing. doi:10.1109/TSUSC.2021.3056621

51. CHEN, N., ZHONG, Z., & PANG, J. (2021). An Exploratory Study of COVID-19 Information on Twitter in the Greater Region. Big Data and Cognitive Computing, 5 (1), 5. doi:10.3390/bdcc5010005

52. SHANG, L., Hoareau, C., & ZILIAN, A. (2021). A geometrically nonlinear shear deformable beam model for piezoelectric energy harvesters. Acta Mechanica, 232 (12), 4847-4866. doi:10.1007/s00707-021-03083-5

53. DEHGHANI, H., & ZILIAN, A. (September 2020). Poroelastic model parameter identification using artificial neural networks: on the effects of heterogeneous porosity and solid matrix Poisson ratio. Computational Mechanics, 66, 625-649. doi:10.1007/s00466-020-01868-4

54. DALLE LUCCA TOSI, M., & THEOBALD, M. (2024). OPTWIN: Drift Identification with Optimal Sub-Windows. 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW). doi:10.1109/icdew61823.2024.00049

55. DALLE LUCCA TOSI, M., Venugopal, V. E., & THEOBALD, M. (2024). TensAIR: Real-Time Training of Neural Networks from Data-streams. In ICMLSC '24: Proceedings of the 2024 8th International Conference on Machine Learning and Soft Computing (pp. 73-82). Association for Computing Machinery. doi:10.1145/3647750.3647762

56. Buendía, R. N., TABIBI, S., & Talpe, M. (2023). An Improved Ionospheric Correction Model for Grazing Angle GNSS-R Altimetry. IEEE International Geoscience and Remote Sensing Symposium, 4332–4335. doi:10.1109/IGARSS52108.2023.10282507

57. CHEN, N., CHEN, X., ZHONG, Z., & PANG, J. (2023). The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users During the COVID-19 Pandemic [Paper presentation]. Joint European Conference on Machine Learning and Knowledge Discovery in Databases, France. doi:10.1007/978-3-031-26390-3_15

58. TEMPERONI, A., DALLE LUCCA TOSI, M., & THEOBALD, M. (2023). Efficient Hessian-based DNN Optimization via Chain-Rule Approximation. In Proceedings of the 6th Joint International Conference on Data Science Management of Data (10th ACM IKDD CODS and 28th COMAD) (pp. 297--298).

59. CHEN, N., CHEN, X., PANG, J., BORGA, L., d'Ambrosio, C., & Vögele, C. (2022). Measuring COVID-19 Vaccine Hesitancy: Consistency of Social Media with Surveys. Lecture Notes in Computer Science, 196–210. doi:10.1007/978-3-031-19097-1_12

60. KOZLOWSKI, D., Larivière, V., Sugimoto, C. R., & Monroe-White, T. (2022). Institutional determinants of intersectional inequalities in science. In BRIDGES BETWEEN DISCIPLINES: GENDER IN STEM AND SOCIAL SCIENCES. Transmitting Science.

61. INFANTI, A., Starcevic, V., Schimmenti, A., Khazaal, Y., Karila, L., Giardina, A., Flayelle, M., Baggio, S., Vögele, C., & Billieux, J. (2022). Predictors of cyberchondria during the COVID-19 pandemic: A supervised machine learning approach. Journal of Behavioral Addictions, 73. doi:10.1556/2006.2022.00700

62. DALLE LUCCA TOSI, M., Ellampallil Venugopal, V., & THEOBALD, M. (2022). Convergence time analysis of Asynchronous Distributed Artificial Neural Networks. In 5th Joint International Conference on Data Science Management of Data (9th ACM IKDD CODS and 27th COMAD) (pp. 314--315).

63. Fazio, M., VITELLO, P., PINEDA JARAMILLO, J. D., CONNORS, R., & VITI, F. (2022). A Classification Approach Using Machine Learning for Predicting Traffic Flows in Areas with Missing Sensors. In Transportation Research Board 101st Annual Meeting.

64. CCHEN, N., CHEN, X., Zhong, Z., & PANG, J. (2021). From #jobsearch to #mask: improving COVID-19 cascade prediction with spillover effects. Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 455–462. doi:10.1145/3487351.3488555

65. KOZLOWSKI, D., Murray, D. S., Bell, A., Husley, W., Larivière, V., Monroe-White, & Sugimoto, C. R. (2021). Avoiding bias when inferring race using name-based approaches. In 18th INTERNATIONAL CONFERENCE ON SCIENTOMETRICS & INFORMETRICS, 12–15 July 2021KU Leuven, Belgium (pp. 597-608).

66. Cantelmo, G., VITELLO, P., Toader, B., Antoniou, C., & VITI, F. (January 2020). Inferring Urban Mobility and Habits from User Location History. Transportation Research Procedia, 47, 283-290. doi:10.1016/j.trpro.2020.03.100

67. VITELLO, P., CAPPONI, A., FIANDRINO, C., CANTELMO, G., & KLIAZOVICH, D. (2019). The Impact of Human Mobility on Edge Data Center Deployment in Urban Environments. In IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, 2019.

68. CAPPONI, A., VITELLO, P., FIANDRINO, C., CANTELMO, G., KLIAZOVICH, D., SORGER, U., & BOUVRY, P. (2019). Crowdsensed Data Learning-Driven Prediction of Local Businesses Attractiveness in Smart Cities. In IEEE Symposium on Computers and Communications (ISCC), Barcelona, Spain, 2019.

69. CECCHINI, V. F., NGUYEN, T.-P., PFAU, T., DE LANDTSHEER, S., & SAUTER, T. (2019). An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction. In V. F. CECCHINI, An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction (1st ed, pp. 5). Da Nang, Vietnam: DA NANG PUBLISHING HOUSE.

70. SALEHIAN GHAMSARI, S., van Dam, T., & HALE, J. (2025). A random model of anisotropic hydraulic conductivity tailored to the InSAR-based analysis of aquifers. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/65440.

71. DALLE LUCCA TOSI, M., & THEOBALD, M. (2023). Convergence Analysis of Decentralized ASGD. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/56001.

72. DALLE LUCCA TOSI, M., & THEOBALD, M. (2023). OPTWIN: Drift identification with optimal sub-windows. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55440.

73. DALLE LUCCA TOSI, M., ELLAMPALLIL VENUGOPAL, V., & THEOBALD, M. (2022). TensAIR: Real-Time Training of Neural Networks from Data-streams. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/54534.

93. HALE, J. (2024). Tractable computation of Bayes factors for robust model selection in the physical sciences [Paper presentation]. Probability and Statistics Seminar, Luxembourg.

94. KOZLOWSKI, D. (16 November 2022). Intersectional Inequalities in Science [Paper presentation]. CREST colloquium, Stellenbosch, South Africa.

95. FARINA, S. (10 June 2022). A Mechanistic Multiscale Metabolic Model in Human Astrocytes [Paper presentation]. EMIx Workshop, Oslo, Norway.

96. MONTORSI, C., & CLARK, A. (18 May 2022). The effects of Parental Retirement on Adult Children Well-Being [Paper presentation]. PhD Colloquium.

97. CHAU, M. V., & ZILIAN, A. (04 April 2022). Data-driven constitutive laws for hyperelasticity in principal space: numerical challenges and remedies [Paper presentation]. 18th European Mechanics of Materials Conference, Oxford, United Kingdom.

98. SALEHIAN GHAMSARI, S. (22 March 2022). InSAR for climate change [Paper presentation]. Doctoral Programme in Computational Sciences (DPCS) presentations workshop, Esch-Sur-Alzette, Luxembourg.

99. DEHGHANI, H., & ZILIAN, A. (January 2022). AI-supported Modelling of Brain tissue as Soft Multiscale Multiphysics (Poroelastic) medium [Paper presentation]. Interdisciplinary meeting for brain tissue modelling.

100. KOZLOWSKI, D. (06 December 2021). Intersectional Inequalities in Science [Paper presentation]. Science Studies Colloquium, Online, Denmark.

101. MINGO NDIWAGO, D. (21 May 2021). Uncertainty, precision and reliability of eco-hydrological models [Paper presentation]. DTU DRIVEN Colloquium, University of Luxembourg, Luxembourg.

102. MONTORSI, C. (21 May 2021). Predicting well being in old age [Paper presentation]. DTU-Driven Colloquium, University of Luxembourg, Luxembourg.

103. FARINA, S., Claus, S., HALE, J., VOORSLUIJS, V., SKUPIN, A., & BORDAS, S. (May 2021). Mechanistic modelling of astrocytic metabolism in physiological geometries reveals spatiotemporal effects potentially driving neurodegeneration [Paper presentation]. DTU DRIVEN Colloquium.

104. SALEHIAN GHAMSARI, S., van Dam, T., & HALE, J. (21 November 2025). Linking Ground Deformation to Subsurface Anisotropy: Integrating InSAR, PDE Modeling, and Bayesian Inference [Paper presentation]. 103rd JLG dedicated to slow moving landslides with a special focus on Central Nepal, Dommeldange, Luxembourg.

105. VITELLO, P., FIANDRINO, C., CONNORS, R., & VITI, F. (2023). Exploring the potential of Google Popular Times for transit demand estimation [Paper presentation]. Transportation Research Board (TRB) 102nd Annual Meeting.

106. SALEHIAN GHAMSARI, S., VAN DAM, T., & HALE, J. (2023). Towards assimilating SAR data into an anisotropic model of an underground aquifer [Paper presentation]. The European Geosciences Union (EGU) General Assembly 2023, Vienna, Austria.

107. MONTORSI, C. (24 November 2022). Predicting depression in old age: Combining life course data with machine learning [Paper presentation]. PhD conference in Social Science.

108. MONTORSI, C. (06 October 2022). Predicting depression in old age: Combining life course data with machine learning [Paper presentation]. SHARE 7th User Conference.

109. FARINA, S., VOORSLUIJS, V., Fixemer, S., BOUVIER, D., Claus, S., BORDAS, S., & SKUPIN, A. (2022). 3D Modelling of a Spatially Resolved Energy Metabolism in Physiological Astrocytic Morphology [Paper presentation]. ECMTB 2022.

110. DEHGHANI, H., & ZILIAN, A. (21 May 2021). AI-aided, incremental numerical approach for fi nite strain poroelasticity: On the brain tissue deformation [Paper presentation]. SIAM Conference on Mathematical Aspects of Materials Science.

111. SALEHIAN GHAMSARI, S., van Dam, T., & HALE, J. (09 September 2025). Stochastic anisotropic aquifer characterization: a poroelastic finite element model and the potential of using InSAR data [Poster presentation]. Near Surface Geoscience Conference & Exhibition 2025, Naples, Italy. doi:10.3997/2214-4609.202520124

112. SALEHIAN GHAMSARI, S., PALMIROTTA, G., Van Dam, T., & HALE, J. (06 June 2024). Using random circular models in aquifer flow simulation [Poster presentation]. DPCSS PhD Day, Esch-sur-Alzette, Luxembourg.

113. DIDIER, J., DE LANDTSHEER, S., PIRES PACHECO, M. I., KISHK, A., SCHNEIDER, J., Demuth, I., & SAUTER, T. (26 October 2022). Improving Machine Learning-based Prediction of Frailty in Elderly People with Digital Wearables : Data from the Berlin Aging Study II (BASE-II) [Poster presentation]. European Digital Medicine Conference Luxembourg 2022, Belval, Luxembourg.

114. DIDIER, J., DE LANDTSHEER, S., PIRES PACHECO, M. I., KISHK, A., SCHNEIDER, J., Demuth, I., & SAUTER, T. (09 October 2022). Machine learning-based prediction of frailty in elderly people : Data from the Berlin Aging Study II (BASE-II) [Poster presentation]. 21st International Conference on Systems Biology, Berlin, Germany.

115. GOGER, S., SZABO, P., FEDOROV, D., & TKATCHENKO, A. (23 August 2022). Non-Local Polarizability Density and DFT [Poster presentation]. Psi-k Conference.

116. DALLE LUCCA TOSI, M., ELLAMPALLIL VENUGOPAL, V., & THEOBALD, M. (2022). CONVERGENCE TIME ANALYSIS OF ASYNCHRONOUS DISTRIBUTED ARTIFICIAL NEURAL NETWORKS [Poster presentation]. 5th Joint International Conference on Data Science Management of Data (9th ACM IKDD CODS and 27th COMAD).

117. GOGER, S. (21 May 2021). Transferability of the Tkatchenko-Scheffler and the Many-body Dispersion Method Between Quantum Chemical Codes [Poster presentation]. DTU DRIVEN Colloquium, Luxembourg.

118. CHAU, M. V. (21 May 2021). Data-driven constitutive laws for hyperelasticity in principal space using symbolic representations of Pytorch ANNs in FEniCS [Poster presentation]. DTU DRIVEN Colloquium, Esch-sur-Alzette, Luxembourg.

119. KOZLOWSKI, D. (21 May 2021). Science Inequalities [Poster presentation]. DTU DRIVEN Colloquium, University of Luxembourg, Luxembourg.

120. CHEN, N. (21 May 2021). Mining social media data: information diffusion and social engagement in the Greater Region [Poster presentation]. DTU DRIVEN Colloquium, University of Luxembourg, Luxembourg.

121. NAVARRO BUENDÌA, R. (21 May 2021). GNSS-R GRAZING ANGLE FOR SEA ICE ALTIMETRY [Poster presentation]. DTU DRIVEN Colloquium, University of Luxembourg, Luxembourg.

122. HURTADO CATHALIFAUD, D. R. (21 May 2021). A data-driven computational framework to provide deformable solids with the sense of touch [Poster presentation]. DTU DRIVEN Colloquium, Esch-sur-Alzette, Luxembourg.

123. TAYE, A., & d'Ambrosio, C. (21 May 2021). Predicting Vulnerability to Poverty with Machine Learning [Poster presentation]. DTU DRIVEN Colloquium, University of Luxembourg, Luxembourg.

124. DALLE LUCCA TOSI, M., THEOBALD, M., & ELLAMPALLIL VENUGOPAL, V. (21 May 2021). Online Learning using Distributed Neural Networks [Poster presentation]. DTU DRIVEN Colloquium, Luxembourg.

125. USLU, S. (21 May 2021). Individually Tailored Neurofeedback [Poster presentation]. DTU DRIVEN colloquium, University of Luxembourg, Luxembourg.

126. KALAITZIDOU, C. (21 May 2021). DATA-INTEGRATED MULTISCALE MODELLING OF FIBROUS EXTRACELLULAR MATRIX [Poster presentation]. DTU DRIVEN Colloquium 2021, Luxembourg.

127. INFANTI, A., Vögele, C., Deleuze, J., Baggio, S., & Billieux, J. (21 May 2021). Assessing the clinical utility of the DSM-5 internet gaming disorder criteria by using supervised machine learning [Poster presentation]. DTU DRIVEN Colloquium, University of Luxembourg, Luxembourg.

128. VITELLO, P. (2021). Leverage crowdsourced datasets for travel demand analysis [Poster presentation]. DTU DRIVEN Colloquium, University of Luxembourg, Luxembourg.

129. VITELLO, P., CAPPONI, A., Klopp, P., CONNORS, R., VITI, F., & FIANDRINO, C. (November 2020). The CORONA Business in Modern Cities [Poster presentation]. The 18th ACM Conference on Embedded Networked Sensor Systems (SenSys 2020). doi:10.1145/3384419.3430606

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