Felix Conrad Dipl.-Ing.
Person

Affiliations

Chair of Machine Tools Development and Adaptive Controls
- Academic Staff
- felix.conrad@tu-dresden.de

Identification Numbers

ORCID	0000-0002-9998-1907
Scopus author ID	57961717600

Exploring design space: Machine learning for multi-objective materials design optimization with enhanced evaluation strategies

Conrad, F., Stöcker, J. P., Signorini, C., De paula salgado, I., Wiemer, H., Kaliske, M. & Ihlenfeldt, S., 1 Jan 2025, In: Computational materials science. 246, 113432.

Research output: Contribution to journal › Research article › Contributed › peer-review

AutoML Applied to Time Series Analysis Tasks in Production Engineering

Conrad, F., Mälzer, M., Lange, F., Wiemer, H. & Ihlenfeldt, S., 2024, In: Procedia Computer Science. 232, p. 849-860 12 p.

Research output: Contribution to journal › Conference article › Contributed › peer-review

Need for UAI–Anatomy of the Paradigm of Usable Artificial Intelligence for Domain-Specific AI Applicability

Wiemer, H., Schneider, D., Lang, V., Conrad, F., Mälzer, M., Boos, E., Feldhoff, K., & 2 othersDrowatzky, L. & Ihlenfeldt, S., Mar 2023, In: Multimodal Technologies and Interaction. 7, 3, 23 p., 27.

Research output: Contribution to journal › Research article › Contributed › peer-review

Illustration of the Usable AI Paradigm in Production-Engineering Implementation Settings

Wiemer, H., Conrad, F., Lang, V., Boos, E., Mälzer, M., Feldhoff, K., Drowatzky, L., & 2 othersSchneider, D. & Ihlenfeldt, S., 2023, Artificial Intelligence in HCI - 4th International Conference, AI-HCI 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Proceedings. Degen, H. & Ntoa, S. (eds.). Springer Science and Business Media B.V., p. 640-661 22 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14050 LNAI).

Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review

Impact of Data Sampling on Performance and Robustness of Machine Learning Models in Production Engineering

Conrad, F., Boos, E., Mälzer, M., Wiemer, H. & Ihlenfeldt, S., 2023, Lecture Notes in Production Engineering. Springer Nature, p. 463-472 10 p. (Lecture Notes in Production Engineering, Vol. Part F1163).

Research output: Contribution to book/Conference proceedings/Anthology/Report › Chapter in book/Anthology/Report › Contributed › peer-review

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