Projects per year
Jason Rhuggenaath received his MSc. degree in Management Science and Operations Research from Erasmus University Rotterdam where he also obtained his MSc. degree in Economics and Business Economics. Currently, he pursues a Ph.D. at the School of Industrial Engineering in the Information Systems group. His research interests are data-driven optimization, sequential decision-making under uncertainty and machine learning, focusing on applications in operations management and revenue management.
Refaei Afshar, R., Rhuggenaath, J., Zhang, Y. & Kaymak, U., 10 Apr 2021, (Accepted/In press) Proceedings of the International Joint Conference on Neural Networks (IJCNN2021).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-reviewOpen AccessFile19 Downloads (Pure)
Rhuggenaath, J., Zhang, Y., Verwer, S. E. & Hilgeman, M. J., 5 Jan 2021, (E-pub ahead of print) In: Annals of Mathematics and Artificial Intelligence. XX, X
Research output: Contribution to journal › Article › Academic › peer-reviewOpen AccessFile24 Downloads (Pure)
Low-Regret Algorithms for Strategic Buyers with Unknown Valuations in Repeated Posted-Price AuctionsRhuggenaath, J., Oliveira da Costa, P. R. D., Zhang, Y., Akcay, A. & Kaymak, U., 2021, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Proceedings. Hutter, F., Kersting, K., Lijffijt, J. & Valera, I. (eds.). Springer Science and Business Media Deutschland GmbH, p. 416-436 21 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12458 LNAI).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-reviewOpen AccessFile20 Downloads (Pure)
Rhuggenaath, J., Afshar, R. R., Akcay, A., Zhang, Y., Kaymak, U., Çolak, F. & Tanyerli, M., Mar 2021, In: Operations Research Letters. 49, 2, p. 250-256 7 p.
Research output: Contribution to journal › Article › Academic › peer-reviewOpen Access
De Oliveira Da Costa, P., Rhuggenaath, J., Zhang, Y., Akcay, A., Lee, W-J. & Kaymak, U., 30 Apr 2020, The European Conference on Machine Learning and Principles (ECML2019) and Practice of Knowledge Discovery in Databases (PKDD2019). Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M. & Robardet, C. (eds.). Berlin: Springer, p. 719-734 16 p. (Lecture Notes in Artificial Intelligence; vol. 11908 LNAI).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-reviewOpen AccessFile65 Downloads (Pure)