Prof. Dr. Peter Haddawy 

Mahidol University, THAILAND
Mai 2026 - Aug 2026
Fellow
Jun 2025 - Jan 2026
Fellow
Jun 2018 - Aug 2018
Fellow
Mai 2017 - Aug 2017
Fellow
Jun 2016 - Dez 2016
Fellow

Peter Haddawy

Projekte & Publikationen

Abstract

Diseases spread by insects are emerging at a growing rate and bearing a disproportionate segment of all new infectious diseases. Mosquitoes transmit 36% of all such diseases, including malaria, dengue, and Zika. With climate change the habitat of disease-carrying mosquitoes is now expanding even into temperate regions, bringing along the risk of disease emergence. The research proposed for this fellowship will focus on developing techniques to assist in effectively targeting control efforts to prevent the spread of emerging mosquito-borne diseases. Effective targeting requires knowledge of the areas most at risk from the spread of transmission, the rate at which this might occur, and the key factors affecting vulnerability. Such information can be provided by predictive models. But the challenge here is that predictive models require data, which is typically scarce, uncertain, and evolving in early stages of an emerging disease. A modeling framework will thus be developed that can produce initial estimates with limited and uncertain data, and more refined estimates as more data becomes available. An essential component in such models is an estimate of mosquito populations. But existing mosquito population monitoring approaches are either too inaccurate or too labor intensive. As an alternative solution, we will develop electronic sensors that are able to count and to classify mosquitoes into species based on their wingbeat sounds during flight.

Kooperationspartner
Prof. Dr. Anna Förster, Universität Bremen
Publikationen
Haddawy, P., Wettayakorn, P., Nonthaleerak, B., Su Yin, M., Wiratsudakul, A., Schöning, J., Laosiritaworn, Y., Balla, K., Euaungkanakul, S., Quengdaeng, P., Choknitipakin, K., Traivijitkhun, S., Erawan, B., Kraisang, T. (2019). Large scale detailed mapping of dengue vector breeding sites using street view images. Plos Neglected Tropical Diseases, 13 (7): e0007555. https://doi.org/10.1371/journal.pntd.0007555
Kooperationspartner
Prof. Dr. Ron Kikinis, Universität Bremen
Publikationen
Imrul Hasan, A.H.M., Haddawy, P., Lawpoolsri, S. (2018). A Comparative Analysis of Bayesian Network Approaches to Malaria Outbreak Prediction. Meesad, P., Sodsee, S., Unger, H. (eds.) Recent Advances in Information and Communication Technology 2017, Springer, 108-117. https://doi.org/10.1007/978-3-319-60663-7_10
Haddawy, P., Hassan, S.-U., Abbey, C.W., Lee, I.B. (2017). Uncovering Fine-Grained Research Excellence: The Global Research Benchmarking System. Journal of Informetrics, 11 (2), 389-406. https://doi.org/10.1016/j.joi.2017.02.004
Bonaccorsi, A., Haddawy, P., Cicero, T., Hassan, S. (2017). The solitude of stars. An analysis of the distributed excellence model of European universities. Journal of Informetrics, 11 (2), 435-454. https://doi.org/10.1016/j.joi.2017.02.003
Haddawy, P., Kasantikul, R., Imrul Hasan, A.H.M., Rattanabumrung, C., Rungrun, P., Suksopee, N., Tantiwaranpant, S., Niruntasuk, N. (2016). Spatiotemporal Bayesian Networks for Malaria Prediction: Case Study of Northern Thailand. Studies in Health Technology and Informatics, 228, 773-777. https://doi.org/10.3233/978-1-61499-678-1-773
Haddawy, P., Imrul Hasan, A.H.M., Kasantikul, R., Lawpoolsri, S., Sa-angchai, P., Kaewkungwal, J., Singhasivanon, P. (2017). Spatiotemporal Bayesian networks for malaria prediction. Artificial Intelligence in Medicine, 84, 127-138. https://doi.org/10.1016/j.artmed.2017.12.002
Siriapisith, T., Kusakunniran, W., Haddawy, P. (2018). Outer Wall Segmentation of Abdominal Aortic Aneurysm by Variable Neighborhood Search Through Intensity and Gradient Spaces. Journal of Digital Imaging, 31 (4), 490-504. https://doi.org/10.1007/s10278-018-0049-z
Imrul Hasan, A.H.M., Haddawy, P. (). Integrating ARIMA and Spatiotemporal Bayesian Networks for High Resolution Malaria Prediction. Frontiers in Artificial Intelligence and Applications, 1783-1790. https://doi.org/10.3233/978-1-61499-672-9-1783
Hassan, S., Akram, A., Haddawy, P. (2017). Identifying Important Citations using Contextual Information from Full Text. 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL), IEEE, 1-8. https://doi.org/10.1109/JCDL.2017.7991558
Vannaprathip, N., Haddawy, P., Schultheis, H., Suebnukarn, S. (2017). Generating Tutorial Interventions for Teaching Situation Awareness in Dental Surgery – Preliminary Report. Phon-Amnuaisuk, S., Ang, S.-P., Lee, S.-Y. (eds.), Multi-disciplinary Trends in Artificial Intelligence, Springer, 69-74. https://doi.org/10.1007/978-3-319-69456-6_6
Bonaccorsi, A., Cicero, T., Haddawy, P., Hassan, S.-U. (217). Explaining the transatlantic gap in research excellence. Scientometrics, 110, 217-241. https://doi.org/10.1007/s11192-016-2180-2
Ali, A., Ven, J., Saphangthong, T., Freksa, C., Barkowsky, T., Thongmanivong, S., Chanthavong, H., Haddawy, P. (2017). Experience with the Mobile4D Disaster Reporting and Alerting System in Lao PDR,. Choudrie, J., Islam, M.S., Whid, F., Bass, J.M., Priyatma, J.E. (eds.), Information and Communication Technologies for Development, Springer, 525-535. https://doi.org/10.1007/978-3-319-59111-7_43
Dwisaptarini, A.P., Suebnukarn, S., Rhienmora, P., Haddawy, P., Koontongkaew, S. (2018). Effectiveness of the Multilayered Caries Model and Visuo-tactile Virtual Reality Simulator for Minimally Invasive Caries Removal: A Randomized Controlled Trial. Operative Dentistry, 43 (3). https://doi.org/10.2341/17-083-C
Haddawy, P., Su Yin, M., Wisanrakkit, T., Limsupavanich, R., Promrat, P., Lawpoolsri, S., Sa-angchai, P. (2018). Complexity-Based Spatial Hierarchical Clustering for Malaria Prediction. Journal of Healthcare Informatics Research, 2, 423-447. https://doi.org/10.1007/s41666-018-0031-z
Haddawy, P., Su Yin, M., Wisanrakkit, T., Limsupavanich, R., Promrat, P., Lawpoolsri, S. (2017). AIC-Driven Spatial Hierarchical Clustering: Case Study for Malaria Prediction in Northern Thailand. Phon-Amnuaisuk, S., Ang, S.-P., Lee, S.-Y. (eds.), Multi-disciplinary Trends in Artificial Intelligence, Springer.
Sa-ngamuang, C., Haddawy, P., Luvira, V., Piyaphanee, W., Iamsirithaworn, S. , Lawpoolsri, S. (). Accuracy of Dengue Clinical Diagnosis with and without NS1 Antigen Rapid Test: Comparison between Human and Bayesian Network Model Decision. PLOS Neglected Tropical Diseases, 12 (6): e0006573. https://doi.org/10.1371/journal.pntd.0006573
Sararit,N., Hadddawy, P., Suebnukarn, S. (2017). A VR Simulator for Emergency Management in Endodontic Surgery. Papadopoulos, G., Kuflik, T. (eds.), IUI '17: Proceedings of the 22nd International Conference on Intelligent User Interfaces, Association for Computing MachineryNew YorkNYUnited States, 117-120. https://doi.org/10.1145/3030024.3040976
Su Yin, M., Haddawy, P., Suebnukarn, S., Schultheis, H., Rhienmora, P. (2017). Use of Haptic Feedback to Train Correct Application of Force in Endodontic Surgery. Papadopoulos, G., Kuflik, T. (eds.), IUI '17: Proceedings of the 22nd International Conference on Intelligent User Interfaces, Association for Computing MachineryNew YorkNYUnited States, 451-455. https://doi.org/10.1145/3025171.3025217