2025年2月24日に，准教授のHamada先生および本研究室がモバイルコンピューティング・スマートシティに関する研究を行っている海外の研究者を招待し，ワークショップ「Japan-US-Europe-Australia Workshop on Innovating Smarter Cities with AI, Sensing, and Spatial Computing」で講演いただきました．
招待した海外の研究者と発表題目は下記の通りです．
- Flora Salim, Professor, University of New South Wales, Australia
- Talk title: Sensor and Multimodal Foundation Models for Human Behaviour Understanding
- Bio: Professor Flora Salim is an academic in the field of human-centred AI, machine learning, and ubiquitous computing. She currently holds the position of Professor in the School of Computer Science and Engineering at the University of New South Wales (UNSW) Sydney, where she also serves as the Deputy Director (Engagement) of the UNSW AI Institute. Her work focuses on developing innovative multimodal machine learning solutions for time-series and sensor data, for applications in human behaviour understanding and in energy, climate, and transport and complex systems modelling.
- Mahmoud Sakr, Professor, Université Libre de Bruxelles, Belgium
- Talk title: Urban mobility data science
- Bio: Mahmoud Sakr is a professor at the Université libre de Bruxelles (ULB). He holds a PhD from the FernUniversität in Hagen, Germany. He completed the B.Sc. and M.Sc. studies in the Faculty of Computer and Information Science at Ain Shams University in Egypt. His main research scope is mobility data science and he has published many papers on this topic. He is a main contributor and a co- founder of MobilityDB, a mobility database that extends PostgreSQL and PostGIS with temporal and spatiotemporal data types. He is also a main contributor and co- chair of the Moving Feature Standards Working Group (MF-SWG) of the Open Geospatial Consortium (OGC). He participates in several Horizon Europe research projects on the topic of mobility data science, including MobiSpaces and EMERALDS. He is actively participating in open-source community conferences including FOSS4G, PGConf, and FOSDEM.
- Amr Magdy, Assistant Professor, UC Riverside, USA
- Talk title: Scalable Spatial Data Science for Social Scientists
- Bio: Amr Magdy is a Professor of Computer Science and Engineering and a co- founding faculty member of the Center for Geospatial Sciences at the University of California Riverside. His research interests include data science, big data management, spatial computing, database systems, spatio-temporal data management, large-scale data analytics, indexing, and main-memory management. His research has been published in prestigious research venues, including ACM SIGSPATIAL, IEEE ICDE, VLDB, VLDB Journal, ACM SIGMOD, ACM TSAS, and IEEE TKDE. Amr's research is recognized as the best paper runner-up in IEEE MDM 2023, among the best papers of SSTD 2023, ACM SIGSPATIAL 2019 and 2023, and IEEE ICDE 2014, and has been incubated by several industrial collaborators in the Middle East and USA. Amr has received several research awards, including the Google-CAHSI, Microsoft, and NSF CAREER awards in 2023.
- Xue Hao, Lecturer, University of New South Wales, Australia
- Talk title: Leveraging LLMs for Time Series Forecasting
- Bio: Dr Hao Xue currently holds a Lecturer position at the School of Computer Science and Engineering at University of New South Wales (UNSW Sydney), Australia. He obtained his PhD from The University of Western Australia in 2020. After completing his doctorate, he worked as a Research Fellow at the School of Computing Technologies at RMIT University and UNSW Sydney. He is an Associate Investigator at the UNSW node of the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S). His research interests include spatiotemporal data modelling, time series forecasting, language generation based forecasting, and data-efficient time series representation learning.
