Mobiili pilvilaskenta
Mobile cloud computing (MC2) -tutkimusryhmä tekee kokeellista järjestelmätutkimusta tavoitteenaan kehittää uusia järjestelmiä, sovelluksia ja palveluja, jotka ratkaisevat tosielämän ongelmia. Tutkimusryhmän kehittämät ratkaisut perustuvat uusimpiin tutkimustuloksiin tekoälyn, lisätyn todellisuuden, älysensorien ja reunalaskennan alueilla.

Group members
Latest publications
Designing Beyond Hot and Cold – Exploring Full-Body Heat Experiences in Sauna
Tim Moesgen, Ramyah Gowrishankar, Yu Xiao
2024
Eighteenth International Conference on Tangible, Embedded, and Embodied Interaction
VFogSim: A Data-Driven Platform for Simulating Vehicular Fog Computing Environment
Ozgur Umut Akgul, Wencan Mao, Byungjin Cho, Yu Xiao
2023
IEEE Systems Journal
Motion and Appearance Representation Learning of Human Activities From Videos and Wearable Sensor
Petr Byvshev
2023
A repeated unknown game
Byungjin Cho, Yu Xiao
2023
IEEE Transactions on Vehicular Technology
Quantum bandit with amplitude amplification exploration in an adversarial environment
Byungjin Cho, Yu Xiao, Pan Hui, Daoyi Dong
2023
IEEE Transactions on Knowledge and Data Engineering
Detecting Malicious Accounts in Online Developer Communities Using Deep Learning
Qingyuan Gong, Yushan Liu, Jiayun Zhang, Yang Chen, Qi Li, Yu Xiao, Xin Wang, Pan Hui
2023
IEEE Transactions on Knowledge and Data Engineering
Multi-agent Reinforcement Learning-based Capacity Planning for On-demand Vehicular Fog Computing
Wencan Mao, Jiaming Yin, Yushan Liu, Byung Cho, Yang Chen, Weixiong Rao, Yu Xiao
2023
IEEE Transactions on Vehicular Technology
On-demand Vehicular Fog Computing for Beyond 5G Networks
Wencan Mao, Ozgur Umut Akgul, Byungjin Cho, Yu Xiao, Antti Yla-Jaaski
2023
IEEE Transactions on Vehicular Technology
Designing for Uncertain Futures: An Anticipatory Approach
Tim Moesgen, Antti Salovaara, Felix Anand Epp, Camilo Sanchez
2023
Interactions
Automatic Map Update Using Dashcam Videos
Aziza Zhanabatyrova, Clayton Souza Leite, Yu Xiao
2023
IEEE Internet of Things Journal