Santi Phithakkitnukoon

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Carlos Lisboa BentoUniversidade de CoimbraDirección de correo verificada de dei.uc.pt
Carlo RattiProfessor, Senseable City Lab, Department of Urban Studies and Planning, MITDirección de correo verificada de mit.edu
Marco VelosoPh.D.and Researcher at Centre for Informatics and Systems of the University of Coimbra (CISUC)Dirección de correo verificada de dei.uc.pt
Zbigniew SmoredaOrange / Orange Labs / SENSEDirección de correo verificada de orange.com
Teerayut HoranontSirindhorn International Institute of Technology, Thammasat UniversityDirección de correo verificada de siit.tu.ac.th
Giusy Di LorenzoPWCDirección de correo verificada de it.pwc.com
Patrick OlivierAction Lab, Monash UniversityDirección de correo verificada de monash.edu
Gerd KortuemProfessor of Internet of Things, Delft University of TechnologyDirección de correo verificada de tudelft.nl
Tuck Wah LeongProfessor, Director of Apple Foundation Program, RMIT UniversityDirección de correo verificada de rmit.edu.au
Sourav BhattacharyaSamsung AIDirección de correo verificada de samsung.com
Francesco CalabreseRichemontDirección de correo verificada de richemont.com
Dietmar OffenhuberProfessor & Department Chair, Northeastern UniversityDirección de correo verificada de neu.edu
David LeeKAIST, Massachusetts Institute of TechnologyDirección de correo verificada de mit.edu
Rui GomesUniversidade de Coimbra, Faculdade de Engenharia da Universidade do Porto, Portugal Telecom InovaçãoDirección de correo verificada de dei.uc.pt
Petteri NurmiProfessor of Computer Science, University of HelsinkiDirección de correo verificada de helsinki.fi
Arto KlamiAssociate Professor, University of HelsinkiDirección de correo verificada de cs.helsinki.fi
Neal LathiaGradient LabsDirección de correo verificada de gradient-labs.ai
Marco ContiConsiglio Nazionale delle Ricerche (CNR)Dirección de correo verificada de iit.cnr.it
Reza RawassizadehAssociate Professor, Boston UniversityDirección de correo verificada de bu.edu

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Santi Phithakkitnukoon

Professor of Data Engineering, Chiang Mai University

Dirección de correo verificada de eng.cmu.ac.th - Página principal

Urban informatics Human mobility


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Activity-aware map: Identifying human daily activity pattern using mobile phone data S Phithakkitnukoon, T Horanont, G Di Lorenzo, R Shibasaki, C Ratti Human Behavior Understanding: First International Workshop, HBU 2010 …, 2010	416	2010
Socio-geography of human mobility: A study using longitudinal mobile phone data S Phithakkitnukoon, Z Smoreda, P Olivier PLoS ONE, 2011	281	2011
Taxi-aware map: Identifying and predicting vacant taxis in the city S Phithakkitnukoon, M Veloso, C Bento, A Biderman, C Ratti Ambient Intelligence: First International Joint Conference, AmI 2010, Malaga …, 2010	214	2010
Urban mobility study using taxi traces M Veloso, S Phithakkitnukoon, C Bento Proceedings of the 2011 international workshop on Trajectory data mining and …, 2011	156	2011
Group recommendation system for facebook EA Baatarjav, S Phithakkitnukoon, R Dantu On the Move to Meaningful Internet Systems: OTM 2008 Workshops: OTM …, 2008	130	2008
Weather effects on the patterns of people's everyday activities: a study using GPS traces of mobile phone users T Horanont, S Phithakkitnukoon, TW Leong, Y Sekimoto, R Shibasaki PloS one 8 (12), e81153, 2013	127	2013
Inferring passenger travel demand to improve urban mobility in developing countries using cell phone data: a case study of Senegal MG Demissie, S Phithakkitnukoon, T Sukhvibul, F Antunes, R Gomes, ... IEEE Transactions on intelligent transportation systems 17 (9), 2466-2478, 2016	104	2016
Understanding tourist behavior using large-scale mobile sensing approach: A case study of mobile phone users in Japan S Phithakkitnukoon, T Horanont, A Witayangkurn, R Siri, Y Sekimoto, ... Pervasive and Mobile Computing 18, 18-39, 2015	96	2015
Sensing urban mobility with taxi flow M Veloso, S Phithakkitnukoon, C Bento Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location …, 2011	64	2011
Inferring social influence in transport mode choice using mobile phone data S Phithakkitnukoon, T Sukhvibul, M Demissie, Z Smoreda, J Natwichai, ... EPJ Data Science 6, 1-29, 2017	61	2017
Behavior-based adaptive call predictor S Phithakkitnukoon, R Dantu, R Claxton, N Eagle ACM Transactions on Autonomous and Adaptive Systems (TAAS) 6 (3), 1-28, 2011	59	2011
Exploratory study of urban flow using taxi traces M Veloso, S Phithakkitnukoon, C Bento, N Fonseca, P Olivier First Workshop on Pervasive Urban Applications (PURBA) in conjunction with …, 2011	56	2011
Behavior analysis of spam botnets H Husna, S Phithakkitnukoon, S Palla, R Dantu 2008 3rd International Conference on Communication Systems Software and …, 2008	56	2008
Visualizing public transit system operation with GTFS data: A case study of Calgary, Canada P Prommaharaj, S Phithakkitnukoon, MG Demissie, L Kattan, C Ratti Heliyon 6 (4), 2020	49	2020
Interpretable machine-learning model with a collaborative game approach to predict yields and higher heating value of torrefied biomass T Onsree, N Tippayawong, S Phithakkitnukoon, J Lauterbach Energy 249, 123676, 2022	46	2022
Trip distribution modeling using mobile phone data: emphasis on intra-zonal trips MG Demissie, S Phithakkitnukoon, L Kattan IEEE Transactions on Intelligent Transportation Systems 20 (7), 2605-2617, 2018	45	2018
Mining temporal patterns of transport behaviour for predicting future transport usage S Foell, G Kortuem, R Rawassizadeh, S Phithakkitnukoon, M Veloso, ... Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing …, 2013	44	2013
Weather Effects on Mobile Social Interactions: A Case Study of Mobile Phone Users in Lisbon, Portugal S Phithakkitnukoon, TW Leong, Z Smoreda, P Olivier PLoS ONE 7 (10), e45745, 2012	43	2012
Out of sight out of mind--How our mobile social network changes during migration S Phithakkitnukoon, F Calabrese, Z Smoreda, C Ratti 2011 IEEE third international conference on privacy, security, risk and …, 2011	43	2011
Analysis of demand–supply gaps in public transit systems based on census and GTFS data: a case study of Calgary, Canada K Kaeoruean, S Phithakkitnukoon, MG Demissie, L Kattan, C Ratti Public Transport 12, 483-516, 2020	38	2020

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