Scholarly Service




Santi Phithakkitnukoon


I am an associate professor and head of the Department of Computer Engineering, Faculty of Engineering, at Chiang Mai University, Thailand. My research in the area of Urban Informatics, which focuses on mining large-scale digital footprints such as mobile phone CDRs, GPS traces, social media data, and sensory data to better understand human behavior and urban dynamics. My research interests lie at the intersection of Social Computing, Pervasive Computing, and Urban Computing.


I am originally from Chiang Mai, Thailand. I received my B.S.(hons) and M.S. both in Electrical Engineering in 2003 and 2005 respectively from the Southern Methodist University, Dallas, Texas, USA. I received a Ph.D. in Computer Science & Engineering from the University of North Texas, Denton, Texas, USA in 2009. I then joined the SENSEable City Laboratory at Massachusetts Institute of Technology (MIT) as a postdoctoral researcher until January 2011 and continue my association with the Lab as a research affiliate since. In 2011, I went to the United Kingdom (UK) and joined the Digital Interaction group at the Culture Lab (now Open Lab), Newcastle University as a research associate. Before coming to Chiang Mai University in June 2014, I was a Lecturer in Computing (assistant professor) at the Computing and Communications Department at The Open University, Milton Keynes, UK (October 2012 - July 2014).


For prospective students


+ If you are interested in doing a Ph.D. in Computer Engineering at Chiang Mai University under my supervision, please contact me to discuss a research proposal.

+ You should have a strong background in machine learning, data mining, and statistics.

+ You should be capable of programing with a high level language such as R or Matlab.

+ Please also read this for information about our Ph.D. program.



What*s new


Mar 2022

+ We’re pleased to share our latest publication in Elsevier Energy Journal on Interpretable Machine-Learning Model With a Collaborative Game Approach to Predict Yields and Higher Heating Value of Torrefied Biomass. It’s a collaboration between CMU’s computer engineering and mechanical engineering departments, and University of South Carolina’s department of chemical engineering.


Feb 2022

+ Our work on inferring and analyzing temporary migration flows from a massive mobile phone network data (CDR) has been published in IEEE Access. This is an interdisciplinary research and international collaborative effort between CMU –Computer Engineering, University of Calgary – Civil Engineering, Orange Labs – Sociology and Economics, and MIT – Urban Studies and Planning. 

+ Our work on utilizing Wi-Fi connectivity data for physical space segmentation, namely Xplaces has been accepted for publication in IEEE Access. It is a collaborative project with MIT Senseable City Lab.


Nov 2021

+ Our work on Predicting Spatiotemporal Demand of Dockless E-Scooter Sharing Services with a Masked Fully Convolutional Network has been published in ISPRS International Journal of Geo-Information (Impact factor: 3.294, ISI-Q2, Scopus-Q1). It’s a collaborative effort within the department with Dr. Karn who is an expert in computer vision, and Dr. Demissie who is with the Department of Transportation Engineering at the University of Calgary, Canada.





Copyright (c) 2012 by Santi Phithakkitnukoon