#  Martino Tran 

[He/his](https://equity.ubc.ca/resources/gender-diversity/pronouns/)

PhD (Oxon)

Associate Professor, Tier 2 CRC: Complexity and Sustainability

 - Office: WMAX 233
 
- Email: <martino.tran@ubc.ca>
 
 

 

 

- Bio
- Research
- Courses
 
#####   Bio  

 

Martino is Associate Professor and Canada Research Chair (T2) in Computational Urban Science and Planning. He is also Principal Investigator of the Urban Predictive Analytics Lab that is broadly interested in the application of computational and data sciences for tackling urban planning challenges.

Martino has led both technical and policy research on the large-scale deployment of smart energy and transport technologies, and has worked with UNEP, UNDP, Hitachi Europe’s Smart Cities Program, and various municipal governments. He has lectured at UBC and Oxford on Sustainable Energy, Climate Change and Smart Cities.

Previously, he was Co-Director, [Master of Engineering Leadership (MEL) in Urban Systems](https://apscpp.ubc.ca/programs/mel/urban-systems/) at UBC (2015 - 2018), Oxford Martin Fellow in Complexity, Resilience and Risk, University of Oxford (2013 - 2015), and Senior Research Fellow for the UK Infrastructure Transitions Research Consortium (2012 - 2014) where he contributed to the national infrastructure simulation platform now used by the UK government and the United Nations Engineering Branch (UNOPS). Martino completed his PhD in Environmental Science specializing in Computational Modelling at the University of Oxford, where he developed algorithmic behavioural models of social network influence to understand and predict early adoption of electric vehicles for climate change mitigation.



 

 

 

#####   Research  

 

Martino's research focuses on understanding the environmental, societal and ethical implications of new data, technology and infrastructure in cities. He applies complexity sciences and computational methods to measure, characterize and model interdependencies between people, technology and the built environment to address the following research questions: Who benefits from new data and technology and what are the implications for equity and inclusiveness? What are the limitations and opportunities for technology to improve human well-being and mitigate climate change? How can scientific research inform policy and planning to achieve more positive sustainability outcomes?



 

 

 

#####   Courses  

 

###  PLAN 341 : Smart Cities: Concepts, Methods and Design

 

 

**[Martino Tran](/directory/martino-tran)**

The objective of this course is to understand the technological, social, ethical and policy challenges and opportunities for Smart Cities. This begins with a high-level overview of assessing key challenges that cities face including urbanization, social well-being, inequality, economic development and climate change; and through global case-studies and tutorials the course details key concepts, tools and frameworks to assess smart cities including: urban metrics and indicators, big-data analytics, data ethics and risk, and applications in urban modelling and simulation. Specifically, there is a focus on how data-driven analytics, and technological and social innovation can help address urban policy challenges and inform decision-making.

###### Second-year students may be admitted with instructor permission.



- Level
- Undergraduate
- Eligibility
- Third-year standing or above in any program
 
 

 





 



 

 

 

 

 

 

  ![Martinio, in grey suit among green neighbourhood](/sites/default/files/styles/square_200/public/profile-images/2022-10/Martino%20Tran%20hr.jpg.webp?itok=ezcon0ds) ### Affiliations

- Master Engineering Leadership
 
### Research and Specialties

- Climate change
- Data science
- Technology
- Transportation
- Urban systems
 
 [Website](https://www.urbanpredictiveanalytics.com/)