Haokun Liu

Haokun Liu

PhD Student at UNIL

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Virtual Food Sustainability Academy

Master, University of Bern, Institute of Geography, 2022

This course aims to enable course participants to conduct a participatory Food System Sustainability Assessment. It builds on the Food System Sustainability Assessment Framework (FoodSAF). Participants will analyse the sustainability of a food system of a local product in Switzerland by using the FoodSAF tool. The course is conducted with the flipped classroom concept and consists of self-learning course component (out-of-class phase), exercises in classroom (in-class phase) and individual fieldwork with interviews. This course has been developed in collaboration with universities in Kenya, Nigeria, Bolivia and Columbia, but each country is focusing on its own local food systems.

Remote sensing and social-ecological analysis of land surface dynamics in Bern

Master, University of Bern, Institute of Geography, 2023

This practical course offers students the opportunity to learn about remote sensing methods for monitoring land surface dynamics processes, including deforestation and drought, using Google Earth Engine (GEE). The course is divided into three parts: In Part 1, three introductory lectures will cover 1) the background to the course and reading material, 2) remote sensing methods for vegetated terrestrial land surfaces, and 3) links between ecosystem services and remote sensing analyses. In Part 2, students will work through practical tutorials designed to impart basic programming skills using the GEE cloud computing platform. In Part 3, students will choose an example script analyzing either deforestation or drought; they will have the opportunity to develop their own variation of the analysis in a short group (2 to 3 people) research project. Finally, they will present their results as a conference poster, and give a brief presentation to the class.

Systèmes complexes et organisation de l’espace géographique

Bachelor, Université de Lausanne, Institute of Geography and Sustainability, 2023

In this course, our objectives are to introduce systems approaches in geography and the sciences, exploring the theoretical models underpinning complex systems. We aim to foster a multi-dimensional, multi-level perspective in addressing territorial issues and showcase the benefits and challenges of collaborative approaches. Additionally, we’ll encourage students to contemplate the role of systems thinking and artificial intelligence in territorial management and decision-making.

Healthy Urban System

Master, Université de Lausanne, Institute of Geography and Sustainability, 2023

The Healthy Urban Systems MOOC aims at bringing together a group of experts who will contribute to a better understanding of what healthy urban systems are and how they function in system. They will give perspectives on how to approach these complex systems, organize participatory approaches to find and apply solutions with the inhabitants and stakeholders.

CIVIS BIP Workshop: Healthy Urban System

Coursera MOOC, Université de Lausanne, Institute of Geography and Sustainability, 2024

The BIP Healthy Urban Systems provides systemic concepts, practical tools, and detailed illustration of health as the pulse of the new urban agenda, which will serve for different students at bachelor, master, PhD levels.

Introduction to Scientific Programming with Python

Master, Université de Lausanne, Institute of Earth Surface Dynamics, 2024

In this four-week practical course, we will combine tutorials and guided exercises to introduce basic programming skills in Python to help students kickstart their own research projects.

Machine Learning for Earth and Environmental Sciences

Master, Université de Lausanne, Institute of Earth Surface Dynamics, 2024

In this 12-week practical course, we will introduce common machine learning algorithms in the context of their applications in Earth and environmental sciences. By the end of this course, students are able to identify common algorithms and summarize their advantages and limitations, especially in the context of environmental science, and implement them in Python (mostly using the Numpy, Scikit-Learn, Keras, and Tensorflow libraries in Google Collab notebooks). Meanwhile, aiming at the environmental application that they are passionate about (e.g., their thesis and further research), they will have the ability to choose appropriate algorithms from their existing experience.

Advanced Geospatial Data Analysis

Master, Université de Lausanne, Institute of Earth Surface Dynamics, 2025

The spatial and temporal dimensions characterizing the Earth and environmental processes, together with the wealth of available data and the rapid development of analytical models, have become distinctive aspects of Geospatial Data Science (GeoDS). GeoDS encompasses geospatial data manipulation, exploration, analysis, and modeling, from the acquisition phase up to the interpretation of the results. By the end of this course, students will gain a good understanding of the key practical concepts of GeoDS and finish related R programming applications, which is beneficial for mastering various algorithms to analyze complex geo-environmental spatial datasets.