Insect biodiversity is declining worldwide, yet data collection in this field remains complicated. In this workshop, we will dive into the world of detecting tiny bugs with visual AI methods. You will learn about computer vision, tiny models for detection, and challenges in this field. After the workshop, you will be able to train and deploy your own AI model to detect insect species of interest and interpret the performance of the model.
*For this workshop, you will need your laptop and access to Google Collabs.
Hosts:
Titus Venverloo
Titus leads the MIT Senseable City Amsterdam (SCA) research lab. The Lab consists of an interdisciplinary group of MIT researchers, who work on challenges from the City of Amsterdam. By combining disciplines and leverages digital technologies and real-time data, SCA aims to enable a climate-neutral Amsterdam.
Åse Håtveit
Åse is a researcher at MIT Senseable City Lab and AMS Institute, focusing on utilizing edgeAI technologies to monitor insect biodiversity. In previous research, Åse has been working on challenges and opportunities in developing and adapting urban environmental sensing tools for ‘makers’. With a MSc in Informatics, her expertice ranges from low-cost sensing technologies and software development, to designing engaging workshops for tech students.
Giacomo Orsi
Giacomo is a researcher at MIT Senseable City Lab and AMS Institute, focusing on applying large-scale data analysis, causality, and machine learning to urban dynamics, with a strong commitment to open data, open knowledge, and sustainable mobility. At the lab, Giacomo specializes in big-data analysis and the application of artificial intelligence in the mobility field.
Orlando Closs
Orlando is a Master’s student in Metropolitan Analysis, Design, and Engineering at the AMS Institute and a research assistant at MIT Senseable City Amsterdam (SCA) research lab, specializing in computer vision to monitor insect species. Previously, he worked with a startup to develop AI-driven tools for predicting greenhouse tomato yield and, during his bachelor’s in Artificial Intelligence, focused his thesis on using language models to enhance citizen participation and community engagement.