Speaker: Prof. Po Yang(The University of Sheffield, UK)
Time: 2025-04-03 10:00-11:00
Venue: Lecture Hall B404, School of Computer Science
Abstract: Global challenges such as population growth, climate change, and resource scarcity are becoming increasingly severe, placing the agricultural sector at a critical juncture. Traditional agricultural fertilization methods, often based on empirical knowledge or models, require extensive data and parameters while lacking generalizability and adaptability. Sustainable vertical farming, as a transformative solution to these challenges, demands the integration of cutting-edge technologies, with artificial intelligence (AI) at the forefront.
This presentation highlights the UK government’s "Net Zero" strategy and related R&D initiatives, examining the current state of sustainable digital agriculture research centered on sensor technology, pervasive computing, and AI. It also outlines our team’s strategic positioning in advancing climate-smart agriculture. Through concrete project case studies, we detail our research efforts and achievements in intelligent sensing, data analytics, and trustworthy decision-making using large language models (LLMs), along with their collaborative applications and impacts. Key focus areas include: A sustainable agricultural data interoperability platform and intelligent analytics technology,Multi-class pest identification and pest threshold quantification technique,Trustworthy agricultural decision-making systems based on LLMs.
Yang Po, Chair Professor of Computer Science, Vice Dean for Research, and Head of the Pervasive Computing Department at the University of Sheffield, UK; Independent Scientific Advisor at the Alan Turing Institute; Member of the UK Government's Smart Agriculture Expert Group. His primary research focuses on pervasive computing, machine learning, data fusion, proactive health, and smart agriculture. His work centers on mobile IoT systems, specifically:(1) Precision data collection and validation of multimodal sensing;(2) Anomaly detection and adaptive learning for complex long-term multimodal correlations;(3) Trustworthy multimodal decision-making powered by large language models (LLMs). With over 180 publications (including 52 IEEE Transactions papers), he has authored/co-authored 16 JCR Q1 and CCF-A conference papers as first/corresponding author in the past five years. His work boasts 7,600+ Google Scholar citations and an H-index of 43. Recognized with three IEEE Best Paper Awards (e.g., INDIN-2019 and TC-TII 2022), he has been consecutively listed in Stanford’s Top 2% Most Influential Scientists (2020–2022).
He serves as Senior Editor for IEEE Journal of Translational Engineering in Health and Medicine and Journal of Biomedical Informatics. Recently securing £4.2M+ in research funding, he co-founded Mutustech Ltd—a UK leader in AgriTech—developing platforms like ParallalFarm and Pezego, now adopted by ADAS, Velcourt, India’s Ministry of Agriculture, and Argentina’s National Crop Protection Center**.
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