Shiqiao Li

About

Shiqiao Li took up his position in 2012 as Weedon Professor in Asian Architecture at the University of Virginia's School of Architecture, where he teaches and researches into emerging issues in contemporary Chinese cities. His academic portfolio includes history and theory courses as well as design studio instruction, under which his students have won several first prizes in international student design competitions and were nominated and shortlisted for the RIBA President’s Medal. He studied architecture at Tsinghua University in Beijing and obtained his PhD from the AA School of Architecture and Birkbeck College, University of London. Li practiced architecture in London and Hong Kong, initiating design proposals that have been published and exhibited in journals and international exhibitions. His writings have appeared in numerous architectural and cultural journals, and his books include 'Understanding the Chinese City,' 'Architecture and Modernization,' and 'Power and Virtue, Architecture and Intellectual Change in England 1650-1730.' He has served as an external examiner for PhD degrees at RMIT University and the University of New South Wales, and as an international judge for the RIBA President’s Medal for Dissertations in 2006. Li has been a keynote speaker at various universities worldwide and has lectured extensively, including at the University of Virginia, University of Sheffield, University of Tokyo, and others. Prior to his appointment at Virginia, he taught at…

Research topics

• Artificial Intelligence
• Data Mining
• Machine Learning
• Computer Science
• Geology
• Materials science
• Data science
• Biology
• Ecology
• Mathematics

Selected publications

• Climate change: Strategies for mitigation and adaptation

  The Innovation Geoscience · 2023 · 205 citations

  <p>The sustainability of life on Earth is under increasing threat due to human-induced climate change. This perilous change in the Earth's climate is caused by increases in carbon dioxide and other greenhouse gases in the atmosphere, primarily due to emissions associated with burning fossil fuels. Over the next two to three decades, the effects of climate change, such as heatwaves, wildfires, droughts, storms, and floods, are expected to worsen, posing greater risks to human health and glo…

  DOI

• Large language models management of complex medication regimens: a case-based evaluation

  Frontiers in Pharmacology · 2025-11-24 · 1 citations

  articleOpen access

  Background: Large language models (LLMs) have shown the ability to diagnose complex medical cases, but only limited studies have evaluated the performance of LLMs in the development of evidence-based treatment plans. The purpose of this evaluation was to test four LLMs on their ability to develop safe and efficacious treatment plans on complex patients managed in the intensive care unit (ICU). Methods: Eight high-fidelity patient cases focusing on medication management were developed by critical…

  PublisherOA PDFDOI

• The Photographer’s Eye: Teaching Multimodal Large Language Models to See and Critique like Photographers

  2025-06-10

  articleSenior author

  "While editing directly from life, photographers have found it too difficult to see simultaneously both the blue and the sky."John Szarkowski, William Eggleston’s Guide <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>Photographer and curator, Szarkowski insightfully revealed one of the notable gaps between general and aesthetic visual understanding: while the former focuses on identifying the factual element in an image (sky), the latter tran…

  PublisherDOI

• Large Language Models for Causal Discovery: Current Landscape and Future Directions

  2025-09-01

  articleSenior author

  Causal discovery (CD) and Large Language Models (LLMs) have emerged as transformative fields in artificial intelligence that have evolved largely independently. While CD specializes in uncovering cause-effect relationships from data, and LLMs excel at natural language processing and generation, their integration presents unique opportunities for advancing causal understanding. This survey examines how LLMs are transforming CD across three key dimensions: direct causal extraction from text, integ…

  PublisherDOI

• RoE-FND: A Case-Based Reasoning Approach with Dual Verification for Fake News Detection via LLMs

  ArXiv.org · 2025-06-04

  preprintOpen accessSenior author

  The proliferation of deceptive content online necessitates robust Fake News Detection (FND) systems. While evidence-based approaches leverage external knowledge to verify claims, existing methods face critical limitations: noisy evidence selection, generalization bottlenecks, and unclear decision-making processes. Recent efforts to harness Large Language Models (LLMs) for FND introduce new challenges, including hallucinated rationales and conclusion bias. To address these issues, we propose \tex…

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: III: Small: Physics Guided Graph Networks for Modeling Water Dynamics in Freshwater Ecosystems

  NSF · $250k · 2023–2026

• NIH Grant R15NS053442

  NIH · $212k · 2009

Frequent coauthors

• Yun Fu

  53 shared

• Zhixuan Chu

  30 shared

• Xiao‐Yuan Jing

  Guangdong University of Petrochemical Technology

  29 shared

• Mengxuan Hu

  First Affiliated Hospital of Anhui Medical University

  27 shared

• Ronghang Zhu

  25 shared

• Frank G. Zöllner

  University Medical Centre Mannheim

  25 shared

• Haihu Liu

  25 shared

• Zhengliang Liu

  Augusta University

  24 shared

Education

• PhD, Electrical and Computer Engineering

  Northeastern University

  2017

Awards & honors

• RIBA President’s Medal (shortlisted)

Similar researchers at University of Virginia

• Amy Chanh-28
• Tyler Jo Smithh-12
• Amanda Phillipsh-9