Dr. Jimeng Sun is a Health Innovation Professor at the Siebel School of Computing and Data Science and Carle Illinois College of Medicine at the University of Illinois Urbana-Champaign. Co-founder of Keiji AI , he leads groundbreaking research at the intersection of artificial intelligence and healthcare, actively deploying clinical AI systems and developing frameworks like PyHealth and Therapeutics Data Commons . His research spans four major areas: Clinical AI Systems : Developing interpretable models (e.g., RETAIN) for patient similarity, temporal event prediction, medication recommendation, and clinical outcome forecasting Drug Discovery : Creating molecular optimization frameworks, drug-target interaction models, and AI-driven platforms Clinical Trials : Pioneering patient-trial matching, outcome prediction, and optimization frameworks using deep learning and graph neural networks Biosignal Analysis : Advancing sleep staging, seizure classification, and automated EEG/Cardiac monitoring systems With over 500 top-tier publications (including in Nature , NEJM AI , and leading AI conferences) and an h-index of 99, his work has been recognized with the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare award. He maintains active collaborations with institutions like Massachusetts General Hospital , Medidata Solutions , and OSF Healthcare . His recent publications reveal a strong focus on: Reinforcement learning applications in medical data analysis Large language model adaptation for clinical tasks Knowledge graph integration with AI systems Synthetic data generation for healthcare Multi-modal learning in clinical contexts Explainable AI for medical applications Dr. Sun's lab ( Sunlab ) emphasizes practical impact over theoretical work, actively collaborating with hospitals and healthtech companies. He welcomes contributions from clinicians, researchers, and industry partners through initiatives like his AI for Health webinar series .
Marlon Dumas is a Professor of Information Systems at the University of Tartu's Faculty of Science and Technology, with a 20-year academic career spanning Estonia and Australia. He holds a PhD in Computer Science from the University of Grenoble 1, France, and has served as Head of Chair and Programme Director in Software Engineering programs. Specializes in Business Process Management (BPM) and Process Mining Current research focuses on prescriptive process monitoring, simulation modeling, and data privacy Recipient of 25+ scientific awards, including multiple Test of Time Awards and the Estonian National Research Award in Technical Sciences Editorial leadership: Area Editor for Information Systems (Elsevier) and ERC Starting Grant Panel Chair His work bridges theoretical advancements in BPM with practical applications in financial services and anti-money laundering. He has developed tools like SIMOD, Kronos, and Kairos for process optimization and analysis. His research integrates AI/ML techniques (reinforcement learning, causal inference) with traditional process modeling. Key trends in his recent publications include: Prescriptive monitoring systems combining causal inference and machine learning Privacy-preserving process mining techniques (differential privacy, anonymization) Resource availability modeling and multi-objective process optimization LLM applications for process analysis and intervention policies Scientific honors include: 2024 BPM Best Paper & Prototype Awards 2023 ICPM Best Prototype Award 2019 ERC Advanced Grantee 2017 Estonian National Research Award in Technical Sciences 2019 MODELS Test of Time Award 2017 BPM Best Prototype Award He has mentored PhD candidates as thesis examiner and contributed to 30+ conference program committees, including General Co-Chair roles at ESEC-FSE 2019 and CAiSE 2018. His work has been supported by European Research Council grants and Estonian Science Foundation projects.
John Duchi is an Associate Professor at Stanford University, holding positions in the Department of Statistics and the Department of Electrical Engineering (with a courtesy appointment in Computer Science). He is affiliated with the School of Engineering. His research focuses on statistical learning, optimization, information theory, and computation, with an emphasis on balancing computational efficiency, privacy, and robustness. Key interests include developing algorithms for large-scale optimization, privacy-preserving techniques, and tools for evaluating machine learning systems' validity. Education: BS and MS in Computer Science (Stanford University, 2007–2008), MA in Statistics (UC Berkeley, 2012), and PhD in EECS (UC Berkeley, 2014). Research Interests: His work addresses three core areas: (1) optimizing trade-offs between computational resources and statistical performance, (2) creating scalable optimization methods, and (3) quantifying confidence in machine learning systems. Recent publications highlight contributions to privacy in federated learning, robust statistical validation, and uncertainty quantification. Articles: His recent work explores topics like distribution-free M-estimation, private federated learning, and instance-optimal mechanisms for statistical estimation. These studies emphasize privacy, robustness, and scalable solutions for modern data challenges. Advising & Grants: While no advisees are listed, his research has been supported by grants focused on optimization, privacy, and statistical theory.
Prof. Dr. Sebastian Steinhorst is an Associate Professor (W3-level with tenure) at the Technical University of Munich (TUM) within the Embedded Systems and Internet of Things group at the TUM School of Computation, Information and Technology . His research focuses on advancing the security, predictability, reliability, and interoperability of smart connected and autonomous systems, particularly for applications in Internet of Things (IoT) , Industry 4.0 , and automotive systems . PhD in Computer Science (2011) from Goethe University Frankfurt Postdoctoral roles at TUMCREATE Singapore (2011-2016) and Aarhus University (2016) Joined TUM in 2016 as Rudolf Moessbauer Tenure Track Professor His research areas include decentralized embedded systems, hardware/software co-design, modeling and verification of cyber-physical systems, security protocols for automotive networks, and time-sensitive networking (TSN) for industrial applications. Recent work explores blockchain-based data sovereignty, zero-knowledge proofs for vehicle authentication, and resilient architectures for autonomous systems. Key scientific contributions include the 2019 ACM TODAES Best Paper Award and pioneering work on CyberSecDome , LeapChain , and Simutack frameworks. He serves on editorial boards and conference committees, including co-organizing the Autonomous Systems Design initiative at DATE. His teaching portfolio spans lectures on System Design for IoT , Software Architecture for Distributed Systems , and IoT Security across multiple semesters. He also leads advanced seminars on embedded systems and IoT.
Tuuli Toivonen is a Professor of Geoinformatics at the Department of Geosciences and Geography, University of Helsinki. She leads the transdisciplinary Digital Geography Lab , which addresses human-scale spatial analytics for sustainable societies. She serves as Vice-Director of Geography Degree Programs (post-2022) and previously held the Director role (2020-2022). After receiving the ERC Consolidator Grant in 2022, she continues advancing open science through active memberships in HELSUS and URBARIA . PhD in Geography (University of Turku, 2006) Specialist Vocational Qualification in Leadership (2023) Life Member, Clare Hall, University of Cambridge (since 2021) Her research focuses on Human-Place Interactions through accessibility/mobility lenses, combining Open Data , Machine Learning , and Spatial Analytics . Key application areas include Urban Geography , Conservation Science , and Governance Policy . Recent publications address Dynamic Cities (2018), Social Media for Conservation (2019), and Environmental Exposure During Travel (2021). Her lab produces datasets like the Helsinki Region Travel Time Matrix series (2014-2023). Scientific Awards: European Open Data Champion (2017) Open Science Price (2017) University of Helsinki Geography Award (2018) She supervises Master's thesis work and serves as Opponent for doctoral defenses across Europe. Her teaching portfolio includes Advanced Geoinformatics and Digital Geographies courses.
Niccolò Ridi is Senior Lecturer in Public International Law and Associate Director of the Centre for International Governance and Dispute Resolution (CIGAD) at King's College London's Dickson Poon School of Law. He joined King's in 2021 after roles at Liverpool University, Copenhagen University, and the Graduate Institute of International and Development Studies. He holds a PhD from King's, an LLM from Cambridge, and an LLB/MA from Florence. His research focuses on international law (public/private), dispute settlement, and empirical methodologies including data mining/social network analysis. He is finalizing books on international adjudication precedent and comity principles (with Thomas Schultz). He serves as Assistant Editor of the Journal of International Dispute Settlement and is affiliated with leading legal societies. Key research areas include judicial behavior analysis, international court performance, and legal communities' practices. His recent work employs scientometrics to study legal idea propagation and network analysis of scholarly collaboration. He co-leads interdisciplinary initiatives like the Centre for Data Futures, exploring data-driven legal tools. His 2020s research emphasizes ICJ dynamics, Security Council resolution impacts, and investment arbitration innovations. He has supervised 1 PhD student and participates in global legal forums.
Dino Pedreschi is a Full Professor of Computer Science at the University of Pisa, affiliated with the Department of Computer Science (DI-UNIPI). He co-leads the Pisa KDD Lab, a joint research initiative between the University of Pisa and the Italian National Research Council’s Institute of Information Science and Technology, one of the earliest labs focused on data mining and knowledge discovery. His research spans Big Data Analytics , Social Network Analysis , Human Mobility Analysis , Privacy-by-Design , Explainable AI (XAI) , and ethical data mining . He is a pioneer in privacy-preserving data mining and has contributed significantly to understanding societal impacts of AI and big data. Recent publications highlight trends in explainable AI , fairness-aware data mining , urban mobility modeling , and socio-economic nowcasting , reflecting a strong interdisciplinary focus combining computer science, social science, and policy. Notable scientific awards include: Google Research Award on Privacy (2009) University of Pisa Ordine del Cherubino (2017) Pedreschi has played leadership roles in major conferences such as ECML/PKDD (Co-Chair 2004), ICDM (Vice-Chair 2005), and ICDE (Vice-Chair 2014). He founded the Business Informatics MSc program at the University of Pisa to train interdisciplinary data scientists. He has been a visiting scientist at the University of Texas at Austin, CWI Amsterdam, UCLA, and the Barabási Lab at Northeastern University. He actively contributes to European research initiatives including SoBigData++, FAIR, and TAILOR, and has advised on AI policy, including testimony before the Italian Parliament on AI and labor markets. He is a key member of the Pisa KDD Lab, a leading research group in data science and AI ethics, fostering collaboration between academia and public institutions.
Thomas Rüde is Universitätsprofessor for Hydrogeology at RWTH Aachen University , Germany, where he leads the Hydrogeology group within the Faculty of Georesources and Materials Engineering. Holding the chair since 2005, he also serves as Managing Director of the Vereinigung Aachener Geowissenschaftler e.V. and has previously been Vice-President (2008-2014) and Executive Council member (2000-2008) of the International Mine Water Association (IMWA). Education 2004 – Privatdozent (Dr. rer. nat. habil.), University of Munich 1995 – Dr. rer. nat., University of Karlsruhe 1991 – Diplom-Geologe, University of Karlsruhe Research focus Professor Rüde’s work centres on understanding and modelling flow and reactive transport in complex aquifer systems . Key themes include: Contaminant hydrogeology – behaviour of geogenic arsenic and uranium in groundwater Groundwater protection and remediation – risk assessment and mitigation strategies Mine-water management – acid mine drainage, dewatering-well clogging, post-mining landscapes Tracer and hydraulic testing – field experiments to quantify subsurface heterogeneity Numerical modelling – high-performance simulation of multi-aquifer systems and karst His research spans Europe (Germany, Austria, Netherlands), Latin America (Mexico, Indonesia) and South-East Asia, frequently in close collaboration with local universities and industry partners. Publication trends Since 2010, Rüde has published extensively on geogenic contamination (As, U, F) in sedimentary and volcanic aquifers, mine-water impacts , and karst hydraulics . Recent work (2022-24) highlights advanced environmental tracers (gadolinium), transboundary groundwater issues, and the sustainable management of post-mining landscapes under climate change. Numerical models range from site-scale dewatering optimisation to catchment-scale coupled flow-transport simulations. Scientific awards & recognition Best Teaching Award 2010 – RWTH Aachen University Best Teaching Award 2012 – RWTH Aachen University Best Teaching Award 2014 – RWTH Aachen University Supervision & academic service Since 1998 he has taught hydrogeology through lectures, seminars, laboratory and field courses, and computer-based modelling labs. To date he has supervised: 13 PhD candidates 34 Diploma students 57 MSc students 63 BSc students He is Chairman of the Study Commission for the BSc programme in Georesources Management at RWTH Aachen, ensuring curriculum development and quality assurance. Laboratory & field infrastructure His group operates modern hydrochemical laboratories for trace-element analyses and maintains field stations for tracer experiments in Germany, Mexico and Indonesia. High-performance computing resources (in collaboration with the Jülich Supercomputing Centre) enable large-scale groundwater modelling and Monte-Carlo uncertainty assessments.
Laurie Williams serves as a Goodnight Distinguished University Professor in the Computer Science Department within the College of Engineering at North Carolina State University. She co-directs both the NCSU Secure Computing Institute and the NC State Science of Security Lablet, demonstrating deep institutional leadership in cybersecurity research. With over 260 refereed publications, her work establishes her as a prominent figure in software security academia. Her research spans critical areas including software security, agile development practices (particularly continuous deployment), software reliability, and software supply chain security. Williams focuses on practical security solutions addressing modern challenges like malicious dependencies in open-source ecosystems, AI-generated code vulnerabilities, and runtime protection mechanisms. Her work bridges theoretical security principles with industry-relevant applications. Recent publications reveal strong trends toward software supply chain security, with multiple 2024-2025 papers addressing vulnerability exploitability, malicious commit detection, and metrics-driven security control selection. Her research increasingly incorporates machine learning for threat detection while maintaining focus on human factors in secure development practices. IEEE Fellow (2018) National Science Foundation CAREER Award (2004) ACM SIGSOFT Influential Educator Award (2009) Multiple IBM Faculty Awards (2002-2012) NCSU Alumni Association Outstanding Research Award (2015-2016) Williams leads multiple major NSF-funded projects including the $5.7M SaTC Frontiers grant on secure software supply chains and the Science of Security Lablet with $3.6M in DoD funding. Her research emphasizes practical industry impact through collaborations with Cisco and Laboratory for Analytic Sciences. She actively mentors through the NCSU Research Leadership Academy and maintains significant educational outreach in software security. Her laboratory work centers on the Secure Computing Institute and Science of Security Lablet, where her team develops frameworks for vulnerability prediction, supply chain risk assessment, and secure development methodologies. Current projects focus on machine learning integrity, cognitive modeling for security decisions, and empirical analysis of build/deployment logs for anomaly detection.
Dr. Bo Liu is an Associate Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he serves as a core member and director of the AI Security and Privacy (AISP) Research Lab at the Australian Artificial Intelligence Institute (AAII). With expertise spanning cybersecurity, privacy protection, AI and machine learning, and wireless communications, Dr. Liu has established himself as a leading researcher in the field of AI security and privacy. Dr. Liu earned his PhD from the Department of Electronic Engineering at Shanghai Jiao Tong University in 2010. His academic journey at UTS has progressed from Senior Lecturer (November 2019-December 2022) to his current position as Associate Professor (January 2023-present). Dr. Liu's research focuses on the critical intersection of artificial intelligence and security, particularly addressing emerging threats in the age of advanced AI systems. His work spans multiple dimensions of security and privacy, including deepfake detection, privacy-preserving data synthesis, AI model security, and fair machine learning. He has pioneered approaches to detect AI-generated content, protect visual privacy through de-identification techniques, and address the complex relationship between algorithmic fairness and privacy preservation. His publication record demonstrates significant contributions across multiple cutting-edge research areas, with particular emphasis on detecting and mitigating threats from generative AI systems. His recent work reveals a strong focus on deepfake detection across multiple modalities (images, video, and audio), privacy-preserving techniques for sensitive data, and the security implications of emerging AI architectures like Retrieval-Augmented Generation systems. Dr. Liu has secured substantial research funding, including as Lead Chief Investigator on multiple ARC Discovery and Linkage Projects, totaling over $3.5 million AUD. His industry collaborations include partnerships with the NSW Department of Planning and the Reserve Bank of Australia, demonstrating the practical applicability of his research. As an academic leader, Dr. Liu serves as Associate Editor for IEEE Transactions on Broadcasting and actively contributes to the academic community through conference organization, peer review for top-tier venues, and assessment for ARC grant schemes. He also teaches courses including Penetration Testing, Ethical Hacking and Offensive Security, and supervises Masters and PhD students in cybersecurity and privacy research.
Roberto Perdisci is a Professor at the University of Georgia , holding the Patty and D.R. Grimes Distinguished Professorship in Computer Science . He also serves as an Adjunct Associate Professor at the Georgia Tech School of Cybersecurity and Privacy and is a faculty member of the UGA Institute for Artificial Intelligence . His research focuses on securing networked systems through web security , malware detection , and machine learning applications. Directed the UGA Institute for Cybersecurity and Privacy Post-Doctoral Fellow at Georgia Institute of Technology Research Scholar at Georgia Tech Information Security Center His work combines systems research with data mining to address challenges in network security , malware analysis , and Internet-scale measurements . Key contributions include DNS reputation systems analysis , CAPTCHA attack frameworks , and robocall mitigation prototypes . He has received the NSF CAREER award for adaptive malware detection research. Conference service includes: Program Chair for ACSAC 2024 and EuroS&P 2024 Area Chair for WWW 2024 Security Track Best Reviewer Award at ACM CCS 2022 Current affiliations span multiple institutions, with research groups focusing on: Phishing and Social Engineering (PhishInPatterns, TRIDENT projects) Web Browser Forensics (WEBRR, Clickminer) IoT Device Identification (IoTFinder)
McKenzie F. Johnson is an Assistant Professor at the University of Illinois Urbana-Champaign's Department of Natural Resources and Environmental Sciences (NRES), part of the College of Agricultural, Consumer and Environmental Sciences. She is also affiliated with the Institute for Sustainability, Energy, and Environment (ISEE). Her research focuses on global environmental politics, environmental justice, and human security, with a particular interest in how environmental governance initiatives impact marginalized communities. Education: Began with fisheries governance studies, earned a Master of Arts in Conservation Biology from Columbia University (2007), and a PhD in Environmental Policy from Duke University. Her Fulbright scholarship in West Africa (2010s) focused on extractive industries and social justice linkages. Research Interests: Explores intersections between environment, institutions, and justice through projects in South Asia, Africa, and South America. Current U.S.-focused work examines environmental impact assessments and pipeline development's effects on communities. The (in)Secure Landscapes Lab she leads investigates environmental governance's role in creating human security and justice. Key Themes in Publications: Energy infrastructure conflicts (e.g., Dakota Access Pipeline), environmental peacebuilding in post-conflict regions (Colombia, Afghanistan), carbon market equity, and invasive species governance. Her work critiques neoliberal environmental governance models and advocates for inclusive decision-making processes. Lab Activities: The IL Lab analyzes environmental governance's societal impacts, emphasizing participatory approaches. Current projects include studying soil carbon markets' equity implications and climate change adaptation strategies in conflict zones.
Professor Jill Atkins is a Professor of Accounting at Cardiff Business School, Cardiff University, with a distinguished career spanning accounting and finance. She also serves as a Visiting Professor at the University of the Witwatersrand in South Africa. As a leading academic in sustainable accounting, she has published over 50 journal articles and several influential books, establishing herself as a thought leader in the field of extinction accounting and biodiversity finance. Professor Atkins holds a BA Hons (First Class) in European Economics with a Licence ès Sciences Economiques from the University of Nantes, an MSc in Corporate and International Finance from the University of Durham, and a PhD in Finance from the University of Manchester. She is Series Editor for the de Gruyter Studies in Corporate Governance and has authored the leading international textbook "Corporate Governance and Accountability," now in its 5th edition. Professor Atkins' research focuses on three interconnected areas that have significantly contributed to sustainability accounting literature. Her work on private social and environmental reporting (SER) has evolved into "private integrated reporting," where institutional investor engagement processes increasingly integrate social, environmental, and financial issues. She has pioneered the development of "extinction accounting," creating a framework that has inspired extensive international academic research and influenced investment institutions' pollinator engagement strategies. Her third major contribution involves exploring the historical roots of environmental and ecological accounting, connecting accounting history with sustainability research across various historical periods from Victorian water pollution accounting to 18th century nature diaries. Analysis of Professor Atkins' recent publications reveals a clear trajectory toward increasingly specialized and urgent environmental accounting. Her work has evolved from general sustainability reporting to highly focused extinction accounting frameworks, with growing attention to historical precedents and cross-cultural applications. The publications demonstrate a sophisticated integration of critical accounting theory with practical applications in biodiversity conservation, showing how accounting mechanisms can serve as tools for species protection and environmental preservation. Her research increasingly incorporates interdisciplinary perspectives, drawing from ecology, history, art, and philosophy to develop comprehensive approaches to extinction governance. Professor Atkins has received significant recognition within the ESG investment industry and governance circles as a thought leader, regularly invited to give keynotes at international practitioner and academic events. She has led influential projects including a Nuffield Foundation-funded study on private SER and has developed innovative frameworks such as the extinction governance model that brings together accounting practices with governance mechanisms aimed at preventing species extinctions. Professor Atkins supervises doctoral candidates in extinction accounting, extinction governance, ESG investment, accounting for biodiversity, and corporate governance (qualitative research). She has established collaborative networks with leading practitioners in responsible investment, sustainability ratings, financial analysis, and reporting framework providers, including the Capitals Coalition, Moody's, Vigeo Eiris, AXA, and the WWF.
Dr. Victoria C. P. Chen is a Professor in the Industrial, Manufacturing, and Systems Engineering (IMSE) department at The University of Texas at Arlington (UTA), where she has served since 2002. She previously held positions at the Georgia Institute of Technology from 1993-2001. Dr. Chen has held several leadership roles at UTA, including Interim Department Chair (2012-2014), Director of the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS) (2008-2012, and again from 2017-present), and Director of Doctoral Studies (2019-present). She was also the George & Elizabeth Pickett Professor from 2015-2017 and was inducted into the UT Arlington Academy of Distinguished Teachers in 2019. Dr. Chen is actively involved with INFORMS (Institute for Operations Research and the Management Science), where she currently serves as Secretary on the Executive Board. Dr. Chen earned her B.S. in Mathematical Sciences from The Johns Hopkins University, and her M.S. and Ph.D. in Operations Research and Industrial Engineering from Cornell University. Her academic journey includes visiting professorships at the University of Genoa, Italy, and Iowa State University. Dr. Chen's research utilizes statistical perspectives to create new methodologies for operations research problems appearing in engineering and science. Her expertise includes the design of experiments, statistical modeling, and data mining, particularly for computer experiments and stochastic optimization. Through her statistics-based approach, she has developed computationally-tractable decision-making methods for many high-dimensional complex systems. Her work spans multiple domains including sustainability, energy, water management, healthcare, and law enforcement. Specific application areas include inventory forecasting, airline optimization, water reservoir networks, wastewater treatment, air quality monitoring, green building design, nurse assignment systems, and pain management programs. Her recent publications demonstrate continued innovation in mixed integer programming for electric vehicle charging stations, vacuum ultraviolet spectroscopy prediction, and sustainable building education. Senior Member, Institute for Operations Research and the Management Sciences (INFORMS) (2024) Data Mining Prize (Lifetime Achievement Award), INFORMS Society on Data Mining (2023) College of Engineering Teaching Award, UT Arlington (2021) Third Place Award, C3.ai COVID-19 Grand Challenge (2020) Academy of Distinguished Teachers, University of Texas at Arlington (2019) George & Elizabeth Pickett Professorship (2015-2017) As an educator and mentor, Dr. Chen has advised over 25 doctoral students across diverse research topics in operations research and systems engineering. She has secured substantial research funding from multiple sources including the National Science Foundation (over $1.5 million in active projects), Environmental Protection Agency, National Institute of Justice, and industry partners like Luminant and Dallas-Fort Worth International Airport. Her current research projects focus on decision analytics for sustainable urban environments, optimization for Texas water management, and statistical methods for pain management programs. She has served as Principal Investigator or Co-PI on more than 20 externally funded research projects totaling over $3 million in funding. Dr. Chen co-founded the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS) at UTA with Dr. H. W. Corley. This research center brings together faculty and students from multiple disciplines to address complex problems through advanced statistical and optimization methods. She also leads interdisciplinary research teams working on projects related to sustainable infrastructure, energy systems, and healthcare optimization, frequently collaborating with researchers from civil engineering, environmental science, and medical fields.
Professor James Watson is a leading conservation scientist and biogeographer at The University of Queensland , affiliated with the Centre for Marine Science and Centre for Biodiversity and Conservation Science. As a Professor of Conservation Science, he specializes in biodiversity policy, climate change impacts, and species recovery strategies. PhD from University of Oxford (Rhodes Scholar) Co-leader of Green Fire Science and RARES research groups Over 400 peer-reviewed publications His research focuses on ecosystem integrity , protected area effectiveness , and conservation economics , with recent work addressing mining impacts on biodiversity, climate change adaptation, and the global 30x30 initiative. He advocates for evidence-based strategies to save Australia’s rarest species. 2025-2024 research trends show expertise in tropical forest regeneration, climate-species interactions, and policy implementation gaps. Collaborative projects span scientific modeling , GIS analysis , and international conservation frameworks . International Panel on Biodiversity and Ecosystem Services (IPBES) Task Force member Research Fellow, United Nations Environment Program Senior Technical Expert, UNDP’s Nature for Development Program Founding Chair, IUCN Climate Change Specialist Group Supervision includes 12 current PhD candidates working on topics such as night parrot conservation , ecological corridors , and urban biodiversity . Completed students have addressed threatened species recovery and climate adaptation planning . He leads lab teams at Green Fire Science (www.greenfirescience.com) and RARES (https://raresgroup.com.au), focusing on applied conservation solutions.
