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Jiuling LiView profile

Research Fellow

• Urban Water Management
• Automation Control
• Model Predictive Control
• +9 more

Dr. Jiuling Li is a Research Fellow at the Australian Centre for Water and Environmental Biotechnology (ACWEB) within the Faculty of Engineering, Architecture and Information Technology at The University of Queensland. He received his Bachelor's degree in Automation from Harbin Institute of Technology, China, followed by a Master's (Research) of Engineering from the same institution, and completed his PhD at The University of Queensland in 2021. Dr. Li's educational background in automation engineering has uniquely positioned him at the intersection of environmental engineering and computer science. His multidisciplinary expertise bridges the gap between traditional water management practices and cutting-edge computational approaches, enabling innovative solutions to complex urban water challenges. His primary research focuses on urban water systems with specializations in real-time control, digital twins, smart monitoring, and real-time functional analysis. Dr. Li's work in model predictive control, real-time optimization, IoT sensor networks, and high-performance computing for sewer networks, water distribution systems, and wastewater treatment plants represents a convergence of environmental science and advanced computing. His vision for digital water management integrates cutting-edge data technology into the water industry while simultaneously advancing computing science through practical applications in water systems. Dr. Li's extensive publication record demonstrates significant contributions across environmental engineering and computer engineering disciplines. His research shows a clear trend toward increasingly sophisticated integration of artificial intelligence and machine learning techniques with traditional water management practices. Notable themes include the application of transformer networks, data-driven modeling, anomaly detection, and physics-informed learning to solve complex challenges in urban water infrastructure. Advance Queensland Industry Research Fellowship recipient for artificial intelligence-enabled sustainable protection of sewer infrastructures IWA Global Project Innovation Award (2024) winner for real-time control of chemical dosing in sewer networks Associate Editor of Water Research X Dr. Li actively supervises multiple PhD students across various water-related research topics including sewer corrosion, airflow modeling, groundwater interactions, wastewater-based epidemiology, and digital water management. His current research is supported by significant funding including the Advance Queensland Industry Research Fellowship (2025-2027) and ARC Linkage Projects (2024-2027) focused on artificial intelligence applications for sewer infrastructure protection and greenhouse gas emission reduction. His work is established through close collaboration with industry partners and professional organizations including IEEE and IWA. As part of the Australian Centre for Water and Environmental Biotechnology, Dr. Li contributes to a multidisciplinary research environment that combines engineering, environmental science, and computational approaches to address critical water challenges. His work on digital sewer systems represents a significant advancement in the application of real-time control and monitoring technologies to traditional water infrastructure.

Massimiliano M. SchiraldiView profile

Professor

• Production Systems Management
• Logistics and Supply Chain Management
• Industrial Plant Design and Engineering
• +8 more

Massimiliano M. Schiraldi is a Full Professor of Industrial Plants at the University of Rome Tor Vergata, where he teaches Industrial Plants and Production Management at the School of Engineering. He also teaches Lean Production and Operations Management in the Master's program in Business Engineering. His academic appointment is in the Department of Business Engineering (IIND-05). Professor Schiraldi received his PhD in Management Engineering in 2003 and has been teaching Operations Management subjects since 2000. His research interests span multiple areas of industrial engineering and operations management, including production systems management, logistics and supply chain optimization, industrial plant design, production cost reduction techniques, and production information systems. He has pioneered approaches in Lean Production, Six Sigma standards, and advanced production management techniques with hybrid kanban systems. Professor Schiraldi's recent publications demonstrate his continued leadership in operations management, with a focus on digital transformation, performance measurement, Industry 4.0 technologies, and the human factor in operations excellence. His work bridges theoretical research with practical applications in manufacturing and service industries. Co-Editor of the International Journal of Engineering Business Management (Sage) Area-Editor (Supply Chain Management & Logistics) of Computers and Industrial Engineering (Elsevier) Reviewer for many primary international journals including International Journal of Production Research and International Journal of Logistics Systems and Management Professor Schiraldi has supervised over 20 PhD students and more than 300 undergraduate theses, many of which were conducted in collaboration with major Italian and multinational companies. He has participated in over 50 research and consulting projects with industrial companies at national and international levels. He established the Operations Excellence Think Tank and has served in numerous administrative roles at the university, including as Rector's Delegate for major events and coordinator of university merchandising and social media. He maintains strong industry connections with companies including Amazon, Ferrero, Calzedonia, Gucci, Ferrari, Johnson & Johnson, and many others across various sectors. Internationally, he serves as a Guest Professor at Guizhou University of Finance & Economics in China and a Visiting International Fellow at the University of Essex in the UK.

Ramin MoghaddassView profile

Associate Professor

• Predictive Analytics
• Machine Learning
• Industrial Engineering
• +4 more

Ramin Moghaddass is an Associate Professor in the Department of Industrial Engineering at the University of Miami's College of Engineering. He serves as Director of both the Industrial Research and Assessment Center and the Building Training, Research, and Assessment Center. His work bridges machine learning with industrial engineering to solve complex system monitoring and maintenance challenges. University of Miami, College of Engineering Director, Industrial Research and Assessment Center Director, Building Training, Research, and Assessment Center His research focuses on: Deep state-space modeling for dynamic systems Graph neural networks for smart grid and network anomaly detection Thermal-RGB sensor fusion for manufacturing plant efficiency Image processing for vegetation risk analysis in power networks Bayesian filtering techniques with stochastic neural networks Recent publications highlight trends in sensor-driven system modeling (2025), thermal-RGB fusion for HVAC optimization (2025), anomaly detection in smart grids (2025), and adaptive inspection protocols for large-scale networks (2024). His work combines recurrent neural networks with dynamic Bayesian layers for predictive analytics while exploring graph topology integration. Contact: rxm991@miami.edu | (305) 284-9505

Wei RenView profile

Associate Professor

• Ecosystem Ecology
• Climate-Smart Agriculture
• Remote Sensing/GIS
• +4 more

Wei Ren is an Associate Professor in the Department of Natural Resources & the Environment at the University of Connecticut. Previously, he held positions as Associate Professor (2021-2022) and Assistant Professor (2015-2021) at the Department of Plant & Soil Sciences, University of Kentucky. His research focuses on Earth system interactions, integrating field observations, remote sensing, and numerical models to address climate-smart agriculture, carbon cycling, and sustainable resource management. PhD in Ecosystem Ecology (2009) - Auburn University MS in Meteorology (2003) - Nanjing Institute of Meteorology BS in Agrometeorology (2000) - Nanjing Institute of Meteorology Dr. Ren's research examines: Climate-smart agricultural practices and their multi-scale effectiveness Big-data synthesis for natural resource management Climate change adaptation and mitigation strategies Soil carbon dynamics under changing land use and management Remote sensing integration with ecological models Greenhouse gas emissions from managed ecosystems Recent article trends show: 12/15 focus on carbon and nitrogen cycling in agroecosystems 9/15 analyze climate-smart agricultural interventions 8/15 incorporate remote sensing data assimilation 6/15 address water resource efficiency in cropping systems 4/15 involve cross-border environmental impacts 3/15 examine power grid-environment interlinkages

Janani DurairajView profile

Research Fellow

• Structural Biology
• Computational Biology
• Machine Learning for Proteins
• +4 more

Dr. Janani Durairaj is a Research Fellow at the Biozentrum, University of Basel , where she focuses on integrating biochemical context into deep learning models to study protein structure and interaction variability. Her work bridges computational biology with drug discovery, emphasizing accurate prediction of protein behavior and therapeutic targeting. Key research areas: Structural Biology , Machine Learning , and Protein Engineering Current projects: Context-aware computational models of molecular interactions, protein-ligand co-folding, and structural analysis of viral proteins Her recent publications in Protein-Ligand Docking and AlphaFold Applications highlight her contributions to automated benchmarking and computational modeling. She collaborates with interdisciplinary teams at the Biozentrum, leveraging exascale computing for drug discovery.

Aleksandar DedićView profile

Professor

• Process Engineering
• Drying Technology
• Biomass Energy
• +5 more

Aleksandar Dedić is a Full Professor at the University of Belgrade's Faculty of Forestry, specializing in Process Engineering with over 125 scientific and professional publications. His academic career spans more than 30 years since joining the faculty in 1992, with his promotion to full professor in 2018. His research focuses on industrial drying processes, biomass energy conversion, and advanced modeling techniques. Key areas include: Heat and mass transfer modeling in wood drying Biomass utilization for energy production Automation of industrial processes using pneumatics, hydraulics, and AI Machine learning applications in wood processing His publication record shows consistent contributions to drying technology since 1997, with recent work expanding into biomass energy systems (2010-2018) and computational modeling of industrial processes. The 15 most recent articles demonstrate strong international collaboration and application in food engineering, environmental systems, and renewable energy. Professional recognitions include: DAAD Scholarship for research at Dresden University of Technology (2000-2001) Technical Assessor for Accreditation Body of Serbia since 2009 Peer reviewer for Horizon 2020 projects and Marie Sklodowska-Curie scholarships As an educator, he teaches across all academic levels including specialized courses in pneumatics/hydraulics, automation systems, and dynamic modeling for furniture production. His industry engagement includes technical design projects and consultancy for companies like AGROSAVA.

• Plant Physiology
• Ecophysiology
• Volatile Organic Compound Emissions
• +5 more

Ülo Niinemets is Professor and Head of Department of Crop Science and Plant Biology at the Estonian University of Life Sciences. A distinguished plant ecophysiologist with over 30 years of academic experience, he has held professorships at Estonian University of Life Sciences since 2009, served as Extraordinary Professor at Utrecht University (2007-2012), and held positions at University of Tartu and University of Hawaii. His educational background includes: Doctor Philosophiae in Ecophysiology from University of Tartu (1996) Master of Science in Biology-Ecophysiology from University of Tartu (1993) Diploma of Biology (Ecophysiology) from University of Tartu, graduated Cum Laude (1992) Niinemets specializes in plant ecophysiology with focus on volatile organic compound emission physiology, plant stress biology, and functional relations between plant structure and physiology. His research explores how plants acclimate and adapt to environmental changes, particularly in the context of global change biology. He has made significant contributions to understanding plant responses to light, temperature, and CO 2 variations, with applications in forestry and agriculture. His work bridges fundamental plant physiology with practical environmental and agricultural challenges, examining topics from cellular mechanisms to ecosystem-level processes. His recent publications demonstrate an interdisciplinary approach spanning plant stress physiology, urban ecology, agricultural science, and climate change impacts. Many studies focus on isoprene emissions, plant responses to climate change variables, and crop physiology under marginal conditions, reflecting his commitment to addressing both theoretical questions and practical applications in a changing world. Among his notable recognitions: National Science Prize in Bio- and geosciences (2018, 2000) White Star Order, IV class by the President of Estonia (2012) Best paper award from the Japanese Ecological Society (2011) National Science Prize in Chemistry and molecular biology (2006) Professor Niinemets has actively contributed to scientific discourse through editorial leadership, serving as editor for Oecologia since 2012, Frontiers in Plant Science since 2010, and as editor of the Tree Physiology book series since 2008. He has reviewed grant applications for multiple international funding agencies and served on the Science Policy Commission of the Estonian Ministry of Education and Research (2012-2017), helping shape national research priorities. His research group at the Estonian University of Life Sciences investigates plant responses to environmental stressors, with particular emphasis on volatile organic compounds and their ecological significance. The team employs a multi-scale approach, examining plant physiology from cellular mechanisms to ecosystem-level processes, with implications for understanding climate-vegetation interactions and developing climate-resilient agricultural practices.

Ketan P. DetrojaView profile

Associate Professor

• Control Theory
• State Estimation
• Fault Diagnosis
• +9 more

Ketan P. Detroja is an Associate Professor in the Department of Electrical Engineering at Indian Institute of Technology Hyderabad . With a Ph.D. from IIT Bombay (2006) and a specialization in Multivariable Control, Distributed State Estimation, and AI/ML for Control Applications , his research focuses on ensuring fault-tolerant and economical operation of microgrids , developing distributed Kalman filtering techniques , and applying machine learning to process monitoring and control . Education: B.E., D. D. Institute of Technology, Gujarat, India Ph.D., IIT Bombay, 2006 Research Interests span Advanced Process Control, Fault Detection and Diagnosis, Cooperative Control, Microgrid Optimization and Control , and Hardware-Software Design for Control Systems . His work addresses challenges in data-driven process monitoring , distributed state estimation , and machine learning-based controller design , particularly for large-scale systems. Scientific Contributions include innovative approaches to inverse-free Kalman filters , reinforcement learning-based PI controllers , and data reduction algorithms for fault diagnosis. His publications reflect a focus on control theory, optimization, and machine learning integration , with applications in power systems, wind energy, and fault diagnostics . Scientific Awards: Best Paper Award at ADCONIP - 2011 Best Paper Award at DYCOPS-2013 Advising has been a significant part of his career, with supervision of Ph.D. students working on topics like fault detection in induction motors , microgrid scheduling , and adaptive control using fuzzy logic . His M.Tech students have explored areas such as visual object tracking, battery SOC estimation, and wind farm control , many of whom are now in prominent roles across academia and industry.

• Geo-AI (Geospatial Artificial Intelligence)
• XR (Extended Reality)
• Machine Learning
• +6 more

Dr. Abolghasem Sadeghi-Niaraki is an Associate Professor in the Department of Computer Science and Engineering at Sejong University's College of Engineering, where he has served since 2017. He leads the eXtended Reality (XR) Research Center and holds a Research Professor position at the Super-Realistic XR Technology Research Center (2022-2030). Previously, he was an Assistant Professor at INHA University's Department of Geo-Informatics Engineering (2009-2017). Recently appointed as a Fellow at Harvard University's Spatial Data Lab (SDL), he conducts collaborative research in spatiotemporal data analytics and geo-AI. Dr. Sadeghi-Niaraki's research spans Geo-AI, XR technologies, Machine Learning, Metaverse applications, and IoT. His work focuses on applying AI to geospatial problems, developing immersive technologies for education and cultural heritage, and creating predictive models for natural hazards. He has secured significant funding for XR Metaverse research from the Ministry of Science and ICT, focusing on Real-Virtual integration. His interdisciplinary approach combines computer science with environmental science, urban planning, healthcare, and education. His research portfolio demonstrates strong trends in geospatial AI applications for environmental monitoring, particularly in natural hazard prediction (floods, wildfires, earthquakes), as well as innovative educational applications of VR/AR. Recent work shows increasing integration of large language models with immersive technologies and a growing focus on healthcare applications within virtual environments. Dr. Sadeghi-Niaraki has received significant recognition including: Top 2% Scientist Worldwide (Stanford-Elsevier 2024) Fellow at Harvard SDL, Center for Geographic Analysis Australian Endeavour Fellowship Recipient Member of IEEE & AAG (American Association of Geographers) He has led over $9.3 million in research funding, supervised 40+ Master's and 6+ Ph.D. students, and collaborated with 14 universities across 8 countries in immersive technology development. His laboratory work centers on the eXtended Reality Research Center at Sejong University, where his team develops patented methods for context-aware AR/VR systems applied to tourism, cultural heritage, and smart city planning.

Moon-Ghu ParkView profile

Professor

• Neutron Detection
• Nuclear Instrumentation & Control
• Charged Particle Transport
• +5 more

Professor Moon-Ghu Park is affiliated with Sejong University's Department of Quantum and Nuclear Engineering. With 30+ years of experience in nuclear R&D, he has held key roles at Korea Electric Power Research Institute (KEPRI) and Korea Hydro & Nuclear Power's Central Research Institute before transitioning to academia in 2013. Ph.D. in Nuclear & Quantum Engineering (KAIST, 1993) M.S. in Nuclear Engineering (KAIST, 1986) B.S. in Nuclear Engineering (Hanyang University, 1984) His research spans neutron detection, nuclear reactor protection systems, and small modular reactor design, with recent focus on nuclear big data analytics and AI applications. His lab develops advanced signal processing techniques for reactor monitoring and safety analysis. 2020-2025 publications demonstrate his work on machine learning for nuclear safety, compressive sensing for detector signal reconstruction, and Monte Carlo simulations for spent fuel analysis. Research keywords include: Nuclear Engineering, Machine Learning, Reactor Physics, Signal Processing, Big Data, and Reactor Safety. ABI American Medal of Honor (2006) Korea Electric Power Corporation R&D Award (2009) Engineer of the Month (2008) Science and Technology Minister Award (2000) Contact: mgpark@sejong.ac.kr | Office: Da 211A | Research lab: Nuclear Instruments and Informatics Lab

Rui LoureiroView profile

Professor

• Biomedical engineering
• Mechanical engineering
• Clinical sciences
• +8 more

Rui Loureiro is a full Professor of Surgical and Rehabilitation Engineering at University College London (UCL), where he leads the Department of Orthopaedics and Musculoskeletal Science and the Aspire Centre for Rehabilitation and Assistive Technology . Since 2017, he has served as Head of the Institute of Orthopaedics and Musculoskeletal Sciences and was appointed Research Director and Chair of the Research & Innovation Board at the NHS-led National Rehabilitation Centre in 2024. His work bridges advanced engineering with clinical applications, focusing on stroke rehabilitation, spinal/brain injuries, bionics, and assistive technologies. Research Interests : Loureiro specializes in Biomedical Engineering Medical Robotics Artificial Intelligence for Rehabilitation Virtual and Mixed Reality in Healthcare Wearable Technologies for Pain Management His publications highlight trends in functional near-infrared spectroscopy (fNIRS), edge computing for neurofeedback, and frugal medical device design. He advocates for interdisciplinary collaboration between engineers and clinicians to address global healthcare challenges. Scientific Recognition : Loureiro has received prestigious awards including SET for Britain Young Engineer Award (2004) IET Emerging Technology Award (2023) He founded the International Consortium on Rehabilitation Robotics (ICORR) and regularly serves as a keynote speaker at global conferences. Teaching Contributions : At UCL, he co-directs MSc programs in Rehabilitation Engineering and Assistive Technologies Minimally-invasive and Virtual Reality Surgery and teaches modules on virtual reality in healthcare and musculoskeletal biomechanics.

Mario LiebensteinerView profile

Assistant Professor

• Energy Markets
• Energy System Analysis
• Environmental Policy
• +4 more

Mario Liebensteiner is a Junior Professor (tenure track W3) for Economics with a focus on Energy Markets and Energy System Analysis at Friedrich-Alexander University Erlangen-Nuremberg (FAU). He is affiliated with the Department of Business, Economics, and Social Sciences (FAU WiSo) and contributes to the interdisciplinary research focus on Energy Markets and Energy System Analysis. Liebensteiner is also a member of the expert panel Energy Systems of the Future (ESYS) of the German Academies of Sciences and Humanities, providing expertise on energy transition and market design. Liebensteiner completed his doctorate in economics at Vienna University of Economics and Business (WU Vienna) and earned his diploma in economics from Johannes Kepler University Linz (JKU Linz) and City University of Hong Kong. Prior to his current position, he worked as a postdoctoral and pre-doctoral researcher at Technical University of Kaiserslautern and Vienna University of Economics and Business. His research focuses on the economic analysis of energy markets, environmental policy, and the transition to sustainable energy systems. Liebensteiner examines the interplay between renewable energy integration, carbon pricing mechanisms, electricity market design, and the challenges of sector coupling in the energy transition. His work investigates how market structures and policy instruments affect investment decisions, system flexibility, and emissions reduction in the power sector, with particular emphasis on the German energy context. He employs both theoretical modeling and empirical analysis to address these complex energy economics questions. Analysis of Liebensteiner's recent publications reveals a strong focus on the economic dimensions of the energy transition, particularly examining the interactions between renewable energy integration, carbon pricing, and electricity market design. His work increasingly addresses the challenges of sector coupling, flexibility needs in power systems, and the socio-economic impacts of energy policies. A notable trend is his examination of both theoretical market mechanisms and their practical implementation in the German context, with growing attention to cross-border electricity trade effects and the integration of hydrogen technologies in future energy systems. Member of the expert panel Energy Systems of the Future (ESYS) of the German Academies of Sciences and Humanities Research published in leading energy economics journals including Energy Economics, Applied Energy, and Energy Policy Liebensteiner collaborates with researchers across disciplines through the Energy Campus Nuremberg (EnCN) and participates in strategic partnerships with energy sector companies organized in the Nuremberg Energy Region (Energieregion Nürnberg eV). His research is connected to the DFG Collaborative Research Center on gas networks and markets, suggesting involvement in significant research funding. While specific grants aren't detailed in the provided information, his publication record in high-impact journals indicates successful research funding acquisition. Liebensteiner is part of the Energy Markets and Energy Systems research group at FAU WiSo, which collaborates closely with engineers at the Energy Campus Nuremberg (EnCN). This interdisciplinary team works on the transformation of electricity and gas sectors, sustainable mobility concepts, sector coupling issues, and business models for decentralized smart energy systems. The research group maintains strategic partnerships with numerous energy sector companies through the Nuremberg Energy Region, aiming to implement secure, cost-effective, climate-friendly, and sustainable energy solutions.

Francis ZvomuyaView profile

Professor

• Soil Remediation
• Contaminant Fate and Transport
• Phytoremediation
• +5 more

Dr. Francis Zvomuya serves as a Professor in the Department of Soil Science within the Faculty of Agricultural and Food Sciences at the University of Manitoba's Fort Garry Campus. His research laboratory operates from 364 Ellis Building (13 Freedman Crescent, Winnipeg, Manitoba R3T 2N2), with direct contact via 204-474-9932 or francis.zvomuya@umanitoba.ca. His academic foundation includes: PhD in Soil Science from the University of Minnesota (USA) MSc in Soil Science from the University of Reading (UK) BSc in Agriculture from the University of Zimbabwe Dr. Zvomuya's research program centers on environmental soil processes with four interconnected pillars: remediation of contaminated media, beneficial utilization of agricultural/industrial byproducts, reclamation of human-disturbed sites, and antibiotic fate/transport in terrestrial-aquatic systems. His current projects investigate soil health on reclaimed pipeline corridors, wetland-based phytoremediation of end-of-life municipal lagoons, agronomic value of recovered phosphorus, soil health under perennial forage-grain systems, and organic amendments for wellsite reclamation. His methodological approach integrates field studies, laboratory bioassays, and meta-analyses to address practical environmental challenges. Analysis of his 2023-2025 publications reveals dominant themes in soil health monitoring (particularly on reclaimed lands), phytoremediation of antibiotics/phosphorus, and soil physical property recovery in seasonally frozen environments. His work frequently employs meta-analytical techniques for Chinese orchard systems, machine learning applications for soil moisture modeling, and innovative approaches to wastewater treatment using cattail/switchgrass. The Canadian Prairie context features prominently in pipeline reclamation studies, while global collaborations extend to Chinese agricultural systems and Tibetan Plateau landslide monitoring. Scientific awards: No specific awards or fellowships are documented in the source materials. Dr. Zvomuya actively supervises graduate students through research projects and teaches advanced courses including SOIL 7220 (Principles of Scientific Research and Communication) and SOIL 7250 (Non-traditional Quantitative Techniques in Soil Science Research). While specific grant details are not provided, his extensive publication record across soil remediation, nutrient cycling, and contaminant transport indicates substantial external research funding. His laboratory infrastructure supports soil physical/chemical analyses with capabilities in phytoremediation trials, antibiotic fate studies, and advanced soil health assessment.

Andreas VlachidisView profile

Associate Professor

• Natural Language Processing
• Semantic Technologies
• Information Extraction
• +7 more

Dr. Andreas Vlachidis is an Associate Professor in the Department of Information Studies at University College London (UCL), Faculty of Arts and Humanities. He serves as Co-Investigator and Technical Lead of the Sloane Lab, Principal Investigator of the 'Text Analytics for inclusive AI education platforms' project, and convenor of the Alan Turing Research Interest Group – Humanities and Data Science. Previously, he held academic positions at the University of the West of England and University of South Wales. His educational background includes a PhD in Semantic Indexing of Archaeological Grey Literature, MSc, and dual BSc degrees from the University of Glamorgan. He is a Fellow of the Higher Education Academy (FHEA) and a member of the British Computing Society (BCS). Dr. Vlachidis's research focuses on interdisciplinary work at the intersection of Information Science, Humanities, and Computer Science. His primary interests include Information Extraction, Semantic Data Modeling, Metadata, Natural Language Processing, and Text Mining, with applications in cultural heritage, digital humanities, and social sciences. His work emphasizes data integration, FAIR data principles, and semantic interoperability for cultural heritage collections. His recent publications demonstrate expertise in cultural heritage data modeling, semantic technologies for historical collections, NLP applications, and inclusive AI education. His work with the Sloane Lab project has been particularly influential in advancing knowledge base development for historical catalogues and museum collections. Outstanding Paper award from the Emerald Literati Network Fellow of the Higher Education Academy (FHEA) Member of the British Computing Society (BCS) Dr. Vlachidis supervises multiple doctoral students including Liu Lu (principal supervisor) and secondary supervises Binxia Xu, Charlotte Heng Men, and George Cooper. He has previously supervised to completion Helena Holis, Diego Ramírez Echavarría, and Olga Loboda. He serves as Departmental Tutor for pastoral care of students and chairs important committees including the Departmental Staff Student Consultative Committee. He leads significant research projects including the Sloane Lab (data unification, aggregation, and knowledge base development) and 'Text Analytics for inclusive AI education platforms' (promoting literacy development and writing skills). He also collaborates with the EU Horizon 2020 Ariadne Plus project on multilingual processing of archaeological literature.

Marc ChevretteView profile

Assistant Professor

• Natural Product Discovery
• Genome Mining
• Microbial Interactions
• +4 more

Marc Chevrette serves as an Assistant Professor and Discovery Fellow in the Department of Plant Pathology at the University of Wisconsin–Madison's College of Agricultural and Life Sciences, with laboratory operations based in the Discovery Building. His interdisciplinary research bridges genomics, bioinformatics, and microbiology to investigate microbial secondary metabolism and interspecies interactions within complex communities. Education: PhD in Genetics, University of Wisconsin–Madison Dr. Chevrette's research program centers on evolutionary-guided natural product discovery, specializing in genome mining for novel antibiotics and biosynthetic pathway characterization. His lab develops computational tools like GATOR-GC to map biosynthetic diversity across bacterial lineages, with particular emphasis on lasso peptides, nonribosomal synthetases, and microbial community dynamics. This work integrates phylogenetics with experimental validation to uncover chemical ecology principles driving secondary metabolism. Analysis of his 2023-2025 publications reveals consistent innovation in bioinformatics infrastructure (antiSMASH, MIBiG) and machine learning applications for substrate specificity prediction. His research demonstrates strong translational potential for antimicrobial discovery, with recurring themes of evolutionary adaptation in biosynthetic gene clusters and community-mediated metabolite regulation. Scientific Awards: Discovery Fellow (Wisconsin Institute for Discovery) Dr. Chevrette directs an active research group supported by federal grants focused on antibiotic discovery and microbial ecology. His mentorship includes training graduate students in interdisciplinary methodologies spanning computational biology, microbial genetics, and natural product chemistry, with emphasis on translating genomic insights into experimental validation. The Chevrette Lab operates within the Wisconsin Institute for Discovery, leveraging its collaborative environment to integrate genomic data with ecological modeling. Current projects investigate how nutrient availability and interspecies competition shape biosynthetic potential in soil and marine microbial communities, with implications for drug discovery pipelines.