جست‌وجوی استاد و پژوهشگر

Ian Bradleyمشاهده پروفایل

استادیار

• Environmental Engineering
• Water Treatment
• Wastewater Management
• +۳ مورد دیگر

Ian Bradley is an Assistant Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo, State University of New York. His research focuses on creating sustainable biological processes to address needs in engineered and natural systems for water and wastewater treatment and resource recovery. Education: PhD in Environmental Engineering, University of Illinois at Urbana-Champaign (2017) MS in Environmental Engineering, University of Illinois at Urbana-Champaign (2011) MS in Civil Engineering (Structures), University of Illinois at Urbana-Champaign (2010) Research Interests: Dr. Bradley specializes in microalgal-based nutrient recovery, wastewater surveillance for public health monitoring, PFAS degradation using nanomaterials, and sustainable resource recovery systems. His work integrates biological processes with environmental engineering to optimize wastewater treatment efficiency and develop predictive models for water quality and health outcomes. Publications: His recent research includes advancements in microalgal cultivation (EcoRecover process), wastewater-based epidemiology for SARS-CoV-2 tracking, and computational enzyme design for PFAS remediation. These studies demonstrate interdisciplinary expertise spanning environmental engineering, biotechnology, and public health analytics.

Sibel Adaliمشاهده پروفایل

استاد

• Trust in Networks
• Social Networks
• Databases
• +۵ مورد دیگر

Sibel Adali is a Professor in the Department of Computer Science at Rensselaer Polytechnic Institute’s School of Science. She joined RPI in 1996 after earning her PhD from the University of Maryland. Her academic roles include Associate Head and Graduate Program Director of the Computer Science Department (2015-2018) and currently serving as Associate Dean of Science for Research and Graduate Studies at RPI. She teaches foundational Computer Science courses in problem-solving and databases. Education: PhD from University of Maryland. Adali’s research focuses on trust modeling, social networks, information retrieval, and semantic analysis. She has led cross-cutting projects addressing cognitive science intersections with network theory, including roles as ARL-lead CTA Trust Coordinator and SCRNARC Associate Director. Her work explores misinformation mitigation, semantic shifts in language, and expert identification in social media ecosystems. Recent publications highlight her contributions to fake news detection, semantic change modeling, and AI-driven misinformation interventions. Her research trends emphasize interdisciplinary approaches combining machine learning, computational linguistics, and behavioral studies. Scientific Awards: Trustees' Outstanding Teacher Award (2015), Rensselaer Polytechnic Institute’s highest teaching honor. Adali actively collaborates on grants and projects through research centers including MOCA, IDEA, SCNARC, and ARL CTA partnerships. She advises students on advanced computational research and participates in military communications technology initiatives.

• Invasive Species Ecology
• Conservation Biology
• Population Dynamics
• +۴ مورد دیگر

Richard DUNCAN is a Professor in Conservation Biology at the University of Canberra's Science School and Department of Centre for Conservation and Ecology Genetics. His research focuses on the ecology of invasive species, particularly understanding how introduced species arrive, establish, and spread in new environments. Key areas include invasive weeds and pests, ecological community structure, and applying quantitative methods to address both fundamental and applied ecological questions. Education: PhD in Forest Ecology, University of Canterbury (1989, award date noted as 2024 in text) Research Interests: His work spans invasive species ecology, population dynamics, and restoration strategies. He employs diverse methods including field experiments, modeling, and genomics, with recent focus on grasslands and aquatic systems. Current projects address amphibian chytrid fungus, carp invasions, and rodent control. Articles Trends: Recent publications emphasize invasive species impacts on ecosystems, pathogen-driven niche contractions, and conservation tools like geospatial modeling and genomic simulations. Themes include species distribution modeling, pest management, and restoration ecology. Awards & Grants: Lead investigator on 35+ projects, including ARC Plant Biosecurity Training Centre and chytrid fungus mitigation efforts Associate Editor for Proceedings of the Royal Society B and Diversity and Distributions Advising: Accepting PhD students in invasive species ecology, with focus on using biological invasions to explore ecological theory and management applications. Labs/Teams: Collaborates widely on conservation genetics, aquatic invasions, and biosecurity, including work with the Biological Heritage Science Challenge and Indigenous Grasslands Trust.

• Entrepreneurship
• Venture Capital
• Blockchain and Cryptocurrencies
• +۷ مورد دیگر

Christian FISCH is an Associate Professor in Business Economics and Entrepreneurship at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT). His research focuses on the intersection of entrepreneurship with digital technologies, venture finance, and socio-cultural influences. Key areas include blockchain-based financing mechanisms (e.g., ICOs), the psychological and digital identity aspects of entrepreneurs, and the impact of environmental/climate factors on entrepreneurial activity. He has published extensively in top journals, addressing topics such as B Corp certification signaling effects, venture capital decision-making, and the paradox of technology adoption among SMEs. His work spans both theoretical contributions (e.g., extending Schumpeterian frameworks) and applied analyses (e.g., post-pandemic entrepreneurial resilience). FISCH collaborates with global institutions, leveraging mixed-methods approaches including digital trace analysis from platforms like Twitter to study investor behavior and entrepreneurial traits. He has no listed awards but maintains active research agendas in decentralized finance, climate entrepreneurship, and cross-cultural entrepreneurial motivations. Professional activities include editorial roles in entrepreneurship journals and advising on innovation policy. His research often addresses emerging trends such as NFTs in creative industries, DAO governance structures, and the role of trademarks/patents in regional innovation ecosystems.

Stefano Galelliمشاهده پروفایل

دانشیار

• Environmental and Water Resources Systems Engineering
• Water Systems
• Energy and the Environment
• +۶ مورد دیگر

Stefano Galelli is a tenured Associate Professor in the School of Civil and Environmental Engineering at Cornell University, where he leads the Critical Infrastructure Systems Lab. He also holds an adjunct position as a Research Scientist at the Lamont-Doherty Earth Observatory, Columbia University. His career spans roles in Singapore, including a Postdoctoral Research Fellow at NUS (2011–2013) and faculty at the Singapore University of Technology and Design (2013–2023). Dr. Galelli earned his B.Sc. (2004), M.Sc. (2007), and Ph.D. (2011) in Environmental and Land Planning Engineering and Information Technology from Politecnico di Milano, Italy. His research focuses on the interactions between critical infrastructure systems and natural environments, emphasizing adaptive management solutions for water-energy systems. Techniques include process-based modeling, climatology, statistical learning, control theory, and optimization. He explores topics like hydro-climatic variability impacts, dam re-operation for environmental flows, and cyber-physical security in infrastructure. His contributions to journals such as Nature Sustainability, Earth’s Future, and Environmental Modelling & Software have earned him multiple awards, including the Early Career Research Excellence Award (2014) and SUTD Excellence in Research Award (2017). He has served as an editor for several journals and is recognized for advancing interdisciplinary approaches to water-energy nexus challenges. Teaching highlights include foundational mathematics courses and advanced topics in data analytics, optimization, and water-energy management. He is developing new courses on data-driven control of coupled human-natural systems and risk management for interconnected systems.

• Machine Learning
• Generative Artificial Intelligence
• Computational Models of Human Behavior
• +۳ مورد دیگر

Mirco Musolesi is a Full Professor of Computer Science at both University College London (UCL) and the University of Bologna. He leads the Machine Intelligence Lab at UCL, part of the UCL Centre for Artificial Intelligence. His research focuses on Machine Learning, Generative AI, and computational models of human behavior, with applications in ubiquitous systems and societal impacts of AI. Education: PhD in Computer Science from UCL (2007) and Laurea in Electronic Engineering from the University of Bologna (2002). Previous roles include positions at the University of Birmingham, Dartmouth College, and the Alan Turing Institute. Research spans multi-agent systems, reinforcement learning, and AI ethics. Notable awards include ACM UbiComp 10-Year Impact Award (2020/2024) and the NetExplorateur/UNESCO Top 100 Innovations (2011). His work on EmotionSense and CenceMe applications has been recognized with Test-of-Time awards. Recent publications (2024-2025) address moral alignment in AI agents, multi-agent environmental policy simulations, and creativity in LLMs. His labs explore AI-driven solutions for urban systems and ethical decision-making frameworks.

Thomas Smithمشاهده پروفایل

دانشیار

• Wildland fires
• Air pollution
• Tropical environmental change
• +۵ مورد دیگر

Thomas Smith is an Associate Professor in Environmental Geography at the London School of Economics (LSE), specializing in wildland fires, tropical environmental change, and peatland management. He joined LSE in 2018 after lecturing at King’s College London and has held visiting fellowships at institutions including the National University of Singapore and Monash University Malaysia. His research focuses on biomass burning’s role in the Earth system, particularly greenhouse gas emissions from tropical peatlands and savannas. Smith’s expertise includes infrared spectroscopy, wildfire modeling, and land management decision support. He emphasizes interdisciplinary approaches to address fire emissions, agricultural practices, and their environmental impacts. Notable awards include being Highly Commended for Research Guidance & Support at the LSESU Teaching Excellence Awards 2019. His recent work involves field experiments (e.g., GAMBUT project) and citizen science initiatives to measure air pollution. Collaborative research spans global wildfire dynamics, climate change impacts, and policy interventions in Southeast Asia’s haze season. Smith contributes to both academic discourse and practical solutions for sustainable land use and climate resilience.

Sudha Ramمشاهده پروفایل

استاد

• Big Data Analytics
• Business Intelligence
• Large Scale Network Science
• +۱۲ مورد دیگر

Sudha Ram is the Anheuser-Busch Endowed Professor of MIS, Entrepreneurship & Innovation at the Eller College of Management, University of Arizona. She holds joint faculty appointments as Professor of Computer Science and is a member of the BIO5 Institute and the Institute for the Environment. She is also the Director of INSITE: Center for Business Intelligence and Analytics, a leading research center in data-driven decision-making. Her research focuses on Big Data Analytics , Business Intelligence , Large Scale Network Science , and Machine Learning , with applications in healthcare, smart cities, environmental policy, and social media. She has pioneered methods in explainable AI, conceptual modeling, and multimodal data fusion, integrating statistical, ontological, and machine learning approaches. Recent publications demonstrate a strong trend in healthcare analytics (e.g., asthma, diabetes, fracture prediction), explainable AI (ROLEX, argumentation-based models), and urban/smart systems (mobility, wearables, environmental impact). Her work consistently appears in top-tier journals and conferences, reflecting sustained scholarly impact. AIS Fellow (2018) INFORMS ISS Distinguished Fellow IBM Faculty Award Peter Chen Award Best Paper Award, IEEE Smart Cities (2016) Best Paper Award, ACM Digital Health (2016) Woman of Impact Award, University of Arizona (2023) Dr. Ram has secured over $70 million in research funding from agencies like NSF, NASA, CIA, and corporations including IBM, Intel, and SAP. She has mentored numerous students and leads a multidisciplinary research team at INSITE. She has held editorial leadership roles in Information Systems Research , Journal of AIS , and is founding co-editor of the Journal of Business Analytics . She directs the INSITE Center, which fosters collaboration across business, computer science, and health domains, enabling large-scale data synthesis and knowledge discovery. The center supports projects in healthcare innovation, smart cities, and environmental policy analytics.

Bart Somersمشاهده پروفایل

دانشیار

• Combustion Engineering
• Alternative Fuels
• Internal Combustion Engines
• +۳ مورد دیگر

Bart Somers is an Associate Professor at Eindhoven University of Technology , affiliated with the Department of Mechanical Engineering . His primary affiliations include the Power & Flow Group and his own research group, Group Somers , alongside cross-cutting roles in EAISI (Eindhoven Artificial Intelligence Systems Institute) and EIRES (Eindhoven Research on Innovation and Sustainability in Energy Systems). He focuses on advancing combustion science , sustainable fuels , and engine efficiency , leveraging computational fluid dynamics (CFD) and experimental methods. His research interests span alternative fuels (hydrogen, bio-oils, biofuels), high-pressure spray combustion , and low-emission engine design . He investigates combustion optimization through CFD tools like large-eddy simulation (LES) and flamelet-generated manifolds (FGM), emphasizing fuel stratification , ignition dynamics , and emission control . His work bridges experimental diagnostics (e.g., spray visualization, OH* chemiluminescence) and numerical modeling. Academically, he teaches courses such as Thermodynamics , Clean Engines and Future Fuels , and Sustainable Vehicles , integrating practical projects into curricula. His educational activities emphasize interdisciplinary sustainability and innovation, including honors programs focused on professional development. Recent publications highlight his contributions to hydrogen injection strategies, biofuel applications in genset engines, and optimization of diesel-biofuel blends. His work aligns with global sustainability goals, addressing energy transition challenges through advanced combustion technologies.

Monica Lamمشاهده پروفایل

استاد

• Artificial Intelligence
• Privacy-Preserving Technologies
• Compiler Design
• +۴ مورد دیگر

Monica Lam is the Kleiner Perkins, Mayfield, Sequoia Capital Professor in Stanford University's School of Engineering and holds a courtesy professorship in Electrical Engineering. She leads the Stanford Open Virtual Assistant Laboratory and has pioneered work in virtual assistants, privacy protection, and compiler design. Her research includes the Almond virtual assistant, privacy-preserving IoT systems, and the ThingTalk programming language. She co-authored the seminal 'dragon book' on compilers and co-founded Tensilica (now part of Cadence). Education: Bachelor of Science (Honors), Computer Science, University of British Columbia, 1980 Master of Science, Computer Science, Carnegie Mellon University, 1982 Doctor of Philosophy (PhD), Computer Science, Carnegie Mellon University, 1987 Research Interests: Dr. Lam's work focuses on conversational AI with privacy guarantees, compiler optimization for parallel computing, and open-source virtual assistant ecosystems. She is a leader in decentralized systems, having developed frameworks like SociaLite for large-scale graph analysis and Musubi for mobile social networking without centralized platforms. Article Trends: Recent publications emphasize multimodal interactions, multilingual dialogue systems, and LLM-driven applications in areas like question answering, persuasive chatbots, and adaptive assistants. Her work bridges foundational AI research (e.g., semantic parsing) with real-world deployments (e.g., privacy-compliant IoT). Awards & Honors: Member of the National Academy of Engineering ACM Fellow Popular Science's Best of What's New Award (Security, 2019) Advising & Grants: Lam oversees the Open Virtual Assistant Initiative, a collaborative project to build open-source semantic models. Her NSF CNS grant (CNS Core) focuses on federated privacy systems. She has advised over 50 students in AI and systems research, though specific names are not listed in the provided texts. Labs & Teams: Directs the Stanford Open Virtual Assistant Laboratory, collaborates with the Stanford NLP group, and maintains ties to industry through former startup Tensilica's legacy in embedded processors.

Jerelle A. Josephمشاهده پروفایل

استادیار

• Biomolecular Condensates
• Phase Separation
• Computational Biology
• +۴ مورد دیگر

Jerelle A. Joseph is an Assistant Professor at Princeton University , affiliated with the Department of Chemical and Biological Engineering and the Omenn-Darling Bioengineering Institute . They also hold associated faculty roles in the Department of Chemistry , Andlinger Center for Energy and the Environment , Princeton Institute for Computational Science and Engineering , and the Biophysics Graduate Program . Research Interests : The Joseph Group investigates the physicochemical principles governing biomolecular condensate formation, dissolution, and misregulation . Their work focuses on phase separation mechanisms , computational modeling of protein-RNA interactions , and engineering condensates for biomedical and sustainability applications , including therapeutic targeting of neurodegenerative diseases and design of synthetic microreactors . Scientific Awards : NIGMS MIRA (R35) Award (2024) Biophysical Society Award Lecture (2024) Chan Zuckerberg Initiative Investigator (2023) Postdoctoral Award, Biophysical Society IDP Subgroup (2022) Rising Star in Soft and Biological Matter (University of Chicago, 2020) Advising : Dr. Joseph advises graduate students including Ananya Chakravarti , Dominic Curtis , and Pablo Garcia . The group develops chemically-specific coarse-grained models using molecular dynamics , Monte Carlo sampling , and machine learning to study condensate microstructure , aging dynamics , and surface electrostatics .

Mohammed Aledhariمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Data Science
• +۳ مورد دیگر

Mohammed Aledhari is an Assistant Professor at the University of North Texas, specializing in cybersecurity, machine learning, and data science. His research focuses on applications in computational medicine, bioinformatics, and autonomous systems. He holds a Ph.D. from Western Michigan University and degrees from the University of Basrah and the University of Anbar. His research interests include social cybersecurity techniques, federated learning in IoT, and AI-driven solutions for healthcare and transportation. Recent work explores blockchain-enabled digital twins, DDoS attack detection, and equitable ASD diagnostics using machine learning. His publications span cybersecurity frameworks, autonomous vehicle communication protocols, and biomedical IoT innovations. Notable contributions include optimizing intrusion detection in IoMT networks and developing interpretable machine learning models for healthcare. While no formal awards or grants are listed, his work emphasizes interdisciplinary applications of AI in healthcare, transportation, and energy markets. His email is Mohammed.Aledhari@unt.edu .

James Herbert-Readمشاهده پروفایل

دانشیار

• Behavioural Ecology
• Marine Biology
• Collective Animal Behaviour
• +۴ مورد دیگر

Dr James Herbert-Read is an Associate Professor and Whitten Lecturer in Marine Biology at the Department of Zoology, University of Cambridge. He serves as Deputy Head of Department (Postgraduate Education) and leads the Marine Behavioural Ecology Group. His research focuses on understanding how animals, particularly marine organisms, collect and process information from their environments to make behavioral decisions, with emphasis on social interactions, adaptation mechanisms, and ecological constraints. His group employs theoretical frameworks, controlled experiments, and quantitative field studies to investigate behavioral diversity in marine species. Key themes include collective behavior, predator-prey dynamics, camouflage strategies, and the impacts of environmental stressors on animal decision-making. Recent publications highlight work on lionfish vocalization mechanisms, cuttlefish camouflage, citizen science applications in marine research, and behavioral responses to visual and acoustic noise. Scientific awards and affiliations include: Whitten Lecturer in Marine Biology Associate Professor, University of Cambridge He has supervised research projects on topics such as: Social attraction in invasive fish species Evolution of coordinated movement Neurophysiological basis for leadership in shoals Maternal effects on offspring exploration

Paul Pu Liangمشاهده پروفایل

استادیار

• Multimodal Machine Learning
• Human-AI Interaction
• Generative AI
• +۳ مورد دیگر

Paul Pu Liang is an Assistant Professor at the Massachusetts Institute of Technology (MIT) Media Lab and Department of Electrical Engineering and Computer Science (EECS). He directs the Multisensory Intelligence research group, focusing on building AI systems that integrate diverse sensory inputs to enhance human-AI symbiosis. His work spans theoretical foundations, large-scale resources, and neural architectures for multisensory learning. Education: PhD in Machine Learning (Carnegie Mellon University), MS in Machine Learning (Carnegie Mellon), BS with University Honors in Computer Science and Neural Computation (Carnegie Mellon) Research Interests: Multimodal machine learning, human-AI interaction, clinical AI, generative models, and responsible deployment of AI systems Key Contributions: MultiBench, HEMM evaluation framework, CLIMB clinical data foundations, and multimodal transformer architectures Recent publications emphasize multimodal foundation models , clinical applications , and socially responsible AI . His work has been recognized with multiple best paper awards and fellowships from Siebel, Facebook, and other institutions. Scientific Awards Siebel Scholars Award Waibel Presidential Fellowship Facebook PhD Fellowship Center for ML and Health Fellowship Rising Stars in Data Science Four best paper awards Paul teaches courses on machine learning and multimodal AI at MIT and CMU. He mentors students across multiple programs including Media Arts & Sciences, EECS, and IDSS, with former advisees now at institutions like OpenAI, UC Berkeley, and Princeton.

Giorgio Ascoliمشاهده پروفایل

استاد

• Computational Neuroanatomy
• Neuroinformatics
• Neuronal Morphology
• +۵ مورد دیگر

Giorgio Ascoli is a University Professor in the Department of Bioengineering at George Mason University, where he has been since 1997. He is the Founding Director of the Center for Neural Informatics, Structures, & Plasticity (CN3) and Founding Editor-in-Chief of the journal Neuroinformatics . His affiliations span computational neuroanatomy, neuroinformatics, and hippocampal modeling. Education : PhD in Biochemistry and Neuroscience (1996), Scuola Normale Superiore; MS in Chemistry and Biochemistry (1993), Pisa University; BS in Chemistry and Physics (1991), Scuola Normale Superiore. Dr. Ascoli investigates the relationship between brain structure, activity, and function from cellular to circuit levels. His research focuses on anatomically plausible neural networks to model mammalian brains, particularly the hippocampus, with implications for understanding human memory and consciousness . He pioneered computational neuroanatomy, developing tools like L-Neuron for neuronal shape modeling and curating NeuroMorpho.Org , a central repository for digitally reconstructed neurons. His recent publications emphasize neuronal classification , connectome analysis , and biologically informed machine learning . Awards include the 2012 Outstanding Faculty Award (Virginia), 2022 AIMBE fellowship , and 2023 Presidential Faculty Excellence Awards . He has mentored over 20 graduate students and postdoctoral fellows, with funding from NIH, NSF, DARPA, and private foundations. Scientific Contributions : Over 137 peer-reviewed articles, 4 patents, 2 authored/edited books, and leadership in NeuroMorpho.Org and Hippocampome. Grants : $20M+ in cumulative funding, including NIH R01s, NSF BRAIN EAGERs, and Burroughs-Wellcome Trust support. Labs : Leads the Computational Neuroanatomy Group within CN3, focusing on hippocampal modeling, neuronal morphology, and consciousness theories.