جست‌وجوی استاد و پژوهشگر

• Medicinal Chemistry
• Computational Chemistry
• Drug Design
• +۳ مورد دیگر

David Chalmers is an Associate Professor in Medicinal Chemistry at Monash University's Faculty of Pharmacy and Pharmaceutical Sciences, affiliated with the Monash Institute of Pharmaceutical Sciences. He specializes in computational drug design, focusing on molecular dynamics simulations, machine learning, and peptide chemistry to develop novel therapeutics targeting diseases like heart failure, Alzheimer’s, and HIV. His research integrates computational modeling with experimental validation to address challenges in drug-receptor interactions and drug formulation stability. He leads multiple interdisciplinary projects funded by the National Health and Medical Research Council (NHMRC) and collaborates globally on drug discovery initiatives. Research Interests: Computational chemistry, drug design, peptide analogues, AI-driven drug discovery, lipid-based formulations. Key Projects: Alpha1-adrenoceptor drug development for heart failure/Alzheimer’s, HIV reverse transcriptase inhibitors, mRNA lipid nanoparticle stability. Recent Work: Over 110 publications (2022-2025), including studies on peptide antagonists, molecular dynamics of drug formulations, and AI-enhanced molecular property prediction. His work contributes to UN Sustainable Development Goals related to good health and well-being, advancing precision medicine through innovative computational approaches.

Vijay Singhمشاهده پروفایل

استاد

• Radiation Biology
• Radiation Medical Countermeasures
• Biomarkers
• +۳ مورد دیگر

Dr. Vijay Singh is a Professor in the Department of Pharmacology & Molecular Therapeutics at the Uniformed Services University of the Health Sciences (USUHS). His research focuses on developing radiation medical countermeasures and identifying biomarkers for radiation injury assessment. He leads advanced development of agents like BIO 300 (genistein) and gamma-tocotrienol under FDA Animal Rule guidelines. His work integrates multi-omics approaches (metabolomics, proteomics, transcriptomics) to evaluate countermeasure efficacy and predict radiation injury outcomes. Education: Ph.D., Central Drug Research Institute, Lucknow (KU), India (1983) Postdoctoral Fellow, USUHS (1984–1987) Visiting Scientist, National Eye Institute, NIH (1987–1997) Research Interests: Radiation biology, radiation countermeasure development, omics-based biomarker discovery, and translational drug development for acute radiation syndrome (ARS) and delayed effects of acute radiation exposure (DEARE). His lab investigates radioprotectors like amifostine, BBT-059, and Ex-Rad using nonhuman primate models. Funding Highlights (Selected): $8.5M BARDA grant for radiation countermeasure evaluation in NHP models $1.2M NIH/NIAID award for proteomic biomarker studies $4.7M CDMRP grant for BIO 301 development Awards: Honorary Professor title from Amity University, India, and unspecified prestigious awards. Serves on NATO HFM-359 committee and teaches at NATO StTARS workshop. Labs/Teams: Collaborates with academic and corporate partners globally to advance radiation countermeasures through preclinical and translational research programs.

Sheng-feng Qinمشاهده پروفایل

استاد

• Digital Design Technology
• Smart Product and Service Design
• Design Optimization
• +۶ مورد دیگر

Professor Sheng-feng Qin is a faculty member at the Northumbria School of Design, Northumbria University, since 2014. He holds the academic rank of Professor and serves as the Director of the MA Design Programme. His research focuses on digital design and manufacturing, smart technologies, and sustainable urbanization. He leads the Smart Design Lab, exploring AI-driven design methods and interdisciplinary approaches for smart products and services. Professor Qin's educational background includes a PhD in Craft, Design, and Technology (2000) and a BEng in Manufacturing Engineering (1983). He is a Fellow of the Higher Education Academy (FHEA) and a member of IEEE. His work has been recognized with the 2019 Newton Prize for collaborative research on sustainable urbanization. His research interests encompass digital design technology, smart cities, crowdsourcing in product development, and emotion-centric design. He has supervised multiple PhD students focusing on topics like digital twins for elderly care, smart transportation systems, and emotion regulation tools. Professor Qin collaborates internationally, including as a Visiting Professor at Southwest Jiaotong University and through joint labs with Chinese institutions. He also serves as Editor-in-Chief of the International Journal of Rapid Manufacturing and on editorial boards of other journals.

• Quantum Computing
• Machine Learning
• Combinatorial Optimization
• +۳ مورد دیگر

GOH Siong Thye is an Adjunct Lecturer at the Lee Kong Chian School of Business, Singapore Management University. He teaches courses such as Decision Analysis and focuses on interdisciplinary research spanning quantum computing, machine learning, and optimization techniques. His work addresses challenges in high-dimensional data analysis, combinatorial optimization, and algorithm design for quantum systems. Education: Not explicitly stated in the provided text. Research interests include quantum algorithms for differential equations, interpretable density estimation methods, and applications of machine learning in industrial systems such as gas turbine failure detection. He explores hybrid quantum-classical frameworks for solving complex combinatorial problems, leveraging QUBO formulations and variational approaches. His articles highlight contributions to areas like quantum volunteer’s dilemma in game theory, sparse coding methodologies, and surrogate model-based optimization techniques. Notable topics include enhancing QUBO solvers through recommendation systems and developing frameworks for intelligent crime response scheduling. No scientific awards or grants are mentioned in the provided texts. He advises no formally listed students, though his collaborative work may involve academic partnerships.

• Data-Driven Service Operations
• Network Optimization
• Markov Decision Process
• +۶ مورد دیگر

Yanlu Zhao is an Associate Professor in Operations Management at Durham University Business School. His research focuses on data-driven service operations and supply chain management, with applications in network optimization, Markov decision processes, dynamic programming, and machine learning. He holds a doctoral degree from ESSEC Business School and a master's from Tsinghua University. In 2024, he is on research leave at Hong Kong Polytechnic University's Department of Logistics and Maritime Studies. He has received the ESSEC Foundation PhD Award (2019) and regularly presents at international conferences. His work addresses challenges in healthcare systems, online platforms, and vehicle routing, emphasizing robust strategies for operational efficiency. Education: PhD, ESSEC Business School, France MSc in Management Science and Engineering, Tsinghua University, China Research Interests: His primary research areas include: Dynamic scheduling and routing in service systems Applications of machine learning in operational contexts Optimization of healthcare and food delivery systems Competitive facility location modeling Key Awards: ESSEC Foundation PhD Award (2019) Advising & Grants: Supervises students like Qidi Wu and Zibo Zhang. His research has been supported by grants exploring carbon emissions compliance and market thickness in online platforms. Labs/Teams: Engaged with IORA at National University of Singapore (2019) and collaborates with institutions on sustainable supply chain initiatives.

Zhao Bingyuمشاهده پروفایل

استادیار

• Transportation Engineering
• Disaster Management
• Urban Planning
• +۳ مورد دیگر

Dr. Zhao Bingyu is an Assistant Professor in the Department of Transport Planning and Traffic Engineering at TU Wien. His research focuses on transportation systems resilience, agent-based simulation models, and disaster management. He investigates how communities and infrastructures respond to challenges like earthquakes, wildfires, and floods, emphasizing behavioral analysis and multi-system interactions. Key research areas include urban infrastructure resilience, emergency evacuation modeling, and data-driven approaches for traffic and transit systems. Notable projects include studies on the Port of Los Angeles under seismic hazards and wildfire evacuation strategies for vulnerable communities. His work integrates empirical observations with computational frameworks to enhance decision-making in disaster scenarios. Dr. Zhao has presented extensively on topics such as multi-infrastructure network resilience and community resilience through simulation models. He is affiliated with the Network Lab at TU Wien and collaborates with global researchers on projects addressing urban safety and infrastructure vulnerability.

Kashaf Junaidمشاهده پروفایل

مدرس

• Infectious Diseases
• Antibiotic Resistance
• Medical Imaging AI
• +۷ مورد دیگر

Kashaf Junaid is a Lecturer in Parasitology & Infectious Diseases at Queen Mary University of London's School of Biological and Behavioural Sciences. His research focuses on antibiotic resistance mechanisms, parasitic infections, medical imaging AI, and public health challenges. He collaborates on global health issues such as tuberculosis, malaria, and emerging pathogens like Naegleria fowleri. Research interests span microbiology, epidemiology, and translational medicine. Recent work includes leveraging machine learning for disease diagnosis, ethnobotanical studies of traditional healing practices, and investigating genetic factors in infectious diseases. Publications highlight contributions to antimicrobial resistance studies, viral and bacterial pathogenesis, and the development of novel diagnostic tools. He advocates for interdisciplinary approaches to address public health crises, particularly in low-resource settings. No academic awards or grants are explicitly listed in the provided texts. His work intersects lab-based research with clinical applications, though specific lab affiliations are not detailed.

• Movement Ecology
• Collective Animal Behavior
• Insect Ecology
• +۵ مورد دیگر

Dr. Camille Buhl is a Senior Lecturer in Plant Protection at the School of Agriculture, Food and Wine within the Faculty of Sciences, Engineering and Technology at the University of Adelaide. Her work focuses on understanding insect movement and collective behavior through interdisciplinary approaches combining experimental biology, computational modeling, and robotics. Research Interests: Buhl's research explores movement ecology, collective animal behavior, and their applications to agriculture and pest control. Key areas include locust collective movement modeling, termite nest construction mechanisms, and social insect nutrition dynamics. She employs cutting-edge technologies like drones, radar tracking, and machine learning for field monitoring. Current Projects: Her team develops robotic systems for pest detection, simulates locust band migrations using CUDA-based models, and investigates termite nest architecture evolution through computed tomography and mathematical biology. Collaborations include the Plant Accelerator, SARDI Entomology, and ECMS researchers. Grants & Supervision: Buhl is eligible to supervise Masters and PhD candidates focusing on animal behavior, computational ecology, and AgTech applications. Her work bridges ecological theory with practical agricultural solutions, emphasizing sustainable pest management strategies. Labs & Facilities: Active in the University of Adelaide's AgTech ecosystem, she utilizes advanced robotics labs and field stations for experimental work. Her research integrates field robotics, mathematical modeling, and nutritional ecology to address global challenges in sustainable agriculture.

• Behavioral Economics
• Tax Compliance
• Social Psychology
• +۵ مورد دیگر

Benno Torgler is a distinguished Professor at Queensland University of Technology's School of Economics, with an extensive publication record spanning behavioral economics, tax compliance, social psychology, and sports economics. His research bridges theoretical economic principles with practical behavioral insights, making significant contributions to understanding human decision-making in diverse contexts. Dr. Torgler's research interests span behavioral economics, tax compliance, social psychology, and sports economics. His work frequently examines how cognitive biases, social norms, and psychological factors influence economic decisions across various domains. He has developed innovative methodologies for studying human behavior through natural experiments, particularly using sports as a behavioral economics laboratory. His research on tax morale has been particularly influential, examining the psychological and social factors that drive voluntary tax compliance beyond mere enforcement mechanisms. Torgler's publication portfolio demonstrates remarkable breadth and depth, with recent work spanning clinical decision-making, health anxiety, sports economics, AI applications, and tax policy. His research often employs interdisciplinary approaches, combining economics with psychology, sociology, and data science to address complex behavioral questions. The consistent high citation counts across his publications indicate significant scholarly impact in multiple fields. Among his notable scientific contributions are his work on tax morale, behavioral cliometrics, and using sports as a behavioral economics laboratory. His research has been published in top-tier journals including Nature Communications, PNAS, and Scientific Reports, reflecting the high quality and impact of his work. He has received recognition including consideration for the Francis A. Walker Medal. Professor Torgler has mentored numerous researchers who have become established scholars in their own right, particularly in behavioral and experimental economics. His collaborative approach is evident in his extensive co-authorship network, which includes researchers across multiple continents and disciplines. His work has influenced both academic discourse and practical policy applications, particularly in tax compliance and behavioral interventions. Torgler leads a dynamic research team focused on behavioral economics and experimental methodologies. His group employs innovative approaches to studying human behavior, including the use of sports contexts as natural laboratories for economic behavior, analysis of social media data, and experimental designs that bridge laboratory and field settings.

Damien Farineمشاهده پروفایل

استاد

• Social Behaviour
• Collective Behaviour
• Animal Societies
• +۴ مورد دیگر

Damien Farine is an Eccellenza Professor at the University of Zurich, leading the Department of Evolutionary Biology and Environmental Studies. He is affiliated with the Max Planck Institute of Animal Behaviour and the University of Konstanz’s Centre for the Advanced Study of Collective Behaviour. His work focuses on social and collective behavior in animal societies, particularly birds and mammals, emphasizing evolutionary mechanisms and coloniality. Farine holds a Ph.D. from the University of Oxford and has held postdoctoral positions at institutions like the Smithsonian Tropical Research Institute and the University of California Davis. His research explores how group behaviors emerge, evolve, and affect ecological outcomes. He employs interdisciplinary methods, including social network analysis, movement ecology, and computational modeling. Notable contributions include studies on shared decision-making in animal groups, stress transmission in flocks, and the role of collective intelligence in foraging strategies. Farine’s work bridges theoretical and empirical approaches to understand animal societies’ complexity. He leads a research group investigating animal social systems, with projects on vulturine guineafowl, parrots, and dolphins. His studies often involve cutting-edge technologies like drone tracking and machine learning for behavioral analysis. Farine’s research has been published in top journals such as Science , Nature , and Current Biology , reflecting his global impact in behavioral ecology.

Raffaele Vardavasمشاهده پروفایل

استاد

• Infectious Diseases
• Modeling and Simulation
• Health Behaviors
• +۱۶ مورد دیگر

Raffaele Vardavas is a Professor of Policy Analysis at the RAND School of Public Policy and a senior-level mathematician at the RAND Corporation. His work integrates advanced mathematical modeling with public health policy, focusing on infectious disease transmission, socioeconomic systems, and behavioral dynamics. Institution: RAND Corporation School: RAND School of Public Policy Academic Rank: Professor Email: Raffaele_Vardavas@rand.org He holds a Ph.D. and M.Sci. in Physics from Imperial College London and completed postdoctoral training in applied mathematics at UCLA. His research bridges epidemiology, economics, and computational modeling to inform real-world policy decisions. Vardavas specializes in agent-based and population-level models for infectious diseases, with a focus on behavioral adaptation, social networks, and policy evaluation. His work spans influenza, HIV, antimicrobial resistance, and the socioeconomic impacts of pandemics like COVID-19. He has led numerous federally funded projects under NSF and NIH grants and contributed to WHO advisory efforts on integrated epidemiological-economic models. The recent articles reflect a strong trend toward policy-relevant simulation modeling, particularly in pandemic response, health care financing, workforce dynamics, and climate-health interactions. His methodologies emphasize robustness, behavioral realism, and decision support under uncertainty. Scientific Awards and Recognition: Principal Investigator on NSF and NIH (R21, R01) grants Member of WHO Technical Advisory Group on integrated models for COVID-19 Reviewer for NIAID influenza and COVID-19 grant panels Vardavas has led major research initiatives involving grant-funded projects, policy tools (e.g., the COVID-19 Decision Support Tool), and stakeholder-engaged modeling. His work has informed federal and state-level health policies, particularly in pandemic preparedness, insurance reform, and workforce planning. He is affiliated with interdisciplinary teams at RAND that combine behavioral science, economics, and systems modeling. He is actively engaged in developing synthetic data methods, microsimulation models (e.g., LHIEM, COMPARE), and AI-driven approaches to public policy challenges. His lab-like environment at RAND supports large-scale computational modeling and cross-sector collaboration.

Jacek Mazurkiewiczمشاهده پروفایل

پژوهشگر

• Artificial Neural Networks
• Computer Architecture
• Wireless Communication Systems
• +۳ مورد دیگر

Jacek Mazurkiewicz is an academic researcher at Wrocław University of Science and Technology, affiliated with the Faculty of Information and Communication Technology and Department of Computer Engineering . His work spans artificial neural networks, network systems dependability, and transport safety applications. PhD in Computer Engineering Active participation in DepCoS-RELCOMEX conferences Research focuses on: Hardware implementation of neural networks Soft computing for safety improvements Critical situation analysis in network systems Intelligent transport systems development Recent publications highlight his interdisciplinary approach combining AI with transportation safety, creative AI applications in music/art, and dependability engineering. He has contributed to conference proceedings editing and collaborative research projects. Contact: jacek.mazurkiewicz@pwr.edu.pl

Aya Husseinمشاهده پروفایل

مدرس

• Human-swarm Interaction
• Artificial Intelligence
• Human-Computer Interaction
• +۵ مورد دیگر

Aya Hussein is a Lecturer in Artificial Intelligence and Machine Learning at the University of Canberra, specializing in AI and Robotics research within swarm systems and human-autonomy interaction. Her work bridges theoretical AI with practical applications in complex environments requiring human-swarm teaming. Her educational background includes: PhD from UNSW Canberra (Australian Defence Force Academy), awarded 20 January 2021 Dr. Hussein's research centers on human-swarm interaction dynamics, focusing on machine teaching methodologies, autonomy level calibration, and decision-making frameworks for heterogeneous swarms. She pioneers approaches for context-aware control in adversarial scenarios and develops metaverse-based training environments for swarm systems, with significant contributions to swarm interpretability through neural translation techniques and SHAP analysis. Analysis of her 15 most recent publications (2022-2025) reveals dominant themes in swarm intelligence (87%), human-computer interaction (73%), and reinforcement learning (60%). Key trajectories include imitation learning for swarm observation (2023-2025), metaverse integration for multi-level autonomy (2023-2025), and security applications like adversarial patrolling (2024). Her work consistently addresses real-world challenges in search-rescue operations, misinformation resilience, and collective perception systems. Dr. Hussein serves as Co-Investigator on the active ARC-funded project 'Political Misinformation and Media Literacy: Australian Election 2025' (2025), examining misinformation dynamics in electoral contexts. She chairs IEEE Women in Engineering (ACT Section) and organizes the IT & Systems Student Research Conference, demonstrating strong commitment to community engagement and academic service through 12 documented activities including editorial work and peer review. Her research is conducted through the University of Canberra's AI and Robotics group, with significant external collaborations including UNSW Canberra and international institutions. Current projects integrate digital twin technology with swarm metaverse environments to develop next-generation human-swarm teaming frameworks for complex operational scenarios.

Nuno Fachadaمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Modeling and Simulation
• +۴ مورد دیگر

Nuno Fachada is an Assistant Professor at Lusófona University's School of Communication, Arts and Information (ECATI) and a researcher at COPELABS (Cognitive and People-centric Computing). He teaches Programming and AI in the Videogames Bachelor's program and Research Software in the Informatics PhD program, with research spanning Artificial Intelligence, Machine Learning, Modeling and Simulation, High Performance Computing, and Computer Science Education. His work integrates computational methods with applications in game development, wildfire management, and networking. Education: Bachelor's degree in Electrical and Computer Engineering from IST (2005) Master's degree in Electrical and Computer Engineering from IST (2008), focusing on immune system simulation PhD in Electrical and Computer Engineering from IST (2016) with thesis 'Agent-Based Modeling on High Performance Computing Architectures', awarded 'Pass with Distinction and Honour' Research interests emphasize Agent-Based Modeling for complex systems like wildfires and immune responses, Particle Swarm Optimization algorithms, and OpenCL for parallel computing. He develops educational tools for game development curricula and applies AI to environmental monitoring and wireless networks, with strong output in simulation frameworks and human-centric computing. Recent publications (2024-2025) reveal three dominant trends: wildfire modeling using satellite data and agent-based approaches, large language models for engineering code generation (e.g., LoRaWAN), and game AI for procedural content and rehabilitation. His work bridges theoretical computer science with practical applications in environmental science and healthcare, while maintaining focus on education through tools like TextCL and cf4ocl. Scientific Awards: No scientific awards, fellowships, or medals were mentioned in the provided text Advising and Grants: Fachada serves as a researcher in ILIND-funded projects, notably the 'Cybersecurity Awareness Training Simulator' (2024-2025) with six collaborators. He supervises PhD students in Informatics but specific advisees aren't listed. His grant activity primarily involves institutional projects through Lusófona University's research center, with emphasis on simulation-based tools for real-world applications. Labs and Teams: He is a core researcher at COPELABS, focusing on cognitive and people-centric computing projects including wildfire simulation and cybersecurity training. Prior to Lusófona, he conducted postdoctoral work at LaSEEB/ISR (Institute for Systems and Robotics), maintaining connections to IST. His team collaborations span international researchers in environmental modeling and AI, with recent projects involving Portuguese and European institutions.

Andres Karjusمشاهده پروفایل

مدرس

• Evolutionary linguistics
• Cultural analytics
• Digital humanities
• +۶ مورد دیگر

Dr. Andres Karjus is a Lecturer in Digital Humanities and AI at Tallinn University and Senior Research Fellow at Estonian Business School . As member of the CUDAN Cultural Data Analytics Lab , he bridges computational methods with humanistic inquiry through: 15+ years of language evolution research (PhD from University of Edinburgh) Foundational work in computational sociolinguistics and semantic complexity Innovative generative AI applications for cross-sector collaboration Research Themes His work merges machine learning with cultural analytics to study: social media language dynamics, AI's impact on creative industries, film festival networks, and computational approaches to art history. The 2023 fruit-SALAD dataset reveals visual similarity perception in AI models. Scientific Contributions 2024: Polarizing social media analysis in Nature HSSC 2023: Small language challenges in immigration discourse 2021: Aesthetic complexity through compression ensembles Education & Teaching PhD from University of Edinburgh's Centre for Language Evolution , with prior studies at KU Leuven (MSc AI) and University of Tartu (BA/MA Linguistics). Teaches data visualization, R programming, and AI applications for humanities across Estonia and Europe.