جست‌وجوی استاد و پژوهشگر

• Public Health
• Hepatitis C Virus Epidemiology
• Illicit Drug Use
• +۳ مورد دیگر

Dr. Bethany White is a Clinical Senior Lecturer at the Central Clinical School, University of Sydney. Her expertise lies in public health research, particularly in drug and alcohol use, hepatitis C epidemiology, and health services evaluation. She has led numerous clinical and community-based studies focusing on marginalized populations, including people who inject drugs and imprisoned women. Her work integrates harm reduction policies, healthcare access improvements, and substance use disorder treatments in custodial and community settings. Research Focus: Dr. White's research emphasizes epidemiological methods to address health inequalities, with a focus on opioid use disorders, hepatitis C prevention, and women's substance use. She has pioneered studies on depot buprenorphine treatment efficacy in prisons and developed models of care for substance-using mothers. Her work bridges clinical practice and policy, aiming to improve healthcare accessibility in high-risk groups. Key Themes: Health inequalities, harm reduction, custodial healthcare Recent Projects: Costing models for depot buprenorphine, contraception integration in opioid treatment centers Grants & Collaborations: Principal investigator on a 2025 NHMRC-funded grant exploring clinical evidence translation for substance use disorder outcomes. Collaborates with institutions like Edith Collins Centre and NSW Health. Labs/Teams: Affiliated with the Edith Collins Centre, focusing on addiction medicine and health service innovation.

John Dalsgaard Sørensenمشاهده پروفایل

استاد

• Wind Turbines
• Structural Safety
• Risk Analysis
• +۵ مورد دیگر

John Dalsgaard Sørensen is a Professor and Head of Research Group at the Department of the Built Environment, Aalborg University, within the Faculty of Engineering and Science. He leads the Risk, Resilience, Safety, and Sustainability of Systems Research Group and is affiliated with the Danish Centre for Risk and Safety Management. His research focuses on structural safety, wind turbine reliability, probabilistic design, and risk assessment of infrastructure systems. He has supervised 13 PhD students and contributed to over 600 publications. Key research areas include wind turbine structural integrity, fatigue analysis of offshore and onshore structures, probabilistic design standards (e.g., Eurocodes), and risk-based decision-making for infrastructure. He leads projects like Windscanner (remote sensing for wind measurements) and MANTIS (cyber-physical maintenance systems). Collaborations span academia and industry, addressing challenges in energy systems, civil infrastructure, and safety engineering. His work emphasizes practical applications of advanced modeling techniques, such as Bayesian networks and stochastic simulations, to enhance reliability and reduce operational costs. He is actively involved in standardization efforts for structural design and serves on boards like Energi- og MiljøData Fonden. Recent activities include presenting at international conferences and advising on media debates related to structural safety.

• Tribology
• Materials Science
• Surface Engineering
• +۵ مورد دیگر

Auezhan Amanov is an Associate Professor at the Faculty of Engineering and Natural Sciences, Tampere University, specializing in the Engineering Materials Science (EMS) department. His research focuses on tribology, surface engineering, and advanced materials processing. He leads the 'Tribology and Surface Modification' research group, aiming to enhance machine element performance through surface treatments and manufacturing innovations. Dr. Amanov is an active member of international tribology societies (STLE, JAST, KTS), chairing the 'Surface Engineering' committee at STLE. His work emphasizes improving wear resistance, fatigue life, and tribological performance of materials like titanium alloys, high-entropy alloys, and thermal spray coatings. His research integrates additive manufacturing, laser-based processes, and severe plastic deformation techniques to optimize material properties. Key contributions include studies on ultrasonic nanocrystal surface modification (UNSM) for enhancing mechanical and tribological characteristics. Collaborations with industries and academic institutions globally drive his mission to translate research into practical solutions for manufacturing efficiency and sustainable development. Dr. Amanov holds an h-index of 34 (Google Scholar) and has authored numerous peer-reviewed articles on materials science and tribology advancements. Teaching responsibilities include tribology and fatigue-related courses, reflecting his expertise in both academic and applied engineering domains. His vision includes advancing circular economy practices through bearing restoration technologies and improving 'Made in Finland' manufacturing competitiveness through material science innovations.

Adam Doupéمشاهده پروفایل

دانشیار

• Cybersecurity
• Cybercrime
• Binary Analysis
• +۷ مورد دیگر

Adam Doupé is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence (SCAI) and Director of the Center for Cybersecurity and Trusted Foundations (CTF). He holds a Ph.D. and M.S. in Computer Science from the University of California, Santa Barbara. His research focuses on cybersecurity, vulnerability analysis, web security, and hacking competitions. Notable awards include the NSF CAREER Award (2017), Best Teacher Award, and Outstanding Assistant Professor Award from ASU's Fulton Schools of Engineering. Education: Ph.D. and M.S. in Computer Science, UC Santa Barbara (2014, 2009). Research emphasizes automated vulnerability analysis, binary analysis, and cybersecurity education. Key contributions include frameworks like SCAMNet and SENSAI for fraud detection, and tools like Fuzz to the Future for uncovering future vulnerabilities. Recent articles highlight advancements in phishing ecosystem analysis, browser fingerprinting mitigation, and compiler-aware decompilation. Awards reflect his impact in both teaching and research. Advising and grants support his work in secure systems and ethical hacking. He co-leads the SEFCOM lab with Drs. Ahn, Shoshitaishvili, Wang, and Bao, and hosts CTF Radiooo for cybersecurity discussions.

Apurba Duttaمشاهده پروفایل

دانشیار

• Medicinal Chemistry
• Synthetic Organic Chemistry
• Anti-Infectives
• +۳ مورد دیگر

Apurba Dutta is an Associate Professor and Interim Chair in the Department of Medicinal Chemistry at the University of Kansas School of Pharmacy. His research focuses on asymmetric synthesis of bioactive molecules, development of synthetic methodologies, and natural product-based drug discovery. He holds a Ph.D. in Chemistry from North-Eastern Hill University (1989) and completed postdoctoral research at the University of Kansas (1994) and a Humboldt Fellowship at the University of Konstanz (1992). Research Overview : Dr. Dutta’s work includes total synthesis of antifungal peptidyl nucleosides (e.g., polyoxins, nikkomycins), proteasome inhibitors like salinosporamide A, and cytotoxic marine natural products. He also explores combinatorial libraries of biomimetic compounds (nucleosides, azacarbohydrates) for high-throughput screening. Key Projects : His lab investigates antifungal agents targeting chitin synthase, endotoxin sequestration for septic shock, and proteasome inhibition for cancer therapy. Notable contributions include synthetic routes to Jaspine B and structural studies of polyoxamic acid. Publications : Recent work includes stereoselective iminosugar synthesis (2025), SAR analyses of lipopeptides (2010), and neurochemical studies of enantiomers (2016). Over 100 publications span medicinal chemistry, organic synthesis, and drug discovery. Awards & Recognition : While no specific awards are listed, his contributions to antibiotic design and synthetic methodology reflect sustained excellence in the field. Current Activity : Not currently accepting students/postdoctoral fellows, but actively engaged in grant-funded research projects focused on antifungal agents and combinatorial chemistry.

• Structural Health Monitoring
• Seismic Analysis
• Bayesian Calibration
• +۱۴ مورد دیگر

Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.

Mai Ha Vuمشاهده پروفایل

استادیار

• Theoretical Linguistics
• Computational Linguistics
• Mathematical Linguistics
• +۶ مورد دیگر

Mai Ha Vu is an Assistant Professor at the University of Toronto Mississauga , split between the Department of Language Studies and the Department of Mathematics, Computer Science, and Statistics . Her work bridges theoretical linguistics, computational methods, and biological data modeling. Ph.D. in Linguistics, University of Delaware (2020) M.A. in Linguistics, University of Delaware (2014) B.A. in Psychology and Linguistics, Grinnell College (2013) Research focuses on applying formal language theory to understand human language patterns and train biologically reliable language models . Recent work includes antibody language modeling (Nature Computational Sciences 2022) and syntax-prosody mapping via logical transductions (SIGMORPHON 2022). Key research trends in publications: interdisciplinary applications of computational linguistics to immunology, psycholinguistic modeling of neural language models, and formal syntactic analysis of negation and wh-questions across languages.

Ali Ahrariمشاهده پروفایل

مدرس

• Evolutionary Algorithms
• Multimodal Optimization
• Multi-objective Optimization
• +۵ مورد دیگر

Dr. Ali Ahrari is a Lecturer at the School of Systems and Computing, University of New South Wales, Canberra. He holds a Ph.D. in Mechanical Engineering from Michigan State University (2016) and has extensive experience in research and academia, including roles as a Research Fellow and Associate at UNSW-Canberra and the University of Sydney. His research focuses on evolutionary algorithms, multimodal and multi-objective optimization, and surrogate-assisted optimization. Ahrari is a recipient of prestigious awards, including the ARC-DECRA 2023 and multiple international competition wins in optimization (e.g., CEC/GECCO competitions). He leads research groups like the Canberra Evolutionary Optimization (EvOpt) and serves on editorial boards, including Applied Soft Computing. Education: Ph.D. (2016, Michigan State University), M.Sc. and B.Sc. (University of Tehran). Awards: ARC-DECRA, ISCSO, and GECCO/CEC competition wins. Grants: ARC DECRA (2023), NCI Adapter Schemes, UNSW HPC allocations. Supervision: Currently advising 1 PhD student at SEIT, UNSW-Canberra. Engagements: Chair of IEEE Task Force on Multi-modal Optimization, organizer of optimization competitions (GECCO'2024, CEC'2022). His research emphasizes computational optimization, evolutionary computation, and swarm intelligence, with applications in engineering design and dynamic environments. He actively contributes to academic communities through editorial roles and conference organization.

Sven Heidenreichمشاهده پروفایل

استاد

• Technology and Innovation Management
• Business Model Innovation
• Consumer Integration in Innovation
• +۱۲ مورد دیگر

Prof. Dr. Sven Heidenreich is a full Professor of Business Administration, specializing in Technology and Innovation Management at the University of Saarland. He leads an active research group and holds a prominent position in the German-speaking academic community, with consistent recognition in national and international rankings. University: University of Saarland Department: Business Administration Research Focus: Technology and Innovation Management Email: sven.heidenreich@uni-saarland.de His research centers on innovation processes, particularly consumer integration, co-creation, resistance to innovation, and sustainable business models. He employs a quantitative-empirical approach to study individual and organizational aspects of innovation, with applications in digital services, video games, and green innovation. The recent publications reflect a strong trend in understanding consumer behavior in innovation contexts, including greenwashing, leapfrogging, co-creation, and the role of personality in entrepreneurial success. His work frequently appears in high-impact journals such as Journal of Product Innovation Management , R&D Management , and Technological Forecasting and Social Change . Top 0.5% researcher worldwide in Innovation Management (ScholarGPS 2024) JPIM Outstanding Reviewer Award 2023 Multiple appearances in WirtschaftsWoche Economist Rankings (2018–2024) Finalist, Best Paper Award, IRCSM 2024 Prof. Heidenreich supervises doctoral researchers and has led significant research projects, including the DFG-funded TRIP project on integrating different consumer types into new product development. His team includes postdocs, junior professors, and scientific staff, indicating active mentorship and collaborative research. He also collaborates with researchers across Europe and beyond. He leads the DFG project TRIP and has secured funding from major German research bodies. His lab focuses on empirical studies involving consumer panels, student experiments, and idea competitions to validate innovation theories in realistic settings.

• Cloud Computing
• Green Computing
• High-Performance Computing
• +۷ مورد دیگر

Jordi Guitart Fernández is a Professor at the Department of Computer Architecture, Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading national supercomputing facility. He leads the CROMAI research group, focusing on Computing Resources Orchestration and Management for AI. His work bridges high-performance computing, cloud systems, and artificial intelligence. Research Interests: Cloud Computing and Edge Computing Green and Energy-Efficient Computing Containerization and Virtualization for HPC Resource Orchestration and Management Autonomic and Self-Adaptive Systems Machine Learning Workflow Management AI-Driven System Optimization His recent publications reveal a strong focus on intelligent management of computing resources across cloud, edge, and HPC environments using machine learning and agent-based frameworks. He investigates performance, efficiency, and reliability in containerized AI and HPC workloads, particularly within Kubernetes and distributed infrastructures. His work increasingly integrates human-in-the-loop and trustworthiness aspects into AI systems. Scientific Awards: CLOUD Conference 2025 Best Paper Award VISIGRAPP 2025 Best Student Paper Award Premi Extraordinari de Doctorat 2025 - Àmbit d'Enginyeria de les TIC Test of Time Award Honorable Mention (e-Energy) Reconeixement als Mèrits Docents d'Especial Qualitat Top reviewers for Polytechnic University of Catalonia (Computer Science) - September 2017 Advising and Grants: He has advised doctoral students, including Peini Liu. He leads and participates in numerous competitive R+D+i projects, such as CROMAI and DALEST, funded by national and European programs like HORIZON 2020 and the Spanish State Research Plans. His work is supported by grants focused on knowledge generation and industrial leadership in computing technologies. Labs and Teams: He is the leader of the CROMAI - Computing Resources Orchestration and Management for AI research group at UPC. He also collaborates closely with the Barcelona Supercomputing Center (BSC-CNS), contributing to large-scale computing initiatives and strategic research agendas in Europe.

Sumsun Naherمشاهده پروفایل

مدرس ارشد

• Materials Processing
• Laser Engineering
• Metal Matrix Composites
• +۳ مورد دیگر

Dr. Sumsun Naher is a Senior Lecturer in the Department of Engineering at City, University of London , where she has worked since 2013. Previously, she served as Lecturer and Research Development Officer at Dublin City University (2006–2013) and as Scientific Officer at Bangladesh Council of Scientific & Industrial Research (1998–2000). Her academic career includes a Post Graduate Diploma in Academic Practice from City, University of London. PhD , School of Mechanical & Manufacturing Engineering, Dublin City University MSc , Materials & Metallurgical Engineering, Bangladesh University of Engineering and Technology BSc , Materials & Metallurgical Engineering, Bangladesh University of Engineering and Technology Her research focuses on semi-solid processing , laser processing , simulation & modelling of materials technologies , and materials characterisation . Recent work explores cellulose nanofiber-based water filters for antibiotic removal and phase change materials in geothermal energy systems. Key article trends reveal expertise in: Laser Surface Modification of metals and composites Advanced Casting Methodologies and semi-solid metal forming Nanoparticle Reinforcement in metal matrix composites Thermal Modelling for energy systems Sustainable Material Solutions in water treatment and energy Computational Materials Science via finite element analysis Naher has received the DCU Invent Commercialisation Award (2011) and holds fellowships from IMechE , Institute of Materials, Minerals & Mining , and Advance Higher Education Authority . She actively reviews for funding bodies and examines PhD theses internationally. As an organiser of the ESAFORM Conference and co-organiser of its Additive Manufacturing symposium since 2017, she contributes to academic leadership. Her professional roles include Board of Directors for the European Association of Materials Forming and participation in EU COST Action projects (Thixoforming, Thixosteel, Nanostructured Materials).

Nikolaus Kriegeskorteمشاهده پروفایل

استاد

• Computational Neuroscience
• Artificial Neural Networks
• Visual Perception
• +۳ مورد دیگر

Nikolaus Kriegeskorte is a Professor of Psychology and Neuroscience, and Director of Cognitive Imaging at the Mortimer B. Zuckerman Mind Brain Behavior Institute at Columbia University. He is affiliated with the Departments of Psychology, Neuroscience, and Electrical Engineering. Institution: Columbia University Academic Roles: Professor of Psychology and Neuroscience; Director of Cognitive Imaging Email: nk2765@columbia.edu Location: Jerome L. Greene Science Center, 3227 Broadway, L3-064 Research Focus: The lab explores the cognitive neuroscience of vision, modeling biological visual systems with artificial neural networks. Key areas include developing statistical inference and visualization techniques to bridge theory and experimental data, understanding representational geometry in neural systems, and optimizing deep learning frameworks for neuroscience. Recent Publications: Highlighted work spans neural network modeling of visual perception, representational similarity analysis, and the topology of brain representations. The lab's methods, such as the TorchLens Python package, enable transparent extraction and visualization of hidden layer activations in neural networks. Grants: Projects are supported by funding from the National Science Foundation (NSF) - Cognitive Neuroscience and the National Institutes of Health (NIH) - NIMH. Laboratory: The Visual Inference Lab (kriegeskortelab.zuckermaninstitute.columbia.edu) is located at Quad 3D, Zuckerman Institute, 3227 Broadway.

Katarina Domijanمشاهده پروفایل

دانشیار

• Bayesian applications to data analysis
• Machine learning
• Statistical computing
• +۳ مورد دیگر

Katarina Domijan is an Associate Professor in Statistics at the Department of Mathematics and Statistics, Maynooth University, Ireland. She holds a PhD in Statistics from Trinity College Dublin (2008) and has been affiliated with Maynooth University since 2008, transitioning from Lecturer/Assistant Professor to her current role in 2024. Her academic career includes editorial roles as Associate Editor for The R Journal (2021–present) and the Journal of Computational and Graphical Statistics (2015–2024). Research Interests focus on Bayesian methods for high-dimensional data, particularly in classification problems. She specializes in feature selection and model visualization, with applications spanning agricultural data analysis (e.g., hyperspectral imaging for lactose prediction), medical diagnostics (e.g., sepsis and cancer detection), and space physics (e.g., Saturn Kilometric Radiation classification). Her work bridges theoretical statistics with real-world challenges, including socio-economic studies and forensic science. Key Research Areas Bayesian statistical inference Machine learning for large feature spaces Statistical computing and model interpretability Data visualization and chemometrics Scientific Contributions include leading projects like VistaMilk Phase II (2024–2030, €152,300) and Measuring Carbon Sequestration (2024–2028, €174,788.90). Her 15 most recent publications highlight advancements in ensemble modeling, spatial statistics, and medical diagnostics. Scientific Awards Associate Editor, The R Journal (2021–present) Associate Editor, Journal of Computational and Graphical Statistics (2015–2024) Student Supervision includes PhD and MSc graduates such as Dr. Bruna Wundervald (2024) and Dr. Mark O’Connell (2017). She also collaborates with researchers across disciplines, including Dr. Nadim Akasheh in food hypersensitivity studies.

• Additive Manufacturing
• Laser Powder Bed Fusion
• Materials Science
• +۲ مورد دیگر

Prof. Dr.-Ing. Johannes Henrich Schleifenbaum is a Professor and Chair of Digital Additive Production at RWTH Aachen University, where he leads research in the Profile area Production Engineering (ProdE). His work advances additive manufacturing (AM) through interdisciplinary approaches combining materials science, process engineering, and digital technologies. His research encompasses: Laser powder bed fusion (LPBF) process optimization and defect mitigation Development of novel alloys/composites for AM applications Sustainable manufacturing practices including material recycling Integration of AI/ML for accelerated material and process design Digital tools for automated design and distributed manufacturing Recent publications (2023-2025) demonstrate a strong focus on: Multi-material processing and microstructure control Machine learning-driven alloy development Standardization and scalability of AM processes Advanced simulations for meltpool dynamics and thermal behavior Applications in aerospace, construction, and biochemical engineering He leads the Chair of Digital Additive Production, collaborating with industry partners to translate research into industrial solutions for next-generation manufacturing.

Jun Yeمشاهده پروفایل

استاد پژوهشی

• Atomic Physics
• Molecular Physics
• Optical Physics
• +۴ مورد دیگر

Jun Ye is a Chinese-American physicist affiliated with JILA, the National Institute of Standards and Technology (NIST), and the University of Colorado Boulder. He holds the academic rank of Research Professor and has made groundbreaking contributions to atomic, molecular, and optical (AMO) physics, particularly in precision measurement and quantum control of atomic and molecular systems. Education: BS in Physics (Shanghai Jiao Tong University, 1989), MS in Quantum Optics (University of New Mexico, 1991), PhD in Physics (University of Colorado Boulder, 1997) under Nobel laureate John L. Hall. His research spans ultracold atoms, ultracold molecules, and laser-based precision measurement, including the development of the 3D quantum gas clock with 2.5 × 10⁻¹⁹ frequency precision. He explores applications in gravitational field sensing, dark matter detection, quantum simulations, and fundamental physics tests. Recent work includes thorium nuclear clocks, topological optical lattice clocks, and spin dynamics in ultracold polar molecules. Jun Ye's publications (e.g., 2025 articles) focus on atomic clocks, quantum sensing, and precision metrology, with keywords like quantum physics, atomic physics, and optical engineering. His subfields include frequency combs, spin squeezing, superexchange interactions, and many-body quantum systems. Scientific Awards: Department of Commerce Gold Medal (multiple years), Breakthrough Prize in Fundamental Physics (2022), National Academy of Sciences (2011), Norman F. Ramsey Prize (2019), and numerous fellowships. Patents: Four U.S. patents for frequency combs and laser technology. He leads research at JILA, collaborating with institutions like Caltech and MIT, and has been featured in documentaries such as The Most Unknown (2018). His work bridges experimental physics, quantum information science, and applied photonics.