جست‌وجوی استاد و پژوهشگر

Yan Zhaoمشاهده پروفایل

دانشیار

• Anomaly Detection
• Autoencoder
• Attention (Machine Learning)
• +۵ مورد دیگر

Yan Zhao is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark, affiliated with The Technical Faculty of IT and Design. His research focuses on data engineering, science, and systems, with a particular emphasis on anomaly detection, machine learning, and spatio-temporal data analysis. He holds a Ph.D. in Computer Science (specific education details not explicitly provided). Research Interests: Dr. Zhao's work spans anomaly detection, autoencoders, attention mechanisms, preference learning, multivariate time series, and computational efficiency. His research often integrates machine learning with real-world applications in spatial crowdsourcing, trajectory analysis, and data privacy. Publications: With 72+ publications, his recent work emphasizes spatio-temporal prediction frameworks, federated learning, and efficient time series analysis. Notable contributions include frameworks for continuous learning on streaming data and privacy-preserving clustering in spatial crowdsourcing. Grants & Supervision: He has supervised one Ph.D. student and actively contributes to research grants focusing on data engineering and smart systems. His work bridges theoretical advancements with practical applications in transportation, social networks, and IoT.

Trevor Cickovskiمشاهده پروفایل

استادیار

• Bioinformatics
• Microbiome Analysis
• GPU Computing
• +۶ مورد دیگر

Trevor Cickovski is an Assistant Professor at Florida International University's Knight Foundation School of Computing and Information Sciences, with a focus on bioinformatics and computational biology. Holding Graduate Faculty status, he specializes in microbiome analysis, GPU computing, network analysis, and Unix systems. His academic journey began with a Ph.D. in Computer Science and Engineering from the University of Notre Dame (2008). Current roles: Associate Director, Assistant Teaching Professor Research affiliations: Bioinformatics Research Group (BioRG), ACM, IEEE Dr. Cickovski's research spans microbiome analysis, software engineering, and GPU-accelerated computing. His work explores the microbiome's role in neuropsychiatric disorders (ADHD), genetic conditions (A1AD), respiratory diseases (COPD), and environmental phenomena (red tides) through multi-omics integration. His publications in Journal of Medical Microbiology , Bioinformatics , and IEEE/ACM TCBB reflect strengths in plugin-based software frameworks (PluMA), network analysis, and computational pipeline optimization. Awards include multiple teaching excellence honors and industry funding from NVIDIA. 2020 Graduate Faculty Status 2019 FIU CAT Fellow 2019 FIU Faculty Teaching Award 2017 Teaching Excellence Award 2014 Promotion to Associate Professor As lead developer of PluMA, he enables cross-language plugin development for bioinformatics workflows. Funded by NIJ and NSF, his projects apply machine learning to epigenetics and computational approaches to vaccine discovery.

Stewart Weissمشاهده پروفایل

دانشیار

• Software Quality Assurance
• Computer Science Education
• Computational Biophysics
• +۳ مورد دیگر

Stewart Weiss is an Associate Professor in the Department of Computer Science at Hunter College, part of the City University of New York (CUNY). His research focuses on Software Quality Assurance, computational biophysics, and integrating open-source software into computer science education. He holds a PhD in Computer Science from New York University's Courant Institute (1987), an M.S. from the same institute (1984), and a B.A. in Mathematics from Hunter College (1982), alongside a B.Arch. from The Cooper Union (1973). Dr. Weiss teaches courses such as Software Design and Analysis, Computer Theory, and UNIX Tools. His work spans grants from NSF and PSC-CUNY, including research in protein structure prediction via the kernel energy method and educational initiatives like 'Computing for Social Good.' He has advised on projects like the 'Gateway for Open Source Software Development' in curricula and contributed to tools for adaptive contrast sensitivity testing. His teaching philosophy emphasizes rigorous academic standards and hands-on learning. He has developed extensive resources, including tutorials on UNIX, parallel programming, and C/C++ programming. His research has explored topics ranging from mutation testing frameworks to quantum chemistry applications in molecular modeling.

Jae Mo Parkمشاهده پروفایل

دانشیار

• Metabolic Imaging
• Magnetic Resonance Imaging (MRI)
• Mitochondrial Metabolism
• +۹ مورد دیگر

Jae Mo Park is an Associate Professor at UT Southwestern Medical Center, affiliated with the Graduate School of Biomedical Sciences and the Department of Biomedical Engineering. He also holds appointments in Electrical Engineering at UT Dallas, where he teaches courses such as Digital Image Processing and Signals and Systems. Education : Electrical Engineering degrees (undergraduate and graduate) from Stanford University; doctoral research on MRI/MRSI for glioma brain tumor metabolism. His lab develops hyperpolarized MRI/MRS methods to assess in vivo metabolic fluxes, focusing on mitochondrial function in diseases like cancer, diabetes, and traumatic brain injury. Research integrates MR pulse sequence design, physiology, and clinical translation. Recent publications highlight hyperpolarized 13C/15N probes for metabolic imaging of the liver, brain, and heart, with applications in fatty liver disease, TBI, and exercise physiology. Awards and grants are not explicitly mentioned, but his work includes collaborations across institutions. Dr. Park teaches courses in neuroimaging, molecular imaging, and metabolic imaging at UT Southwestern and advanced image processing at UT Dallas. The Park Lab investigates metabolic disease characteristics and clinical translation of imaging techniques, with open positions for graduate researchers.

Jazmina Gonzalez Cruzمشاهده پروفایل

پژوهشگر ارشد

• Cancer Immunology
• Vaccine Development
• Immunotherapy
• +۳ مورد دیگر

Dr. Jazmina Gonzalez Cruz is a Senior Research Fellow at the Frazer Institute, University of Queensland, leading the Cancer Immunology and Therapy group. Her research focuses on immunotherapies for virally associated cancers and skin carcinomas, utilizing high-throughput technologies like 10X Genomics and Nanostring DSP. She holds a PhD in Molecular Biology with honors from the National Centre of Biotechnology, Spain, and received postdoctoral training at Heinrich Pette-Institute, Germany. Her work explores T-cell regulation, cytokine immunocomplexes, and tumor microenvironment modulation. Current projects include spatial-omics profiling of head and neck cancers to develop personalized therapies. She collaborates internationally with institutions like Monash University and Technical University of Denmark. Honors and Awards: Garnet Passe & Rodney Williams Memorial Foundation Grant (2019-2023) UQ Postdoctoral Fellowship (2016) Bayer-Humboldt Foundation Fellowship (2013) EEE Department Ph.D. Scholarship

• Process Systems Engineering
• Sustainable Chemical Processes
• Environmental Engineering
• +۴ مورد دیگر

Professor Benoit Chachuat is a Professor of Process Systems Engineering in the Department of Chemical Engineering at Imperial College London, UK. He holds affiliations with the Centre for Process Systems Engineering, Industrial Biotechnology Hub, Institute for Molecular Science and Engineering, and Robotics Forum. His research focuses on developing computational methods for sustainable chemical and biological processes, integrating rigorous modeling, optimization, and data analysis to improve industrial processes. Key areas include process optimization, enviro-economic assessments, and advanced control strategies for bioreactors and energy systems. Prof. Chachuat's career includes roles as Senior Lecturer (2010–2015), Reader (2015–2020), and current Professorship (since 2020) at Imperial College. Prior to this, he held positions at McMaster University (2008–2010), EPFL (2005–2008), MIT (2003–2005), and INRIA (2002–2003). His educational background includes a Research and Teaching Assistantship at Lorraine Institute of Technology (1998–2002). His research interests span computational methods for process systems engineering, with emphasis on global optimization, robust control, and Bayesian estimation. Notable projects include enviro-economic assessments of bioenergy, waste-to-X technologies, and sustainable aviation fuels. His work bridges theoretical advancements with practical industrial applications, supported by software tools for method dissemination. Publications highlight contributions to modeling microalgae cultures, membrane contactors in natural gas processing, and vaccination campaign optimization. His enviro-economic analyses address carbon footprints and externalities in chemical processes, aiming for net-zero solutions. Current projects explore machine learning integration in industrial processes and resilience in biopharmaceutical supply chains. Prof. Chachuat collaborates with experimentalists and industry partners, addressing challenges in energy sustainability, circular economy, and pandemic response. His methodologies prioritize safety, economic viability, and environmental stewardship across chemical and biological systems.

• Glycosaminoglycan Dynamics
• Enzyme Engineering
• Computational Biochemistry
• +۳ مورد دیگر

Andrew Almond is a Reader (equivalent to Associate Professor) in Computational and Theoretical Chemistry at the University of Manchester's Faculty of Science and Engineering. He holds a BSc in Physics from Edinburgh and PhD in Biochemistry from Manchester. His research integrates computational and experimental approaches to study glycosaminoglycan dynamics, enzyme engineering, and molecular interactions in biological systems. His work focuses on developing multiscale models of sugar polymers, accelerating directed evolution in synthetic biology, and advancing NMR techniques for dynamic molecules. Current projects include heparanase inhibition strategies and molecular dynamics of extracellular matrices. Publications showcase methodological innovations in glycosaminoglycan characterization, enzyme design, and spectroscopic analysis, with applications spanning drug delivery, biotechnology, and molecular medicine.

Bruno Correiaمشاهده پروفایل

دانشیار

• Protein engineering
• Computational design
• Immunoengineering
• +۷ مورد دیگر

Bruno Correia is an Associate Professor at the Laboratory of Protein Design & Immunoengineering (LPDI) within the Institute of Bioengineering at École Polytechnique Fédérale de Lausanne (EPFL) , Switzerland. His work bridges computational protein design with experimental validation, focusing on immunoengineering applications for vaccines and cancer immunotherapy. PhD in Computational Biology (Universidade Nova de Lisboa, 2010) BSc in Chemistry (Universidade de Coimbra, 2004) Correia's research spans protein engineering , synthetic biology , and computational design , with key contributions in: Developing MaSIF for protein surface interaction analysis Designing chemically-controlled protein switches for CAR T-cell therapy Creating de novo functional proteins for vaccine development His publications highlight vaccinology , structural bioinformatics , and machine learning applications in protein science. Awards include the Protein Society Young Investigator Award (2021) and ERC Starting Grant (2016) . Scientific contributions: Protein surface fingerprinting for interaction prediction Rational immunogen design for HIV and hepatitis C Deep learning frameworks for protein structure generation

Tom Brownمشاهده پروفایل

استاد

• Nucleic Acid Chemistry
• CRISPR Technology
• Diagnostic Technologies
• +۵ مورد دیگر

Tom Brown is a Professor of Nucleic Acid Chemistry at the University of Oxford's Department of Chemistry. His research focuses on designing and synthesizing chemically modified DNA and RNA for diagnostic and therapeutic applications, including CRISPR systems for genome editing. He has developed Scorpion primers and HyBeacons, used in personalized medicine and rapid forensic analysis. His work has led to the creation of biotech companies like ATDBio and Primer Design, contributing significantly to COVID-19 diagnostics. Research Interests: Brown's group explores nucleic acid modifications, DNA structure-function relationships, and the application of click chemistry for gene assembly. They use techniques like X-ray crystallography and NMR to study DNA interactions with repair enzymes and mutagenic lesions. Key Contributions: Contributions include rapid mutation identification methods, oligonucleotide delivery platforms, and spherical nucleic acids for stem cell isolation. His work bridges chemistry and medicine, with applications in diagnostics, therapeutics, and biotechnology. Awards: While no specific awards are listed, his impactful research has driven industry collaboration and innovation in nucleic acid-based technologies. Labs/Teams: Leads the Nucleic Acids Research Group and the Brown Group, focusing on interdisciplinary projects in chemistry, biology, and medicine.

Fernanda Duarte Gonzalezمشاهده پروفایل

دانشیار

• Computational Chemistry
• Reaction Mechanisms
• Biomimetic Catalysts
• +۳ مورد دیگر

Fernanda Duarte Gonzalez is an Associate Professor of Computational Organic Chemistry at the University of Oxford's Department of Chemistry. She is affiliated with Hertford College and leads the Duarte Research Group, focusing on computational methodologies in chemistry. Her research integrates physical organic chemistry, supramolecular chemistry, and computational approaches to address complex chemical mechanisms and catalysis. Her research interests include Computational Chemistry, Reaction Mechanisms, Biomimetic Catalysts, Physical Organic Chemistry, and Enzyme Catalysis. She employs advanced techniques such as ab initio quantum mechanics (QM), Density Functional Theory (DFT), Molecular Dynamics (MD), and Machine Learning to explore reaction mechanisms, design catalysts, and model supramolecular systems. Key areas of focus are the elucidation of reaction pathways in biosynthetic processes, development of automated computational tools like autodE, and the study of enzyme catalysis mechanisms, including work on the SARS-CoV-2 main protease (MPro). Her research output spans over a decade, with notable contributions in computational chemistry methodologies, supramolecular catalysis, and enzyme mechanisms. Recent work emphasizes the development of machine learning models for reaction prediction, the application of reactive ML potentials in condensed-phase systems, and the design of biomimetic catalysts. Her team's computational frameworks, such as autodE and cgbind, have advanced automated mechanism elucidation and supramolecular assembly characterization. As the leader of the Duarte Research Group, she oversees collaborative projects and experimental collaborations, particularly in enzyme catalysis and supramolecular chemistry. While specific grants are not detailed here, her work is supported through institutional and collaborative funding mechanisms. Her research is conducted through the Duarte Research Group at the University of Oxford, with computational facilities and experimental collaborations enabling her interdisciplinary approach.

Andrew Goodwinمشاهده پروفایل

استاد

• Materials Chemistry
• Correlated Disorder
• Structural Flexibility
• +۷ مورد دیگر

Andrew Goodwin is a Professor of Materials Chemistry and Associate Head of Department (Research) at the University of Oxford, leading a research group focused on structural flexibility and disorder in functional materials. His work bridges fundamental understanding with practical applications in energy storage and smart materials. Education: University of Sydney, University of Cambridge Research in the Goodwin Group revolves around four themes: fundamentals of disorder, advanced characterization techniques, disorder-by-design synthesis, and disorder-property relationships. They specialize in total scattering, PDF, and 3D-ΔPDF methods using X-rays, neutrons, and electrons, with applications in thermoelectrics, magnetocalorics, and adaptive sensing. Recent publications highlight his group's exploration of metal-organic frameworks (MOFs), Jahn-Teller distortions, and disorder-driven properties. Key trends include leveraging correlated disorder for functional materials, developing novel characterization algorithms, and synthesizing hybrid frameworks with unconventional magnetic/electronic states. Royal Society of Chemistry Harrison-Meldola Prize RSC Marlow Prize RSC Corday-Morgan Prize RSC Peter Day Prize Inaugural UK Blavatnik Laureate in Chemistry Andrew has secured both ERC Starting and Advanced Grants, advising roles at the Leverhulme Trust and Max-Planck-Gesellschaft. His group at the Inorganic Chemistry Laboratory collaborates globally on materials synthesis and characterization challenges.

• Quantum Computing
• Quantum Algorithms
• Quantum Simulation
• +۳ مورد دیگر

Professor Jingbo Wang is a faculty member at The University of Western Australia (UWA), serving as Head of the Physics Department and Director of QUISA (Research Hub for Quantum Information, Simulation, and Algorithms). She leads research in quantum walks, quantum simulation, and quantum algorithms. Her affiliations include the Australian Institute of Physics (Chair of WA Branch) and the ARC College of Experts. She holds a PhD from the University of Adelaide. Education: PhD in Physics and Mathematical Physics from the University of Adelaide. Previous affiliations include Murdoch University and UWA. Research focuses on quantum walks, quantum algorithms for optimization, machine learning, and network analysis. Key contributions include quantum compilers, efficient quantum circuits, and applications in complex systems. Her work bridges theory and experimental implementation, with collaborations in photonic quantum processors and quantum machine learning. Recent articles explore quantum computing applications in finance, biology, and physics. Awards include the Vice-Chancellor’s Research Mentorship Award (2022) and Australian Institute of Physics Fellowship (2021). Advising and grants involve leadership in quantum computing initiatives, including the UWA-Pawsey Educational Quantum Computing Centre. Her team develops algorithms for real-world problems like portfolio optimization and metabolic pathway analysis. She co-authored books on computational quantum mechanics and quantum walks. Labs/teams: QUISA Research Hub, UPQCC, and collaborations with institutions like CSIRO and Pawsey Supercomputing Centre.

• Atmospheric Science
• Climate Engineering
• Thermodynamics
• +۳ مورد دیگر

Ali Afzalifar is a Postdoctoral Researcher at Aalto University's Department of Applied Physics, affiliated with the Soft Matter and Wetting group. His research focuses on nucleation theory, atmospheric processes, and engineering applications of supercritical fluids. He holds a Doctoral degree in Engineering and Technology from LUT University (2017). Key research interests include cloud seeding strategies for precipitation enhancement, sensitivity analysis of atmospheric models, and thermodynamic modeling of water clusters. His work bridges fundamental physics with applied engineering, particularly in compressor design for supercritical CO2 systems and real-gas modeling challenges. He led the Academy of Finland-funded project Electric Field; an Active Method to Control Phase Change (2019–2022), exploring nucleation and phase transitions. Collaborations involve institutions like UCLALES-SALSA for cloud modeling. Recent contributions include advancing classical nucleation theory and quantifying cloud seeding efficacy in stratocumulus systems. Publications span atmospheric science, thermodynamics, and engineering, with notable work on Gibbs free energy in water clusters and hygroscopic aerosol effects. His interdisciplinary approach addresses challenges in climate engineering, energy systems, and fluid dynamics.

Gad Landauمشاهده پروفایل

استاد پژوهشی

• Algorithms
• Computational Biology
• String Matching
• +۲ مورد دیگر

Dr. Gad Landau is a Research Professor at the University of Haifa's Department of Computer Science. His work specializes in algorithms, computational biology, and string processing. He has developed foundational methods for sequence alignment, RNA structure comparison, and parallel computing. Landau's research addresses challenges in genomics, text indexing, and bioinformatics optimization. His contributions include efficient algorithms for suffix-prefix problems and unrestricted cost matrix alignment, widely applied in genome sequencing. He collaborates internationally and has served as a professor at NYU Tandon. His lab focuses on theoretical computer science with biological applications, including RNA folding and DNA sequence analysis.

Tina Dürenمشاهده پروفایل

استاد

• Molecular Simulation
• Metal-Organic Frameworks
• Adsorption Science
• +۲ مورد دیگر

Tina Düren is Professor and Head of Chemical Engineering at University of Bath, directing the Centre for Integrated Materials, Processes & Structures. Her research develops molecular simulation methods to design porous materials for carbon capture, hydrogen purification, drug delivery, and catalysis. Research integrates computational modeling with experimental validation to predict adsorption properties and diffusion behavior in metal-organic frameworks, zeolites, and mesoporous oxides. Current projects examine adsorption-induced flexibility, open metal site engineering, and process-scale integration of porous materials. Key investigations include controlled release of bioactive molecules (NO), solvent activation pathways, and dynamic responses in MOFs. Funded by EPSRC and Leverhulme Trust, her work advances sustainable separation technologies through atomistic modeling.