جستجوی استاد راهنمای دانشگاهی

David Graingerمشاهده پروفایل

استاد

• Bacterial Chromosome Biology
• Pathogenicity
• Antibiotic Resistance Mechanisms
• +۳ مورد دیگر

Professor David Grainger is a faculty member at the University of Birmingham's School of Biosciences, specializing in Molecular Microbiology. He leads the Grainger Lab, focusing on bacterial chromosome biology, pathogenicity, and antibiotic resistance. His research integrates high-throughput techniques and single-molecule analysis to study gene regulation and bacterial pathogenesis. Education: PhD (2004), PGCE (2000), BSc (1999) in Biochemistry from the University of Birmingham. Affiliations: Part of the Institute of Microbiology and Infection (IMI), collaborating with experts in genomics, proteomics, and structural biology. Research Interests: Deciphering chromosome biology of pathogenic bacteria, including transcriptional regulation, toxin production control, and antibiotic resistance pathways. Utilizes cutting-edge methods like Hi-C for 3D chromatin analysis and single-molecule microscopy. Recent Articles: Focused on transposon capture mechanisms, bacterial promoter diversity, and quorum sensing signaling. Highlights include studies on Salmonella regulons and Vibrio cholerae biofilm suppression. Awards: Wellcome Trust Career Development Fellowship (2008), Runner-up in 'Science Snaps' competition for scientific communication. Grants: Career Development Fellowship-funded establishment of his research group at the University of Warwick (2008). Labs/Teams: Grainger Lab at the University of Birmingham, part of the IMI network. Engages in public science outreach via Twitter and lab website.

Farhad Pourkamali Anarakiمشاهده پروفایل

استادیار

• Machine Learning
• Data Science
• Computational Mathematics
• +۳ مورد دیگر

Farhad Pourkamali Anaraki is an Assistant Professor in the Department of Mathematical and Statistical Sciences at the University of Colorado Denver, part of the College of Liberal Arts and Sciences. His research focuses on Machine Learning, Data Science, and Computational Mathematics, with interdisciplinary applications in engineering, materials science, and uncertainty quantification. He specializes in developing data-driven methodologies for complex systems, including composite materials, seismic response prediction, and additive manufacturing. Key research themes include probabilistic neural networks, adaptive machine learning for sparse data, and computational techniques for engineering challenges. His work integrates advanced algorithms with domain-specific problems, such as optimizing material properties and enhancing predictive models in civil and mechanical engineering contexts. Despite his prolific publication record, no specific scientific awards or grants are explicitly listed in the provided information. He maintains an active profile in teaching and mentoring, though formal advisee details are not documented here.

• Numerical Modeling
• Computational Simulation
• Materials Science
• +۵ مورد دیگر

Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.

• Neural circuit mechanisms
• Adaptive learning
• State-dependent decision-making
• +۴ مورد دیگر

Dr. Sabine Krabbe is a Group Leader at the German Center for Neurodegenerative Diseases (DZNE) in Bonn, Germany, where she leads research on neural circuit mechanisms underlying adaptive learning and state-dependent decision-making. Her work integrates neuroscience, molecular biology, and behavioral approaches to understand how internal states influence behavior and how these processes are disrupted in neurological disorders. Dr. Krabbe's research focuses on the interactions between midbrain circuits of the substantia nigra and ventral tegmental area with their output structures such as the striatum and amygdala. She investigates how these networks integrate internal states with environmental cues to produce appropriate behavioral responses. Her laboratory employs state-of-the-art techniques including deep-brain calcium imaging at single-cell resolution in mice, opto- and pharmacogenetic manipulations, anatomical tracings, and molecular approaches to characterize neural circuit elements in detail. Her recent publications reveal significant insights into amygdala interneuron plasticity during fear learning, brain-wide representational drift in memory consolidation, and the molecular mechanisms underlying Parkinson's disease progression. Her work demonstrates how activity patterns within specific neural circuits change in early stages of neurodegenerative diseases and how this dysfunction contributes to cognitive deficits and emotional disturbances. Dr. Krabbe is actively involved in the neuroscience community, organizing the BonnBrain Conference 2026 and sharing research through social media platforms. She has established herself as an emerging leader in the field of systems neuroscience with a particular focus on the neural basis of emotional states and decision-making processes.

• Anthropological Genomics
• Paleogenomics
• Human Body Size Evolution
• +۷ مورد دیگر

George Perry is a Professor of Anthropology at Pennsylvania State University, with research intersections in Biology, Evolutionary Medicine, and Genomics. He is affiliated with the Huck Institutes' Center for Infectious Disease Dynamics, Ecology, Molecular Cellular and Integrative Biosciences, and Bioinformatics and Genomics programs. Perry directs the Anthropological Genomics Lab , focusing on paleogenomics and evolutionary adaptation. Research areas: anthropological genomics, parasite evolution, human body size transitions, and evolutionary medicine Key collaborations: international teams in Madagascar, Europe, and Africa Leadership: Bioinformatics and Genomics Chair (2019–2023) His 2025–2022 publications span evolutionary responses to invasive species, human migration health impacts, chemosensory gene adaptation, and primate genomic diversity. Notable methodological contributions include ancient DNA recovery and comparative paleogenomics. Perry advises graduate students like Vanessa Garcia and Annette Mercedes, with grants including NIH support for Cuban health disparity studies. Scientific leadership includes tenure-line promotions (2023) and NASA Space Grant collaborations.

Peter A. Jonesمشاهده پروفایل

استاد

• Epigenetics
• DNA methylation
• Cancer epigenetics
• +۷ مورد دیگر

Peter A. Jones is President and Chief Scientific Officer at the Van Andel Institute (VAI) in Grand Rapids, Michigan, where he leads the Department of Epigenetics. He previously served as Director of the USC Norris Comprehensive Cancer Center from 1993 to 2011 and has been a central figure in advancing epigenetics research, particularly in cancer. His laboratory investigates DNA methylation, chromatin dynamics, and epigenetic therapies. Research Interests: Dr. Jones's work centers on epigenetic mechanisms in cancer, including DNA methylation, histone modifications, nucleosome positioning, and the therapeutic potential of epigenetic drugs. His research has pioneered the use of DNA methylation inhibitors like 5-azacytidine and explored viral mimicry as a mechanism for immune activation in cancer. He also studies transposable elements and their role in gene regulation and immune response. Publication Trends: His recent publications (2021–2024) reveal a strong focus on the interplay between epigenetics and immunotherapy, particularly how DNA methyltransferase inhibitors (DNMTi) induce viral mimicry, enhance immune recognition, and improve responses to checkpoint blockade. Studies span hematological malignancies, solid tumors, and T cell biology, with frequent collaboration with Stephen Baylin and others. Scientific Awards: Member, National Academy of Sciences Member, National Academy of Medicine Fellow, AACR Academy Fellow, AAAS Fellow, American Academy of Arts and Sciences Kirk A. Landon Award for Basic Cancer Research (2009) Medal of Honor, American Cancer Society (2011) Outstanding Investigator Grant, NCI Harvey Prize (2024) Advising and Grants: Dr. Jones mentors multiple postdoctoral fellows, graduate students, and research scientists. His lab is supported by major grants, including the VAI-SU2C Epigenetics Dream Team, which has launched 15 clinical trials. He has received sustained funding from the National Cancer Institute and collaborates with institutions worldwide to advance epigenetic therapies. Labs and Teams: He leads the Peter Jones Laboratory at VAI, a multidisciplinary team investigating epigenetic regulation in cancer. The lab includes computational biologists, clinical researchers, and molecular biologists, working on both basic mechanisms and translational applications. The team is part of larger collaborative initiatives such as the VAI-SU2C Epigenetics Dream Team and the International Linked Clinical Trials Program.

Konstantinos Karapiperisمشاهده پروفایل

استادیار

• Solid Mechanics
• Multiscale Modeling
• Data Science
• +۷ مورد دیگر

Konstantinos Karapiperis is a Tenure Track Assistant Professor at EPFL's Laboratory of Multiscale Modeling of Materials (LMD), within the School of Architecture, Civil and Environmental Engineering (ENAC). His research integrates mechanics , multiscale modeling , and data science to study geomaterials and structural materials. PhD in Applied Mechanics (minor in Applied Mathematics), Caltech Postdoctoral Researcher & Lecturer, ETH Zürich (Marie Skłodowska-Curie Fellowship) Research focuses on granular materials , architected materials , and nonlocal modeling using techniques like Level-Set Discrete Element Method (LS-DEM) and machine learning . Recent work explores fracture control via graph neural networks and thermodynamics-informed models. Selected scientific award: Marie Skłodowska-Curie Fellowship Teaches courses in Soil Mechanics and Multiscale Modeling . PhD students include Thomas Henzel and Hrishikesh Gopakumar Menon. His Data-Driven Mechanics Laboratory (LMD) develops predictive tools for granular and structured material behavior.

Maarten Hornikxمشاهده پروفایل

استاد

• Building Acoustics
• Computational Sound Propagation Modeling
• Mixed Reality Sound Reproduction
• +۴ مورد دیگر

Maarten Hornikx is a Full Professor in Building Acoustics at the Department of the Built Environment , Eindhoven University of Technology. He serves as Vice-Dean of the department, leads the Building Acoustics Chair of Unit Building Physics and Services (BPS), and coordinates the Science of Sound and Music course series since 2013. His research focuses on computational modeling of sound propagation in built environments, with applications in mixed reality platforms and numerical analysis of outdoor/indoor propagation effects like vegetation and meteorological influences. Education : PhD in Applied Acoustics (Chalmers University of Technology, 2009); MSc in Architecture, Building and Planning (2004) Hornikx promotes open research software in acoustics and has received multiple grants, including Marie Curie Individual and Career Integration Grants. His recent publications explore AI-driven diffusion equation modeling, acoustic absorber optimization, and advanced numerical methods like the discontinuous Galerkin technique. He has held international leadership roles, including chairing the Computational Acoustics Technical Committee of the European Acoustics Association and serving as Associate Editor for Acta Acustica . Scientific Awards : Marie Curie Fellowship (2009-2011); Marie Curie Career Integration Grant (2012); 4TU.Built Environment Center Scientific Director (2020-2021); eScience Center Fellow (2022) As a research leader, Hornikx guided the H2020-ITN Acoutect project and conducted sabbaticals at Aalto University, Stockholm University (2018), and Politecnico Torino (2022). His group emphasizes computational acoustics and open-source tools to enhance reproducibility and collaboration.

• Multidisciplinary design optimization
• Topology optimization
• Aeroelasticity
• +۳ مورد دیگر

Kai A. James is an Associate Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign (UIUC), with affiliations in Computational Science and Engineering. He holds a Ph.D. (2012) and M.A.Sc. (2006) from University of Toronto, and B.A.Sc. (2004) in Engineering Science. His research focuses on multidisciplinary design optimization, topology optimization, aeroelasticity, and nonlinear mechanics, with applications to aerospace structures, additive manufacturing, and smart materials. He teaches courses such as Structural Design Optimization (AE 498), Nonlinear Solid Mechanics (AE 598), and Finite Element Analysis (ME 471). His honors include the NSF CAREER Award (2018), Scott White Aerospace Engineering Fellow (2020), and UIUC Teacher of the Year (2017). His work spans academic publications (over 50 journal/conference articles listed) and innovations in topology optimization frameworks for complex systems. Recent research emphasizes bi-stable structures (e.g., cardiovascular stents, morphing airfoils), thermomechanical design of shape-memory alloys, and spatial packing optimization for engineering systems. His lab, located in Talbot Laboratory, develops computational tools for multiphysics and multiscale design optimization.

Kenan Hazirbabaمشاهده پروفایل

استاد آموزشی

• Geotechnical Engineering
• Soil Stabilization
• Earthquake Engineering
• +۵ مورد دیگر

Kenan Hazirbaba is a Teaching Professor in the Department of Civil Engineering at the University of Texas at Tyler. With extensive teaching experience, he specializes in geotechnical engineering and offers courses in statics, mechanics of materials, soil mechanics, foundation design, and seismic site response. Ph.D. in Civil, Architectural, and Environmental Engineering from The University of Texas at Austin (2005) M.S. in Civil Engineering from Bogazici University (1999) B.S. in Civil Engineering (with distinction) from Istanbul Technical University (1996) Hazirbaba's research focuses on applied and experimental geotechnical engineering, particularly the behavior of saturated soils under cyclic loading and non-traditional soil stabilization techniques. His work addresses critical challenges in cold regions, including freeze-thaw effects on soil mechanics and seismic response in permafrost areas. His publications highlight expertise in geofiber-reinforced sands, synthetic fluid stabilization, and seismic design of earth-retaining structures. Research has secured over $2 million in funding from state and non-governmental agencies, emphasizing practical solutions for civil engineers. Hazirbaba is a Registered Professional Engineer in Alaska and promotes undergraduate research engagement. His certifications and applied research bridge academic theory with real-world engineering applications.

• Geotechnical Engineering
• Offshore Engineering
• Civil Engineering
• +۷ مورد دیگر

Amin Barari is an Adjunct Professor at the School of Engineering, RMIT University, Australia. His research focuses on geotechnical and offshore engineering, particularly in foundation systems for offshore wind turbines, soil-structure interaction, and seismic liquefaction mitigation. He has extensive experience in experimental and numerical analysis of pile foundations, bucket foundations, and caisson structures. His work integrates advanced computational methods (e.g., machine learning, finite element modeling) to predict foundation behavior under extreme conditions. Research interests include: offshore wind energy foundations, soil liquefaction, cyclic stability diagrams, and probabilistic hazard assessment frameworks. He has supervised multiple PhD/Masters projects on topics like resilient foundations in calcareous deposits and pile foundation dynamics in expansive soils. His publications span over 147 research outputs, emphasizing geotechnical challenges in coastal and offshore environments. Dr. Barari collaborates with international institutions and has expertise in experimental testing (e.g., large-scale load testing, centrifuge modeling) and advanced AI-driven frameworks for geohazard prediction. His work contributes to sustainable infrastructure design and risk mitigation strategies for renewable energy systems.

Lucia Leeمشاهده پروفایل

استادیار

• Chemical Sciences
• Analytical Chemistry
• Quantum Chemistry
• +۹ مورد دیگر

Lucia Lee is an Assistant Professor in the Department of Chemistry at Queen's University, affiliated with the Faculty of Arts and Science. Her research focuses on applying green chemistry principles to supramolecular interactions involving main-group elements, particularly sigma-hole interactions, with applications in materials science and medicine. She holds a PhD from McMaster University and has completed postdoctoral studies at the University of Geneva and Weizmann Institute of Science. Dr. Lee's educational background includes a PhD supported by an NSERC grant, which explored chalcogen bonding in supramolecular materials. Her postdoctoral work at Weizmann focuses on stimuli-responsive materials using chalcogen elements for photoswitching applications. She has also contributed to academic governance through roles in the McMaster Graduate Students Association. Her research interests span analytical chemistry, quantum chemistry, inorganic and bioinorganic chemistry, organic chemistry, and free radical chemistry. Key projects include integrating chalcogen bonding into d-metal coordination chemistry, catalysis, and chemical biology to create functional materials. Her lab, located in CHE513, emphasizes sustainable approaches to material design through main-group supramolecular systems. Her articles explore topics like chalcogen bonding mechanisms, anion transport, and photoswitching in confined spaces, reflecting a strong focus on molecular assembly and functional materials. She has no listed scientific awards but demonstrates significant contributions to supramolecular chemistry through her publications and cross-appointments at Queen's Carbon to Metal Coating Institute.

• Solid Mechanics
• Materials Science
• Fracture Mechanics
• +۳ مورد دیگر

Jonas Faleskog is a Professor in the Department of Materials and Structural Mechanics at KTH Royal Institute of Technology. His research focuses on mathematical modeling of material deformation and failure mechanisms, particularly in metallic and polymeric materials. Key areas include ductile and brittle fracture analysis, fracture mechanics, and computational modeling of material behavior under various stress conditions. He leads a research group collaborating internationally to develop models describing material failure at microscopic scales. Faleskog teaches courses such as Fracture Mechanics (SE2139) and Modeling in FEM (SE2860), emphasizing practical applications of theoretical models. His work spans experimental and numerical methods, addressing challenges in material heterogeneity, porosity effects, and environmental degradation. Notable contributions include advancements in weakest-link modeling for brittle failure, probabilistic fracture models, and strain gradient plasticity analysis. His research bridges material science, applied mechanics, and numerical methods to optimize material utilization in engineering systems like reactor tanks, aircraft, and vehicles. Key collaborations involve international teams exploring microstructural influences on fracture behavior. While no specific awards are listed, his extensive publication record reflects sustained contributions to mechanical and materials engineering.

Carl Henrik Ekمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Bayesian Non-parametric Methods
• +۶ مورد دیگر

Carl Henrik Ek is a Professor of Statistical Learning at the Department of Computer Science and Technology (Computer Laboratory) at the University of Cambridge. He is also a fellow and Director of Studies at Pembroke College, and holds visiting positions at Karolinska Institute in Stockholm and the Royal Institute of Technology. He serves as co-Director for the UKRI AI Centre for Doctoral Training in Decision Making for Complex Systems, a collaboration between Cambridge and Manchester universities, and is involved with the Accelerate Program in the Computer Laboratory. Dr. Ek's educational background includes a MEng degree in Vehicle Engineering from the Royal Institute of Technology in Stockholm, followed by a PhD from Oxford Brookes University. During his PhD, he spent time at the University of Manchester and the University of Sheffield. His PhD supervisors were Professor Neil Lawrence and Professor Phil Torr, and his postdoctoral research was conducted at UC Berkeley with Professor Trevor Darrell and Professor Raquel Urtasun. Professor Ek's research focuses on statistical learning, particularly on developing data-efficient and interpretable machine learning methods. His work spans modeling and inference in machine learning, with special emphasis on Bayesian non-parametric methods and Gaussian processes. He explores how to specify assumptions that allow learning from small amounts of data, bridging theoretical foundations with practical applications in various domains. His recent publications demonstrate a strong trend toward applying machine learning to healthcare, drug discovery, and engineering design. There's significant work on Gaussian processes, reinforcement learning, and generative models, with applications ranging from medical diagnostics to structural engineering. His research shows an increasing interdisciplinary focus, connecting machine learning with fields like cardiology, pharmacology, and computational geometry. Professor Ek has received numerous teaching awards throughout his career: Pilkington Price for Teaching Excellence (2024) Teacher of the year in Computer Science at University of Bristol (2016) Docent in Machine Learning at Royal Institute of Technology (2016) Teacher of the year at Royal Institute of Technology, Sweden (2015) Teacher of the year from Student chapter in Industrial Economics at Royal Institute of Technology (2015) Teacher of the year in Computer Science at Royal Institute of Technology (2012) Professor Ek teaches Advanced Data Science, Advanced topics in machine learning, and Machine Learning and the Physical World. He has supervised PhD students throughout his career but is not currently accepting new PhD students for 2025/26 or 2026/27. His research is supported by various grants, including his role as co-Director of the UKRI AI Centre for Doctoral Training. He is an active member of the ml@cl research group at Cambridge and has previously been involved with research groups at University of Bristol and Royal Institute of Technology. His work connects with several interdisciplinary initiatives, particularly in healthcare AI and engineering applications of machine learning.

• Computational Mechanics
• Scaled Boundary Finite-Element Method
• Dynamic Soil-Structure Interaction
• +۵ مورد دیگر

Professor Chongmin Song is a faculty member at the University of New South Wales (UNSW), affiliated with the School of Civil and Environmental Engineering. His academic rank is Professor, and he specializes in computational mechanics with a focus on innovative numerical methods. He holds a BE and ME from Tsinghua University and a DEng from the University of Tokyo. His research explores computational mechanics, fracture analysis, wave propagation, and soil-structure interactions. Key methodologies include the Scaled Boundary Finite Element Method (SBFEM), image-based modeling, and dynamic simulations of infrastructure systems. He leads significant ARC-funded projects like 'A scaled boundary framework for nonlinear dynamic analysis of structures' (DP250100955) and 'Developing sustainable graded porous cementitious structures' (LP240100123), totaling over $1M in recent grants. Recent publications emphasize adaptive modeling techniques, multiphysics simulations, and high-performance computing applications. Trends include topology optimization for structural dynamics, phase-field fracture modeling for brittle materials, and GPU-accelerated elastodynamics. His work integrates computational efficiency with real-world engineering challenges, particularly in geomechanics and material failure analysis. Professor Song collaborates extensively on projects involving computational fracture mechanics and maintains laboratories focused on numerical simulation advancements. Future work targets scalable algorithms for 3D crack propagation and multiphysics coupling in infrastructure systems.