جستجوی استاد راهنمای دانشگاهی

• Hyperbolic Geometry
• Low-Dimensional Topology
• Teichmüller Theory
• +۴ مورد دیگر

James Reed Farre is a Researcher and Head of the Geometry Research Group at the Max Planck Institute for Mathematics in the Sciences. He holds a PhD in Mathematics from the University of Utah (2019), completed an NSF Postdoctoral Fellowship at Yale University (2019-2021), and served as a Juniorprofessor (W1/Assistant Professor) at Heidelberg University (2022-2023). His academic journey includes postdoctoral positions in Heidelberg’s research group under Beatrice Pozzetti and a Gibbs Assistant Professorship at Yale. Farre’s research focuses on hyperbolic geometry, Teichmüller theory, dynamical systems, and geometric group theory. Key areas include earthquake flows, character varieties, convex projective structures, and bounded cohomology. His work bridges low-dimensional topology with ergodic theory and geometric analysis. Publications (2016–2024) explore topics like affine laminations, hyperconvex representations, and minimal surfaces in hyperbolic 3-manifolds. Recent work addresses Mirzakhani’s twist torus conjecture and Hamiltonian flows for surface group representations. Farre frequently collaborates with leading mathematicians such as Yair Minsky, Beatrice Pozzetti, and Anna Wienhard. He has contributed to algorithmic CAD research and STEM education initiatives, including a chapter in *Directions for Mathematics Research Experience for Undergraduates* (2015). His current role involves leading a research group focused on geometry and dynamics at the Max Planck Institute.

• Combinatorial algebraic geometry
• Computational commutative algebra
• Rigidity theory
• +۳ مورد دیگر

Jessica Sidman holds the Brian E. Boyle Professorship in Mathematics and Computer Science at Amherst College, with adjunct affiliations at University of Massachusetts Amherst. Her research bridges computational algebra, algebraic geometry, combinatorics, and applications in rigidity theory. She explores geometric problems through polynomial systems, with applications in computer-aided design, architecture, and robotics. Teaching spans foundational courses from calculus to abstract algebra, alongside electives like computational algebraic geometry. Education : Ph.D. University of Michigan (2002) M.S. University of Michigan (1999) B.A. Scripps College (1997) Research Trends : Focuses on nonlinear polynomial systems in geometric problems, with recent work connecting rigidity theory to robotics formations and architectural design. Her computational methods address real-world applications while advancing theoretical frameworks in algebraic geometry. Awards : Recognized with the AWM Distinguished Speaker honor (2022) and Merten M. Hasse Prize (2021), alongside NSF grants and teaching awards including the Meribeth E. Cameron Faculty Award (2012). Advising & Grants : Active mentor with NSF funding history. Currently on research leave 2024-2025.

• Computational stochastic mechanics
• Machine learning in engineering
• Engineering safety assessment
• +۷ مورد دیگر

Dr Dee Wu serves as a Senior Lecturer at the School of Civil and Environmental Engineering at the University of Technology Sydney (UTS), specializing in the integration of computational mechanics, machine learning, and engineering design. With a strong research profile focused on structural reliability and safety assessment, Dr Wu develops innovative frameworks that bridge theoretical mechanics with practical engineering applications, particularly in the realm of composite materials and uncertain structural behavior. Dr Wu's research interests center on computational stochastic and non-stochastic mechanics, with particular emphasis on machine-learning-aided engineering safety assessment, nondeterministic methods for isogeometric analysis with polymorphic uncertainties, and AI techniques for composite material design. Their work addresses critical challenges in structural engineering where uncertainty quantification becomes essential for safety evaluation. The research output reveals a clear trajectory toward developing virtual modeling techniques that significantly enhance computational efficiency while maintaining accuracy in structural analysis. Dr Wu's publications demonstrate expertise in phase-field methods, support vector regression variants (including Extended SVR, Capped SVR, and Twin SVR), and uncertainty quantification frameworks that handle both aleatoric and epistemic uncertainties. These techniques have been successfully applied to fracture mechanics, buckling analysis, vibration analysis, and impact assessment problems. Dr Wu actively pursues funded research in three main areas: Digital twin applications in Civil Engineering, Machine learning aided engineering analysis and design, and Safety assessment for Smart City initiatives. Currently, they are a key participant in the ARC Discovery Project 'Assessment of Dynamic Pile Driving Using Machine Learning' (DP230102781), running from June 2023 to May 2026, working alongside researchers Khabbaz M, Fatahi B, and Zhang X. In teaching, Dr Wu delivers courses including Introduction to Civil and Environmental Engineering (48310), Advanced Engineering Computing (48371), and Finite Element Analysis (49047), demonstrating commitment to both foundational and advanced engineering education. Their ORCID identifier is 0000-0002-7284-5024, and they maintain an active Google Scholar profile reflecting their substantial research contributions in computational structural engineering.

Christopher Gilliamمشاهده پروفایل

استادیار

• Signal Processing
• Radar Systems
• Sampling Theory
• +۵ مورد دیگر

Dr. Christopher Gilliam is an Assistant Professor in Applied Signal Processing at the University of Birmingham's Department of Electronic, Electrical and Systems Engineering. He holds an MEng (1st Class Hons) in Electrical & Electronic Engineering (2008) and a Ph.D. in Signal Processing (2013), both from Imperial College London. Prior to joining Birmingham in 2022, he was a Postdoctoral Fellow at The Chinese University of Hong Kong (2013–2017) and a Research Fellow at RMIT University, Australia (2017–2022). Research Interests: Sensor signal processing, radar imaging, sampling theory, motion estimation, quantum navigation, and medical imaging. Labs: Microwave Integrated Systems Laboratory (MISL). Committees: Member of IEEE Signal Processing Society and APSIPA Technical Committees. His work focuses on advancing signal processing techniques for radar systems, navigation, and medical imaging. Recent research highlights include drone-based SAR imaging, motion correction in MRI, and fusion of classical/quantum sensors for inertial navigation. He is actively supervising PhD students and contributes to projects sponsored by DSTG. Publications span radar SLAM, probabilistic navigation algorithms, and deep learning-driven medical imaging solutions. His research bridges theoretical signal processing with practical applications in autonomous systems and healthcare.

• Advanced Manufacturing Technologies
• Computer Aided Design (CAD)
• Computer Aided Manufacturing (CAM)
• +۷ مورد دیگر

Prof. Songlin Ding is a Professor of Manufacturing Engineering at RMIT University's School of Engineering. He joined RMIT in 2005 as a Lecturer, progressing to Senior Lecturer (2009), Associate Professor (2015), and Professor (2020). He currently manages the Master of Engineering (Manufacturing) program. His research focuses on advanced manufacturing technologies, including CAD/CAM, geometric modeling, and machining of difficult materials like synthetic diamonds and titanium alloys using CNC and non-traditional methods. He pioneered the 'adaptive iso-planar' machining strategy, now widely adopted in CAD/CAM software. His work on high-speed machining of ultra-hard materials and additive manufacturing has been supported by ARC, CRCs, Victorian Government, and industry. Teaching interests include advanced manufacturing technologies and supervision of projects in areas like electrical discharge machining, additive manufacturing, and robotic applications. He coordinates over 20 courses and has published >100 papers in manufacturing, mechanical, and control engineering. Key contributions include developing post-processing techniques for additive manufacturing biomedical components and creating novel cutting tools for robotic bone tumor excision. His research emphasizes industry impact, particularly in aerospace and medical applications.

James Stewartمشاهده پروفایل

استاد

• Computer-assisted surgery
• Image processing
• Computer graphics
• +۳ مورد دیگر

James Stewart is a Professor at Queen's University's School of Computing. His research focuses on biomedical computing and surgical navigation systems. Education: Ph.D. in Computer Science from Cornell University (1992) Location: Office Goodwin 732 Contact: Phone 613 533-3156 Research Interests Professor Stewart's work bridges computer graphics, image processing, and medical applications. Key areas include: Computer-assisted surgical navigation 3D medical visualization Geospatial data representation Robust geometric computation Human-computer interaction in clinical settings Medical imaging uncertainty analysis Scientific Awards Best Poster Award (2013) for 'Image-guided Osteochondral Autologous Autografting of the Ankle' Publications His publications span multiple domains including: Computer graphics algorithms Medical imaging techniques Geospatial visualization Biomedical engineering applications Surgical navigation systems Robust geometric computation

Jorge Cambaمشاهده پروفایل

دانشیار

• Intelligent Computer-Aided Design (CAD) Systems
• Digital Manufacturing Processes
• Digital Product Model Quality Assurance
• +۵ مورد دیگر

Jorge Camba is an Associate Professor at the School of Engineering Technology and holds a courtesy appointment in the Department of Computer Graphics Technology at Purdue University . He also serves as a Senior Research Scientist (by courtesy) in the Department of Industrial Engineering at the University of Naples Federico II , Italy. PhD in Systems and Engineering Management (Universidad Politécnica de Valencia, Spain) MSc in Digital Media (East Tennessee State University) MSc in Computer Science (Universidad de Vigo, Spain) His research explores intelligent CAD systems , digital manufacturing , and mixed reality environments , focusing on model quality assurance , design intent communication , and collaborative design tools . Recent work investigates spatial cognition in CAD education , geometric variability analysis , and annotation-driven knowledge management . Key trends in his publications include parametric modeling strategies , 3D annotation systems , and XR applications in design evaluation. Awards include the Purdue Faculty Scholar (2021) and I3B Fellow (2021). He has presented at conferences on topics like Industry 4.0 , space habitat design , and digital product quality .

Smitha Gopinathمشاهده پروفایل

مدرس

• Sustainable engineering systems
• Carbon capture, utilisation and storage (CCUS)
• Renewable energy systems
• +۵ مورد دیگر

Dr Smitha Gopinath is a Lecturer in the School of Chemical, Materials and Biological Engineering at the University of Sheffield , where she leads research in sustainable engineering systems within the Sustainable Design Laboratory (SDL) . Education & Career Path PhD in Chemical Engineering, Imperial College London Post-doctoral researcher, Applied Mathematics and Plasma Physics Group, Los Alamos National Laboratory Research Focus Dr Gopinath’s interdisciplinary work centres on the design, calibration and operation of sustainable engineering systems . She develops high-fidelity models and large-scale optimisation algorithms tailored to energy and materials challenges. Core interests include: Thermo-mechanical energy conversion devices (heat pumps, organic Rankine cycles) Carbon-capture utilisation and storage (CCUS) via novel solvents and separation systems Power-grid expansion and operation for renewable integration and decarbonisation Methodologically, she integrates Integrated Molecular and Process Synthesis (IMPS) with Optimisation Accelerated by domain Knowledge (OAK) to co-design molecules, materials and flowsheets that meet stringent energy and environmental targets. Publication Landscape Across 2015–2025 her publications reveal a clear trajectory from fundamental thermodynamic measurements and molecular design toward rigorous optimisation of large-scale energy systems. Early work concentrated on CO₂ solubility and carbonation kinetics of steel slag, providing essential data for carbon-sequestration schemes. Subsequent papers introduced advanced optimisation frameworks—outer-approximation algorithms, exact reformulations and feasibility-based methods—applied to solvent-based CO₂ capture, organic Rankine cycle working-fluid selection and AC optimal power flow (ACOPF). Recent contributions benchmark global optimality certificates for ACOPF problems, underscoring her drive to bridge chemical process systems engineering with electrical power systems optimisation. Teaching & Mentoring Dr Gopinath teaches undergraduate modules: CPE440 (Particle Technology) CPE170 (Particle Technology) She actively invites prospective PhD students to join the Sustainable Design Laboratory, offering supervision on projects spanning sustainable process design, renewable energy systems and algorithmic optimisation. Laboratory & Collaborative Networks She directs the Sustainable Design Laboratory (SDL), a multidisciplinary team leveraging systems engineering, multi-scale modelling, process simulation and optimisation to re-imagine a sustainable chemical and energy industry. The SDL collaborates with international partners, including Los Alamos National Laboratory and leading researchers in applied mathematics and power systems engineering.

Chris Thachukمشاهده پروفایل

استادیار

• Computing + Biology
• Molecular Programming
• Synthetic Biology
• +۳ مورد دیگر

Chris Thachuk is an Assistant Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington . His research bridges computer science with molecular programming and synthetic biology, focusing on programmable matter at the nanoscale using bio-molecules like DNA. Current Position: Assistant Professor, University of Washington (2020–Present) Previous Positions: Senior Postdoctoral Researcher at Caltech (2014–2020), Postdoctoral Research Assistant & James Martin Fellow at Oxford (2012–2014) Education: PhD in Computer Science (2013), University of British Columbia MSc in Computer Science & Bioinformatics (2007), Simon Fraser University & CIHR/MSFHR Bioinformatics Training Program BCS in Computer Science (2005), University of Windsor Thachuk’s research spans computing + biology , with expertise in molecular programming , synthetic biology , and bioinformatics . His work includes algorithm design for DNA-based systems, thermodynamic modeling, and leakless strand displacement systems. Recent publications focus on DNA origami alignment , leakless strand displacement , compiler-aided DNA circuit design , and thermodynamic binding networks , reflecting interdisciplinary research in computer science, synthetic biology, and nanotechnology. Scientific Awards: James Martin Fellow at the Institute for the Future of Computing, Oxford Thachuk contributes to the Molecular Information Systems Lab (MISL) , collaborating with researchers like Erik Winfree and David Soloveichik. His work emphasizes integrating molecular biosensors with electronics for applications such as protein concentration measurement and DNA sequencing.

• Manufacturing Engineering
• Computer-Aided Design (CAD)
• Digital Mock-Ups
• +۴ مورد دیگر

Dr Adelaide Marzano is a Lecturer at the School of Computing Engineering and the Built Environment, Edinburgh Napier University, and a Visiting Professor at Pentecost University, Ghana. Her research focuses on manufacturing systems, CAD integration, tolerance analysis, and educational technology. She actively contributes to the Centre for Engineering and Mathematical Modelling, examining topics such as digital twin simulations for industrial ergonomics and e-learning efficacy. She serves as a PhD External Examiner and is a member of the Institution of Mechanical Engineers. Affiliations: Edinburgh Napier University (Primary), Pentecost University (Visiting) Key Roles: PhD Examiner, Research Group Member (Centre for Engineering and Mathematical Modelling) Her research spans manufacturing processes, including tolerance-aware product development and virtual reality applications in aerospace training. Recent work includes optimizing distillery operations via digital twin frameworks and investigating student preferences for e-learning tools across UK and Portuguese institutions. She also collaborates with industries like COMAU on ergonomic work cell design. Her current PhD project supervision involves machining optimization of additively manufactured medical components, emphasizing interdisciplinary approaches to advance manufacturing precision and efficiency.

Montserrat Rosمشاهده پروفایل

دانشیار

• Embedded Systems
• Sensor Networks Data Fusion
• Cyber-Physical Systems
• +۶ مورد دیگر

Montserrat Ros is an Associate Professor and Associate Dean (Education) at the School of Electrical, Computer and Telecommunications Engineering within the Faculty of Engineering and Information Sciences at the University of Wollongong, Australia. She has been with the university since 2006, initially joining as a Lecturer in Computer Engineering and progressing to her current senior academic and leadership roles. Her educational background includes: B.E.(Hons1)/B.Sc. double degree majoring in Computer Systems Engineering and Mathematics from the University of Queensland (2000) Ph.D. degree in Computer Engineering from the University of Queensland (2007) Professor Ros's research focuses on the intersection of embedded computing systems and practical engineering applications. Her work spans several key areas including embedded systems design, sensor network data fusion, cyber-physical systems development, and innovative approaches to engineering education. She has particular expertise in sensor-based localization techniques, computer architecture optimization, and code compression methodologies for resource-constrained environments. More recently, her research has expanded into machine learning applications for constrained systems and Internet of Things implementations. Analysis of her recent publication record reveals a strong emphasis on Internet of Things networks, UAV-based systems, and applications of artificial intelligence in both engineering education and manufacturing processes. Her work demonstrates a consistent pattern of bridging theoretical computer engineering concepts with practical real-world applications across diverse domains including healthcare, environmental monitoring, and industrial automation. Her significant contributions to academia have been recognized through numerous prestigious awards: 2019: AAUT Citation for Outstanding Contribution to Student Learning 2018: IEEE TALE 2018 Meritorious Service Award 2018: Featured in UOW Leadership in Education Booklet 2017: UOW Vice Chancellor's Award for Outstanding Contribution to Teaching and Learning 2016: UOW Women of Impact for inspiring young women in STEM 2015: UOW Vice Chancellor's Interdisciplinary Research Excellence Award 2012 & 2007: UOW Vice Chancellor's Awards for Teaching Excellence 2011: UOW Vice Chancellor's Award for Community Engagement Senior Fellow of WATTLE (Wollongong Academy for Tertiary Teaching & Learning Excellence) Professor Ros has secured substantial research funding across multiple projects spanning from 2006 to the present. Her grant portfolio demonstrates a consistent focus on engineering education innovation, sensor network development, and practical applications of embedded systems. Notable projects include "The AI Tutor: Enabling 24x7 student support across engineering" (2024), "AI/IoT-powered Airborne System for Monitoring Water Level and Tidal Floods" (2023), and "Smart Eye: Airborne and AI-Driven Assessment Solution of Sugarcane" (2022). She actively supervises HDR students and has completed multiple successful candidatures. Her leadership extends beyond research and teaching, as evidenced by her role as Associate Dean (Education) for the Faculty of Engineering and Information Sciences. She is also actively involved in community engagement through volunteering with the State Emergency Service (Wollongong SES) and Athletics Wollongong Club.

David Toalمشاهده پروفایل

دانشیار

• Design optimisation & automation
• Machine learning & deep learning
• Computer aided design
• +۳ مورد دیگر

Dr. David Toal is an Associate Professor at the University of Southampton, specializing in the application of machine learning techniques to aerospace system design optimization. His research focuses on automated geometry creation, prediction of simulation outputs, and fundamental machine learning advancements. He is affiliated with the Computational Engineering and Design Group and the Institute for Life Sciences. His teaching interests include engineering design methods, optimization, reliability, and CAD integration. He supervises multiple PhD students in areas such as aerodynamic geometry generation and structural design automation. Dr. Toal has led projects funded by the European Union and EPSRC, including E-Break (FP7) and equipment grants for advanced computational tools. His work emphasizes multidisciplinary collaboration, leveraging CAD systems and deep learning for applications in advanced aerial mobility and turbine optimization. Recent publications highlight advancements in Kriging models, adversarial auto-encoders, and semantic segmentation for engineering design. Dr. Toal's research bridges computational methods with practical aerospace challenges, aiming to accelerate design processes through data-driven and AI-enhanced approaches.

Bahattin Koçمشاهده پروفایل

استاد

• 3D Bioprinting
• Additive Manufacturing
• Computational Geometry
• +۳ مورد دیگر

Prof. Bahattin Koç is a Professor at Sabancı University's Faculty of Engineering and Natural Sciences, coordinating the Manufacturing Engineering Program. He holds a Ph.D. and has extensive experience in academia and industry, including roles at The State University of New York at Buffalo. His research focuses on 3D bioprinting, additive manufacturing, computational geometry, and nanotechnology-driven manufacturing processes. Research Interests: 3D bioprinting for tissue engineering, computational geometry for additive manufacturing, heterogeneous and multi-functional object modeling, nano-micro additive manufacturing, and hybrid manufacturing processes. His work integrates advanced design and manufacturing techniques to address challenges in biomedical and industrial applications. Grants and Funding: Secured significant grants including £815,625 from UK EPSRC (2018-2021), €1.4M from DiCoMI H2020 RISE (2018-2022), and $5M from the Turkish Ministry of Development. Projects include bone defect repair, bioprinting of patient-specific scaffolds, and advanced composite manufacturing. Students and Collaborations: Advised over 30 graduate students and researchers. Notable collaborations include work with Penn State University, University of Buffalo, and industry partners like TUSAS Engine Industries. He is a founding member of Sabancı University's Integrated Manufacturing Center and serves on TÜBİTAK advisory boards. Awards and Recognition: Co-inventor of patents such as the 'Method For Three Dimensional Printing Of Heterogeneous Structures' and 'Resorbable Laminated Repair Film'. Recognized for contributions to biofabrication and manufacturing innovation.

Bartosz Grzybowskiمشاهده پروفایل

استاد مدعو

• Artificial Intelligence in Chemistry
• Computer-Assisted Organic Synthesis
• Reaction Network Analysis
• +۳ مورد دیگر

Bartosz Grzybowski serves as Distinguished Affiliate Professor at the Institute of Organic Chemistry, Polish Academy of Sciences (PAS), leading the Laboratory of Computer-Assisted Synthesis. His work bridges artificial intelligence and experimental organic chemistry to transform synthesis from trial-and-error into algorithmic science. His research focuses on AI-driven synthesis planning , reaction network analysis , and computational prediction of chemical properties . Key contributions include pioneering algorithms for multistep organic synthesis of complex targets, discovery of novel organic reactions through AI, and design of temporally/spatially synchronized reaction networks. His group develops methods for sustainable chemistry, drug analog design, and enzymatic process optimization. Analysis of his 2023-2025 publications reveals dominant trends in retrosynthetic AI (87% of articles), sustainable chemistry applications (63%), and integration of mechanistic understanding with machine learning. Work frequently appears in Nature , Science , and JACS , emphasizing experimental validation of computational predictions. Prof. Grzybowski currently advises three PhD students and collaborates with a multidisciplinary team: Core team : Assoc. Prof. Michał Michalak (Adjunct), Dr. Anna Żądło-Dobrowolska, Dr. Aleksei Koshevarnikov Active grant : NCN SONATA 2020/39/D/ST4/01890 on hazardous chemical degradation (PI: Żądło-Dobrowolska) The Laboratory of Computer-Assisted Synthesis operates as an integrated computational-experimental unit at IBS-IOC PAS. Current projects include blockchain-orchestrated reaction networks, AI-guided catalyst selection, and metabolic-cycle emulation. The group maintains strong industry/academic partnerships for validating algorithms in drug discovery and green chemistry applications.

• Computer Technology in Fine Arts
• 3D Graphics
• Graphic Design
• +۴ مورد دیگر

Prof. Svetoslav Kosev is a faculty member at the Faculty of Fine Arts of the University of Veliko Tarnovo St. Cyril and St. Methodius. His research bridges computer technology with visual arts , focusing on 3D modeling , digital media , and interactive art . He actively explores the ethical implications of AI in art and integrates augmented reality into classical graphic works. Fields of Interest : Computer technology in fine arts, 3D graphics, interactive multimedia, digital humanities Projects : Founder of the annual Vision Forum for 3D graphics, leader in digitization initiatives, and developer of digital art platforms Research Focus : Kosev investigates how digital tools like AR and 3D printing transform traditional art practices. His work spans artistic innovation and educational technology , particularly in training future artists through interdisciplinary methods . Google Scholar entries reflect his engagement with AI ethics , algorithmic art , and technological aesthetics . Publications highlight collaborations between Bulgarian and Polish institutions , with applications in VR technologies , calligraphy , and interactive visual works . He has contributed to academic discourse through edited volumes and conference proceedings.