جست‌وجوی استاد و پژوهشگر

Lars Linsenمشاهده پروفایل

استاد

• Interactive Visual Analysis
• Medical Visualization
• Scientific Visualization
• +۴ مورد دیگر

Prof. Dr.-Ing. Lars Linsen is a full Professor of Computer Science at the Westfälische Wilhelms-Universität (WWU) Münster, leading the VISualization & graphIX (VISIX) group. His primary affiliation is the Institute of Computer Science within the Faculty of Mathematics and Computer Science. He holds adjunct professorships at Jacobs University, Bremen, and has held previous academic roles including Full Professor at Jacobs University (2012–2017) and Associate/Assistant Professor roles in Germany and the U.S. His research focuses on interactive visual analysis, medical visualization, and scientific visualization, with applications in life sciences and engineering. Education: PhD (Dr.-Ing.) in Computer Science from Universität Karlsruhe (2001), M.Sc. (Diplom) in Computer Science (1997), B.Sc. (Vordiplom) in Computer Science (1994). Awards: IEEE Visualization Design Contest Winner (2008, 2022, 2018), Preis des Fördervereins des Forschungszentrum Informatik (2002). Research Highlights: Develops visualization tools for medical imaging (e.g., mass spectrometry imaging, MRI data analysis) and physical simulations (e.g., wildfire spread analysis, asteroid impact modeling). Active in EU-funded projects like Pig-Pro-QuO (surface coatings) and cells-in-motion initiatives. Supervised over 20 PhD/MS advisees, including notable graduates in medical visualization and simulation ensemble analysis. Publications: Over 100 peer-reviewed articles in top venues like IEEE Transactions on Visualization and Computer Graphics, Computers & Graphics, and EuroVis. Key works include SciVis contest-winning wildfire analysis frameworks and medical visualization tools for stenosis detection. Teaching: Offers courses on visualization, computer graphics, and computational science. Actively involved in thesis supervision and curriculum development at both WWU Münster and Jacobs University. Grants & Collaborations: Principal investigator on DFG-funded projects (e.g., hemodynamics simulations, ensemble visualization) and industry collaborations (e.g., Tascon GmbH for coating quality analysis). Member of the Cells-in-Motion Interfaculty Centre and CDH board at WWU.

Jason H. Andersonمشاهده پروفایل

استاد

• Computer Engineering
• Electrical Engineering
• Computer-Aided Design (CAD)
• +۳ مورد دیگر

Professor Jason H. Anderson is a faculty member in the Department of Electrical & Computer Engineering (ECE) at the University of Toronto, affiliated with the Faculty of Applied Science & Engineering. He specializes in computer engineering, with a focus on field-programmable gate arrays (FPGAs) and related computer-aided design (CAD) tools. BSc in Computer Engineering from the University of Manitoba MASc and PhD in Electrical & Computer Engineering from the University of Toronto His research spans FPGA architecture, circuit design, and CAD tool development. He has contributed to strategic R&D projects through his academic and industry roles. Scientific awards include multiple Best Paper Awards at IEEE and ACM conferences (2017, 2014, 2011, 2010, 2009), the Xilinx Ross Freeman Award (2000), and teaching accolades such as the Gordon Slemon Award (2012) and several ECE Departmental Teaching Awards (2009-2014). He served as General Chair and Program Chair for leading FPGA conferences. As Chief Scientific Advisor and Co-Founder of LegUp Computing Inc., he bridges academic research with industry innovation. He is a licensed Professional Engineer in Ontario and an active IEEE/ACM member.

• Reconfigurable Computing
• Machine Learning Acceleration
• Hardware Acceleration
• +۵ مورد دیگر

Aman Arora is an Assistant Professor at Arizona State University's Ira A. Fulton Schools of Engineering, specializing in the School of Computing and Augmented Intelligence. His research focuses on reconfigurable computing, hardware acceleration of machine learning, and non-traditional computing paradigms like Processing-In-Memory. With over a decade of semiconductor industry experience, he bridges academic research and industrial applications. PhD in Computer Science from The University of Texas at Austin Research interests emphasize domain-specific acceleration through FPGA optimization , compute-in-memory architectures , and machine learning for CAD/EDA . His work addresses critical challenges in energy efficiency and throughput for AI workloads. Recent publications demonstrate trends toward compute-in-memory systems , FPGA-based deep learning acceleration , and sustainable hardware design . Key contributions include frameworks like SAF, CSR, and GAMA for dynamic hardware optimization. Laboratory Website: ADVENT Lab Teaching includes courses on digital hardware design (CSE 320) and advanced topics in machine learning acceleration (CEN 524/CSE 524). Industry experience informs his practical approach to research and education.

• Power cycles and turbomachinery
• CO2 capture
• Process modeling and simulation
• +۳ مورد دیگر

Lars O. Nord is a Professor in the Department of Energy and Process Engineering at NTNU, specializing in thermal energy systems, CO2 capture technologies, and dynamic process modeling. He holds a PhD from NTNU (2010) and a Master's from Virginia Tech (2001). His research focuses on power cycles, turbomachinery optimization, and decarbonization strategies for energy systems. Nord has led projects such as DEXPAND and InnCapPlant, addressing CO2 capture under variable loads and expander efficiency in renewable systems. Current roles: Head of the Thermal Energy research group and teaches courses like Engineering Thermodynamics. Research highlights include thermal energy storage integration, moving bed adsorption processes, and offshore hybrid energy systems. His work spans over 80 publications, emphasizing CO2 capture dynamics, turbine design, and control strategies for flexible power plants. Notable collaborations include SINTEF and Aker Solutions. Nord advises multiple PhD candidates and has mentored alumni now leading roles in industry and academia.

Matt Rattoمشاهده پروفایل

استاد

• Artificial Intelligence
• Human-Computer Interaction
• Critical Making
• +۷ مورد دیگر

Matt Ratto is a full Professor in the Faculty of Information at the University of Toronto , where he also serves as Associate Dean, Research . He is a faculty affiliate of the Climate Positive Energy Institute , the Schwartz Reisman Institute for Technology and Society , and an SDG Fellow with the Sustainable Development Goals Institute . His work bridges critical theory and digital innovation , focusing on the social production of knowledge through emerging technologies. His research explores critical making and socio-technical systems , with applications in 3D-printed prosthetics (deployed in Cambodia, Tanzania, and Uganda), AI-driven healthcare solutions , and climate justice in computing . He has received over $6 million in funding, including two Canada Grand Challenge grants , and founded organizations advancing equitable technology access. Ontario Minister of College and Universities’ Award of Excellence (2020) Bell Canada Usability Labs Chair in Human-Computer Interaction (2018–2023) He supervises students such as Olivia Doggett and Sarah Gram , with past advisees including Brian Sutherland and Dan Southwick . His Critical Making Lab fosters interdisciplinary collaboration, and he teaches courses like INF2241: Critical Making and INF351: Information Design Studio .

• Computer Graphics
• Computer Vision
• Human-Computer Interaction
• +۷ مورد دیگر

Changjian Li is an Assistant Professor in the School of Informatics at the University of Edinburgh. He leads the GraphViX Group (Graphics, Vision and X) and is a member of the Institute of Perception, Action and Behaviour (IPAB). His research spans computer graphics, computer vision, and human-computer interaction with a focus on 3D generation and analysis. Education: Bachelor's Degree from Shandong University (2014) Ph.D. from the University of Hong Kong (2019) under Prof. Wenping Wang Postdoc at University College London (UCL) with Prof. Niloy Mitra Starting Researcher position at Inria with Dr. Adrien Bousseau Research Interests: Changjian's research focuses on sketch-based 3D modeling, CAD modeling, point cloud processing, and medical imaging applications. He develops systems that bridge intuitive sketching with precise CAD workflows, enhances 3D animation pipelines, and applies neural methods to sparse medical data reconstruction. Scientific Recognition: Best Paper Honorable Mention Award (MICCAI 2021) CADTalk selected as Highlight (CVPR 2024 top 10%) ACM SIGGRAPH Asia 2018 cover image selection ACM SIGGRAPH Asia 2015 technical paper highlight CVPR 2019 poster highlighted in 'Computer Vision News' Advising & Collaborations: He mentors postdocs and PhD students including Duolikun Danier, Haocheng Yuan, Ankan Bhunia, and Lei Zhong. Former advisees include Salvatore Esposito (now at Edinburgh), Guangshun Wei (Shandong University), and Mingjun Yang (University of Melbourne). Collaborates with Oisin Mac Aodha, Hakan Bilen, and Niloy Mitra. Professional Service: Currently serves as Associate Editor for IEEE TVCG and participates in program committees for SIGGRAPH Asia, SIGGRAPH, EuroGraphics, and Geometry Design and Computing (GDC) conferences.

Declan Nolanمشاهده پروفایل

مدرس ارشد

• Design to Simulation Automation
• Structural Impact Analysis
• Composite Simulation
• +۸ مورد دیگر

Declan Nolan is a Senior Lecturer in the School of Mechanical and Aerospace Engineering at Queen's University Belfast. He holds a PhD (2013) on 'Defining Simulation Intent,' focusing on automating simulation workflows. Before academia, he worked at Michelin, Williams F1 (as a Stress Engineer), and B/E Aerospace (Senior Structural Engineer), specializing in composite structures and structural integrity. He currently serves as Postgraduate Research Director (since 2022) and is a member of the EPSRC Early Career Forum in Manufacturing and the Circular Economy, and UKACM board member. His research spans design-to-simulation automation, bio-inspired design, and structural impact analysis. Key projects include PROTEUS (reimagining engineering design), COLIBRI (composite research), and Biohaviour (biological development analogies). He teaches Mechanics of Materials and Computer-Aided Engineering courses. Education: PhD in Mechanical and Aerospace Engineering (2013) Affiliations: Chartered Engineer, IMechE Member Grants/Projects: 4 active research grants, including EPSRC-funded initiatives Research outputs include 45+ publications, with recent focus on propulsion system integration, parametric nacelle modeling, and CAD-based machine learning. He has received two Best Paper Awards (2019) for manufacturing research contributions.

• Mesh generation
• Numerical simulation
• Finite element methods
• +۵ مورد دیگر

Houman BOROUCHAKI is a Professor at the University of Technology of Troyes (UTT), France, with over 20 years of academic leadership. He has served as Head of the Automatic Mesh Generation and Advanced Methods (GAMMA3) project team since 2008 and previously led the Laboratory of Mechanical Systems and Concurrent Engineering (LASMIS) (2005-2007). His work bridges academic research and industrial applications through collaborations with INRIA , French Petroleum Institute (IFPEN) , Dassault Aviation , and others. Research Interests: A pioneer in adaptive meshing , he focuses on finite element methods , geometric modeling , and numerical simulations . His innovations underpin mesh generation algorithms , 3D triangulation software , and industrial applications in metal forming, composite simulation, and subterranean modeling. Scientific Trends: His recent work emphasizes metric-based meshing , high-order geometric validity , and parallel processing for mesh generation , with applications in petroleum reservoirs, aviation surfaces, and nanomaterials. His Google Scholar profile reflects 25+ years of contributions to meshing and simulation. Teaching: With 22 years of experience, he teaches courses on meshing , numerical analysis , geometric modeling , and computer graphics at UTT, covering undergraduate to PhD levels. Labs & Teams: He leads the interdisciplinary GAMMA3 team and has contributed to LASMIS (mechanical engineering), L2n (CNRS-UMR 7076) (nanomaterials), and LIST3N (computer science).

• Digital Design and Manufacturing (D2M)
• Sustainable Manufacturing
• Optimization Driven Design
• +۷ مورد دیگر

Inigo Flores Ituarte is a Research Professor at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He leads the Digital Design and Manufacturing (D2M) research lab, focusing on sustainable manufacturing and twin-transition strategies integrating digital and green technologies. His work emphasizes optimization-driven design, additive manufacturing innovations, and AI-driven expert systems to enhance energy efficiency and reduce environmental impacts. Key research pillars include: Pillar 1: Twin-transition in Engineering Design and Manufacturing Processes, addressing sustainable manufacturing and intelligent systems Pillar 2: Development of open D2M systems and Process-Structure-Property-Performance (PSPP) linkages in advanced materials His research explores multi-disciplinary optimization combining model-based simulations and data-driven techniques. Notable contributions include generative AI integration in CAD systems, cognitive manufacturing systems, and cost-effective process monitoring using CNN-based methods. Inigo's work emphasizes environmental sustainability, with a focus on reducing manufacturing's energy consumption (54% of global use) and CO2 emissions. He advocates for interconnected material systems, smart manufacturing processes, and AI-assisted decision-making to achieve cognitive intelligence in industrial operations. His D2M lab's overarching goal is to maximize product/process performance while improving cost-effectiveness and minimizing environmental footprints. Recent projects include railway bogie demonstrators via multi-material deposition and sensor systems leveraging IoT and ChatGPT integration.

Martin Bechtholdمشاهده پروفایل

استاد

• Architectural Technology
• Materials Science
• Design Engineering
• +۴ مورد دیگر

Martin Bechthold is the Kumagai Professor of Architectural Technology at Harvard University’s Graduate School of Design (GSD), serving concurrently as the GSD’s Academic Dean. He holds affiliations with Harvard’s Paulson School of Engineering and Applied Sciences and the Wyss Institute for Biologically Inspired Engineering. His academic career bridges architecture, materials science, and engineering, with a focus on innovative material systems and design robotics. Bechthold earned a Diplom-Ingenieur in architecture from RWTH Aachen University and a Doctor of Design from Harvard GSD. He previously practiced architecture in Europe with firms like Skidmore, Owings & Merrill and Santiago Calatrava. His research groups, including the Material Processes and Systems (MaP+S) Group and the Design Robotics Group, explore topics like multi-material 3D printing, carbon-negative materials, and biofabrication. He founded the Laboratory for Design Technology to foster industry-academia collaborations. His research interests span structural innovation, architectural ceramics, and the perception of materials. He has authored seminal works such as Innovative Surface Structures and Ceramic Material Systems , and his peer-reviewed papers appear in Nature Reviews and Advanced Functional Materials . He teaches advanced courses on material systems, design methods, and structural design. Bechthold’s work emphasizes sustainable technologies and cross-disciplinary design, with projects like the Concrete Origami and Ceramic Futures exhibitions showcasing experimental material applications. He holds patents in material innovation and has curated influential design exhibitions.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

Jonathan Roseمشاهده پروفایل

استاد

• FPGA architecture
• Computer-Aided Design (CAD)
• Field-Programmable Systems
• +۳ مورد دیگر

Jonathan Rose is a Professor in the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto . He received his PhD in Electrical Engineering from the University of Toronto in 1986 and held postdoctoral and research roles at Stanford University's Computer Systems Laboratory (1986-1989). His academic career spans decades, including a 1998-1999 sabbatical at Xilinx and leadership roles at Altera Toronto Technology Centre. He served as Department Chair of Electrical and Computer Engineering (2004-2009) and directed the Engineering Business Minor (2010-2017). Currently, he chairs the Engineering Entrepreneurship Hatchery Advisory Board and engages with organizations like Academics without Borders and Massey College. His research has historically focused on FPGA architecture , Computer-Aided Design (CAD) , Field-Programmable Systems , and Soft Processors . More recently, his work explores the Automation of Medicine , particularly in mental health. His contributions include co-founding the ACM FPGA Symposium and receiving numerous awards for teaching, research, and leadership. Scientific Awards : University of Toronto Engineering Alumni Hall of Distinction Award, 2017 Best Paper Award, ACM TRETS, 2016 University of Toronto President’s Teaching Award, 2016 Foreign Member of the American National Academy of Engineering, 2011 Fellow of the Royal Society of Canada, 2012 The 15 most recent articles reflect his interdisciplinary engagement, spanning Political Science , Public Policy , and Deliberative Democracy , with sub-fields such as Employability Support , Electoral Reform , and Local Governance . His career bridges engineering innovation and societal challenges, particularly in governance and policy.

Wenjing Raoمشاهده پروفایل

دانشیار

• VLSI Test
• Fault-Tolerance
• Reliability
• +۳ مورد دیگر

Wenjing Rao is an Associate Professor at the Department of Electrical and Computer Engineering, College of Engineering, University of Illinois at Chicago (UIC). Her research focuses on VLSI test, fault-tolerance, reliability, and hardware security in emerging nanoelectronic systems. Education: Ph.D. in Computer Science from University of California, San Diego (2008) B.S. in Computer Science from Peking University (2001) Her work explores novel computation paradigms through physical unclonable functions (PUFs), defect-tolerant logic implementation, and scalable fault tolerance in many-processor arrays. Publications emphasize hardware security, reconfiguration strategies, and reliability challenges in nanoscale architectures. Notable honors include the 2017 Harold A. Simon Award for Excellence in Teaching and the 2012 NSF CAREER Award. She has contributed to key journals like IEEE Transactions on Computer-Aided Design and conferences including DATE, ASPDAC, and NANOARCH.

David Zhigang Panمشاهده پروفایل

استاد

• Electronic Design Automation
• Machine Learning
• Hardware Acceleration
• +۵ مورد دیگر

David Zhigang Pan is a Professor in the Department of Electrical & Computer Engineering at The University of Texas at Austin. He also holds the Silicon Laboratories Endowed Chair. Prior to joining UT Austin, he was a Research Staff Member at IBM T. J. Watson Research Center from 2000 to 2003. His academic journey began with a B.S. from Peking University, followed by M.S. and Ph.D. degrees from UCLA. Research Areas: Electronic Design Automation (EDA), Machine Learning Hardware, FPGA Prototyping, Optical Computing, Hardware Security, and CAD for Emerging Technologies Academic Timeline: Assistant Professor (2003-2008), Associate Professor (2008-2013), Full Professor (2013-present) His research focuses on design automation for mixed-signal circuits , GPU-accelerated EDA tools , and hardware-software co-design for AI . Recent work explores FFT-based optical neural networks and deobfuscation techniques for integrated circuits , reflecting his interdisciplinary approach at the intersection of machine learning , computer architecture , and semiconductor manufacturing . Key publication trends reveal expertise in: VLSI design , lithography optimization , and deep learning applications for EDA tools. His work has been recognized with multiple Best Paper Awards at top conferences including DAC , ASP-DAC , and HOST . Awards: IEEE Fellow (2014), SPIE Fellow (2017), ACM SRC Graduate Category Honors for students Patents: 8 U.S. Patents in electronic design and hardware optimization Prof. Pan has mentored 40 PhDs and postdocs who now hold key positions in academia and industry. He leads research initiatives involving GPU acceleration frameworks and optical computing architectures . His lab focuses on vertical integration of architecture, CAD tools, and fabrication technologies for next-generation hardware solutions.

James Reed Farreمشاهده پروفایل

پژوهشگر

• Hyperbolic Geometry
• Dynamics
• Teichmüller Theory
• +۴ مورد دیگر

James Reed Farre is a Researcher and Research Group Leader at the Max Planck Institute for Mathematics in the Sciences (MPI MiS) in Leipzig, leading the Geometry on Surfaces group since October 2023. Previously, he held roles including Juniorprofessor (W1/Assistant Professor) at Ruprecht-Karls-Universität Heidelberg (2022–2023), Gibbs Assistant Professor at Yale University (2021–2022), and an NSF Postdoctoral Fellow at Yale (2019–2020). He earned his PhD in Mathematics from the University of Utah in 2019 under Kenneth Bromberg. His research focuses on hyperbolic geometry, dynamics of earthquake flows, Teichmüller theory, and geometric group theory. Notable areas include affine laminations, hyperconvex representations of surface groups, and ergodic theory in geometric contexts. Farre has contributed to understanding minimal surfaces in hyperbolic 3-manifolds and has explored applications of bounded cohomology to discrete groups. Publications span topics like shear-shape cocycles, horocycle orbit closures, and Hamiltonian flows for pseudo-Anosov mapping classes. His work bridges pure geometry with computational methods, as seen in CAD algorithm development for rigid subsystems. Farre is actively involved in mentoring and has contributed to STEM education initiatives, including the Freshman Research Initiative.