جست‌وجوی استاد و پژوهشگر

Reza Fotouhiمشاهده پروفایل

استاد

• Robotics (Dynamics and Control)
• Structural Dynamics and Vibrations
• Computational Mechanics (Finite Element and Optimization)
• +۴ مورد دیگر

Reza Fotouhi is a Professor in the Department of Mechanical Engineering at the University of Saskatchewan, specializing in Robotics (Dynamics and Control), Structural Dynamics and Vibrations, Computational Mechanics, and Biomechanics. He leads research in agricultural robotics, finite element modeling, and teleoperated systems. Education: BSc, MSc (Iran) MSc, PhD (University of Saskatchewan) His research focuses on human-robot interaction, vibration control for flexible manipulators, composite material applications, and teleultrasound systems. He has developed mobile platforms for crop phenotyping and optimized control strategies for robotic arms. Recent Article Trends: His work spans telerobotic medical systems, agricultural automation, advanced control algorithms (e.g., Particle Swarm Optimization), and structural analysis of composite materials. Key subfields include musculoskeletal imaging, path planning, and dynamic modeling of flexible systems. Research Groups: Applied Mechanics and Machine Design Control Systems, Robotics and Fluid Power Engineering for Agriculture

Stephen Pankavichمشاهده پروفایل

استاد

• Partial Differential Equations
• Kinetic Theory
• Mathematical Biology
• +۴ مورد دیگر

Stephen Pankavich is a Professor and Department Head in the Department of Applied Mathematics and Statistics at the Colorado School of Mines. He holds a PhD in Mathematical Sciences from Carnegie Mellon University, with research focused on partial differential equations, kinetic theory, and mathematical biology. His work bridges theoretical analysis and computational methods, addressing challenges in plasma dynamics, epidemiological modeling, and multiscale systems. Education: PhD, Mathematical Sciences, Carnegie Mellon University (2005) MS, Mathematical Sciences, Carnegie Mellon University (2001) BS, Mathematical Sciences, Carnegie Mellon University (2000) Research interests include the analytical and numerical study of collisionless plasmas, HIV dynamics, and epidemiological models. He has received awards such as the W.M. Keck Mentorship Award and the Colorado School of Mines Alumni Teaching Award. His articles explore topics like plasma decay rates, HIV therapy models, and particle-tracking algorithms. He has advised over 20 graduate and undergraduate students, contributing to impactful research in applied mathematics and computational science.

Kirk R. Pruhsمشاهده پروفایل

استاد

• Algorithmic problems related to green computing
• Fair allocation
• Resource management
• +۳ مورد دیگر

Professor Kirk R. Pruhs is a full Professor in the Department of Computer Science at the University of Pittsburgh's School of Computing and Information. He holds editorial roles at journals such as the Journal of Scheduling and ACM Transactions on Algorithms. His research focuses on algorithmic problems in green computing, scheduling, online optimization, and resource management. Pruhs has advised numerous PhD students and has a strong publication record in top venues like SODA, STOC, and FOCS. His work often addresses energy-efficient algorithms and computational resource management. Notable contributions include studies on stochastic scheduling, energy-efficient routing, and competitive analysis of online algorithms. Education: BS in Mathematics and Computer Science from Iowa State University (1984), PhD in Computer Science from University of Wisconsin-Madison (1989). Research Interests: Algorithmic challenges in green computing, fair allocation mechanisms, scheduling under uncertainty, and online optimization techniques. He explores how computational methods can improve energy efficiency and resource allocation in distributed systems. Recent articles focus on robust scheduling strategies, stochastic systems, and algorithmic approaches to network design and resource optimization. His work bridges theoretical computer science with practical applications in sustainable computing. Students: Includes Jonathan Beaver (2006), Mohamed Aly (2008), Christine Chung (2009), Daniel Cole (2013), Neal Barcelo (2015), Michael Nugent (2015), and Alireza Samadian Zakaria (2021). Labs/Teams: Engaged in algorithm design and analysis within the Department of Computer Science, contributing to initiatives in computational sustainability and high-performance computing.

Vivy Suhendraمشاهده پروفایل

دانشیار

• Software Assurance
• Security and Privacy
• Cybersecurity
• +۱ مورد دیگر

Vivy Suhendra serves as Associate Professor of Practice and Programme Director for Master Programmes at the National University of Singapore's School of Computing, while also holding the position of Assistant Dean for Graduate Studies. Previously, she led the Singapore Cybersecurity Consortium (SGCSC) as Executive Director from 2016 to 2022, driving collaborative cybersecurity research between academia, industry, and government agencies. Her career at NUS spans over two decades, beginning as a Research Assistant before advancing to her current leadership roles. Her academic credentials include: Ph.D. in Computer Science, National University of Singapore (2009). Thesis: "Memory Optimizations for Time-predictable Embedded Software". Advisors: Abhik Roychoudhury and Tulika Mitra. B.Comp. (Honors) in Computer Science, National University of Singapore (2004). Dr. Suhendra's research integrates Software Assurance, Cybersecurity, Security and Privacy, and Embedded Systems domains. Her work bridges theoretical foundations with practical applications, particularly in national cybersecurity ecosystem development, smart grid security protocols, denial-of-service mitigation techniques, and real-time embedded system optimization. This interdisciplinary approach enables innovative solutions for critical infrastructure protection and time-predictable software execution in multi-core environments. Her 14 selected publications (2004-2020) demonstrate an evolving research trajectory from foundational embedded systems timing analysis to applied cybersecurity solutions. Early work focused on memory optimization for predictable execution in multi-core embedded systems, which naturally transitioned into cybersecurity applications for smart grids, cloud environments, and national infrastructure. This progression highlights her ability to translate low-level system expertise into high-impact security frameworks for complex real-world systems. Scientific recognition includes: Microsoft Research Asia Fellowship (2006) Valedictorian at NUS School of Computing Ph.D. Commencement (2010) While specific graduate student advising details aren't provided, her leadership as SGCSC Executive Director involved extensive mentorship across academic-industry partnerships. She has also contributed significantly to the research community through roles including Conference Chair for ESEC/FSE 2022 and Workshops Committee Member for ICSE 2024. Dr. Suhendra established the Singapore Cybersecurity Consortium as a national platform for collaborative R&D during her directorship (2016-2022). Though no personal laboratory is specified, her research leadership manifests through cross-institutional teams focused on cybersecurity innovation, particularly in critical infrastructure protection and embedded systems security where she maintains active publication records.

Mohamed Farhatمشاهده پروفایل

پژوهشگر

• Cavitation & Multiphase flows
• Flow Induced Noise & Vibration
• Fluid-Structure Interaction
• +۵ مورد دیگر

Mohamed Farhat is a Senior Scientist at EPFL's School of Engineering, Department of Mechanical Engineering, where he leads the Research Group on Cavitation and Interface Phenomena. He serves as PhD Director, Lecturer, and Member of EPFL Doctoral Committee (Mechanics), while also representing EPFL at CLUSER association and coordinating activities at the Société Hydrotechnique de France (SHF). His research expertise spans Cavitation & Multiphase flows, Flow Induced Noise & Vibration, Fluid-Structure Interaction, Flow control, Flow instabilities in hydro turbines and pumps, Condition monitoring of Hydraulic Machines, Hemodynamics, and Advanced Instrumentation in Fluid Dynamics. Farhat's work uniquely bridges fundamental fluid mechanics with practical applications across hydropower, marine propulsion, healthcare, and water management sectors. Analysis of his recent publications reveals strong focus on cavitation bubble dynamics, with particular emphasis on measurement techniques for collapsing bubbles, vortex shedding control, hydrodynamic monitoring of hydraulic machinery, and biomedical applications of cavitation phenomena. His work increasingly integrates advanced imaging techniques with computational modeling to understand complex multiphase flow phenomena. 2021: Life Sciences Book Award of the International Academy of Astronautics 2019: 1st Prize Winner of Scientific Image Contest (Swiss National Science Foundation) 2020: EPFL-Rhyming Prize (Best PhD thesis in Fluid Mechanics) 2018: EPFL-EDME Prize (Best PhD thesis in Mechanics) 2015: Edmund Optics Educational Award 2014: APS-DFD Gallery of Fluid Motion Award Farhat has successfully supervised numerous PhD students including Ali Amini, Philippe Ausoni, and Outi Supponen, with research spanning from fundamental bubble dynamics to practical hydraulic machinery applications. His Cavitation Research Group maintains strong collaborations with industry partners in hydropower and medical device sectors. Current research directions include advanced instrumentation for cavitation monitoring, condition-based maintenance of hydraulic machinery, and biomedical applications of cavitation phenomena in therapeutic ultrasound and drug delivery.

Anja Skrivervikمشاهده پروفایل

استاد

• Antenna Design
• Wireless Power Transfer
• Implantable Medical Devices
• +۷ مورد دیگر

Anja Skrivervik is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), holding multiple key academic positions across the institution. She serves as a Full Professor in the School of Engineering (STI) within the Electromagnetics and Antennas group, as Director of the Electrical Engineering Doctoral Program, and as a Full Professor in multiple teaching units including EDEE, SEL, and EDMI. Her extensive institutional affiliations demonstrate her significant leadership role within EPFL's engineering and educational frameworks. Professor Skrivervik's research spans multiple cutting-edge domains in electromagnetic engineering with a particular focus on antenna design for specialized applications. Her work prominently features implantable medical devices, where she develops antennas and wireless power transfer systems for deep-body bioelectronics. She has made significant contributions to mm-Wave technology, particularly in multibeam systems for 5G applications and wireless power transfer. Her research also encompasses tissue phantom development for electromagnetic characterization, with recent work on biodegradable alternatives to traditional materials. The interdisciplinary nature of her work bridges electrical engineering, biomedical applications, and materials science. An analysis of her recent publications (2023-2025) reveals a consistent research trajectory focused on solving practical challenges in antenna design for constrained environments. Her work shows particular strength in optimizing antenna performance for implantable medical devices, where size, efficiency, and biocompatibility present unique challenges. She has developed novel approaches to beamsteering, mutual coupling reduction, and RF radiation modeling specifically tailored for medical applications. Her contributions to tissue phantom development represent an important methodological advancement for testing and validating implantable devices. As Director of the Electrical Engineering Doctoral Program and through her multiple professorial appointments, Professor Skrivervik plays a central role in shaping graduate education at EPFL. Her leadership extends to serving on the Doctoral Commission, where she helps set standards and policies for doctoral education across the institution. While specific grant information isn't detailed in the available materials, her extensive publication record across top journals and conferences suggests successful funding of her research activities. Her work appears to be conducted within EPFL's Electromagnetics and Antennas group (SCI STI AS), which likely houses specialized laboratories for antenna measurement, electromagnetic simulation, and biomedical device testing. The focus on tissue phantoms and implantable devices suggests dedicated facilities for biomedical electromagnetic testing, while her mm-Wave and 5G research indicates capabilities in high-frequency measurement and characterization.

Joseph Katzمشاهده پروفایل

استاد

• Experimental Fluid Mechanics
• Cavitation Phenomena
• Multiphase Flow
• +۳ مورد دیگر

Joseph Katz is the William F. Ward Distinguished Professor of Mechanical Engineering at Johns Hopkins University's Whiting School of Engineering and a member of the National Academy of Engineering. His research focuses on experimental fluid mechanics, multiphase flow, cavitation phenomena, and advanced optical diagnostics. He directs the Laboratory for Experimental Fluid Dynamics and co-founded the Johns Hopkins Center for Environmental and Applied Fluid Mechanics. Key research areas include: - Turbulent boundary layers and compliant wall interactions - Cavitation dynamics in turbomachinery - Environmental fluid dynamics (oil spills, oceanic flows) - Medical imaging applications of fluid mechanics - Turbomachinery flow control (axial compressors) His work has been funded by agencies including the Office of Naval Research, NSF, NASA, and DOE. Over 150+ journal papers, 220+ conference papers, and 7 patents reflect his prolific output. Notable awards include the ASME Fluids Engineering Award and fellowships from ASME and APS. Key Contributions: - Developed novel optical diagnostics techniques - Advanced understanding of tip clearance flows in compressors - Studied oil dispersion mechanisms in marine environments - Pioneered holographic PIV for 3D flow visualization

Jonathan Weareمشاهده پروفایل

استاد

• Monte Carlo sampling
• Multiscale analysis
• Randomized numerical linear algebra
• +۲ مورد دیگر

Jonathan Weare is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. He holds affiliations with the Faculty of Arts and Science and the Graduate School of Arts and Science. His academic journey includes roles as an Associate Professor at the University of Chicago (2014–2019) and Assistant Professor (2011–2014), following postdoctoral work as a Courant Instructor at NYU. He earned his Ph.D. in Mathematics from UC Berkeley in 2007. His research focuses on stochastic algorithms and models, with applications in astrophysics, biophysics, computational chemistry, and climate science. Key areas include Monte Carlo methods, rare event simulation, and machine learning-driven scientific analysis. Collaborations with domain experts ensure his work addresses real-world challenges in diverse fields. Recent publications emphasize advancements in trajectory stratification, rare event prediction using machine learning, and efficient algorithms for high-dimensional problems. Notable contributions include the BAD-NEUS framework and AI-based solar system instability predictions. His group’s interdisciplinary approach bridges computational methods with scientific inquiry. Weare has advised numerous students and mentored postdocs, fostering talent in applied mathematics and computational science. His work on Mercury’s orbital dynamics and extreme weather prediction showcases the societal impact of his research. Current projects explore AI applications in weather modeling and rare event analysis, leveraging cutting-edge machine learning techniques. Labs/Teams: His research group at Courant develops stochastic algorithms and collaborates with interdisciplinary teams in computational chemistry, climate science, and astrophysics. Key collaborations include the University of Chicago and Columbia University.

Damian Arellanesمشاهده پروفایل

مدرس

• Theoretical Computer Science
• Algebraic Composition
• Models of High-Level Computation
• +۵ مورد دیگر

Dr. Damian Arellanes is a Lecturer (Assistant Professor) in Computer Science at Lancaster University, UK, affiliated with the Software Engineering Group and Lancaster Centre for Intelligent, Robotic and Autonomous Systems (LIRA). He holds a PhD from The University of Manchester (2020) and a Postgraduate Certificate in Academic Practice from Lancaster University (2023). His research focuses on theoretical foundations of algebraic composition for high-level computation models, including emergent/self-organising systems and software composition. He has contributed to areas such as category theory, control-flow separation, and compositional programming for IoT systems. Education: PhD in Computer Science, University of Manchester (2020) Postgraduate Certificate in Academic Practice, Lancaster University (2023) MSc in Computer Science, supported by CONACYT (2012–2014) BEng in Computer Engineering, supported by PRONABES (2009–2012) Research Interests: Damian’s work emphasizes algebraic semantics, compositional models for software, and theoretical computer science principles. He explores how abstract mathematical frameworks (e.g., category theory) can formalize computational systems and enable scalable IoT solutions. Publications: Damian has published extensively on algebraic composition, IoT systems, and formal methods. Key themes include compositional programming, self-organizing software, and scalable service architectures. Awards: Official Nominator for the VinFuture Prize (2024) Honourable Mention for Most Outstanding Mexican Student in STEM (2021) Nick Sanders Kickstarter Fund (2019) Outstanding Doctoral Paper Award (2019) Best MSc Thesis in AI (2015) Advising & Grants: Damian supervises PhD students, such as Mina Yavari, and actively reviews for journals like IEEE TSC and conferences like TASE. He has secured scholarships and fellowships from CONACYT and the Mexican government. Labs/Teams: Member of LIRA’s Fundamentals Section and the Software Engineering Group at Lancaster University.

Suresh Venkateshمشاهده پروفایل

استادیار

• Metamaterials
• Millimeter-Wave and Terahertz Communication
• Antenna Design
• +۴ مورد دیگر

Suresh Venkatesh is an Assistant Professor in the Department of Electrical and Computer Engineering at North Carolina State University. He previously served as a postdoctoral research associate at Princeton University (2018–2022) and earned his Ph.D. in Electrical Engineering from the University of Utah in 2017. His academic journey also includes a Master's degree in Electrical Engineering from NC State in 2010. Education: Ph.D. in Electrical Engineering, University of Utah, 2017 Master's in Electrical Engineering, North Carolina State University, 2010 Research Interests: His work focuses on metamaterials and surfaces at GHz-THz frequencies, millimeter-wave phased arrays, and innovative applications in 5G/6G communication systems. Key areas include antenna design, physical layer security, advanced electromagnetic simulations, and reconfigurable systems using CMOS integration. He explores origami-based platforms for adaptive RF imaging and employs spatio-temporal modulation techniques to enhance wireless security and efficiency. Publications Trends: Recent work emphasizes mmWave and THz communication, with a focus on reconfigurable intelligent surfaces, secure low-latency links, and CMOS-based designs for direct detection receivers and cytometers. His research bridges theoretical concepts with experimental validation, particularly in wavefront manipulation and sparse imaging techniques. Awards and Honors: Mistletoe Research Fellowship (2021) Advising and Grants: Venkatesh contributes to research teams like the NC State 6GNC initiative, which spans 6G technologies. He actively organizes conferences such as the World Microwave Congress 2024 as TPC Co-Chair and participates in IEEE technical committees. His grants and collaborations drive advancements in metamaterials, secure wireless systems, and CMOS-integrated solutions. Labs and Teams: He leads efforts in the NC State ECE Department, focusing on labs involving reconfigurable antennas, computational imaging, and integrated systems. His work intersects with the 6GNC team to develop future communication technologies and secure mmWave/THz systems.

Archishman Boseمشاهده پروفایل

مدرس

• Biochemical Engineering
• Biopharmaceuticals
• Process Design and Simulation
• +۹ مورد دیگر

Dr. Archishman Bose is an Eli Lilly Lecturer in Process and Chemical Engineering at University College Cork (UCC), Ireland. He serves as a Principal Investigator (PI) in the Circular Economy, Energy, and Environmental Systems (CEEES) Research Group, part of MaREI, the SFI research centre for energy, climate, and marine. He is currently leading three nationally funded research projects on microalgal biogas upgrading, biochar applications, and sustainable processing of end-of-life tyres, with total grants exceeding €1 million. As a programme director, he oversees the Part-Time MEngSc Pharmaceutical & Biopharmaceutical Engineering and the Full-Time MEngSc Engineering in Pharmaceutical and Biopharmaceutical Systems. Education: Bachelor of Engineering (Mechanical Engineering) from Jadavpur University, 2014 Double Masters in Sustainable Energy Engineering (KTH Royal Institute of Technology, 2018) and Energy and Nuclear Engineering (Politecnico di Torino, 2018) PhD in Energy Engineering (University College Cork, 2022) focused on Photosynthetic Biogas Upgrading, co-funded by SFI and Gas Networks Ireland Research interests span biochemical engineering, biopharmaceuticals, carbon capture and utilization, circular bioeconomy systems, and techno-economic analysis. His work emphasizes decarbonization of industrial processes, microalgae biorefineries, and sustainable waste-to-resource systems. Recent publications highlight advancements in anaerobic digestion, photobioreactor design, and metabolic pathway engineering for environmental applications. His funded projects include CABBBIE (SEAI/DAFM, €616k), EMERGE (SFI, €206k), and EPA-funded tyre processing research. Advising and grants: He has supervised 26 MSc students and co-supervised 5 PhD candidates (including one primary role) since joining UCC. Additional supervisions are planned from July 2025. Teaching includes modules on process design, pharmaceutical validation, and separation technologies, with current roles as year tutor and module coordinator. Labs/teams: Leading research in CEEES at MaREI, collaborating with Prof. Jerry D. Murphy, Dr. David Wall, and others in interdisciplinary circular economy and energy systems.

Timothy Jacobsمشاهده پروفایل

استاد

• Internal Combustion Engines
• Low-Temperature Combustion
• Alternative Fuels
• +۱ مورد دیگر

Timothy Jacobs is Professor and Head of Multidisciplinary Engineering at Texas A&M University, with joint appointment in Mechanical Engineering. His research advances combustion science, emission control, and alternative fuel applications. Education: Ph.D. Mechanical Engineering, University of Michigan (2005) M.S. Mechanical Engineering, University of Michigan (2002) B.S.E. Mechanical Engineering, University of Michigan (1999) Research focuses on fundamental combustion processes in natural gas engines, developing low-temperature combustion strategies and aftertreatment integration. Recent work optimizes prechamber ignition systems for large-bore engines and hydrogen production via piston reactors. Experimental diagnostics characterize cycle variability, unburned emissions, and flame dynamics. Publications demonstrate expertise in combustion modeling, engine control algorithms, and emission formation mechanisms. Applied research supports decarbonization of power generation and marine propulsion. Awards recognize teaching excellence and research leadership, including ASME Fellowship and university professorships. Secures funding for engine technology development from federal agencies and industry partners.

Tianyu Guanمشاهده پروفایل

استادیار

• Sports Analytics
• Machine Learning
• Functional Data Analysis
• +۶ مورد دیگر

Tianyu Guan is an Assistant Professor in the Department of Mathematics and Statistics at York University, Faculty of Science. He previously served as an Assistant Professor at Brock University and joined York University in 2024. He holds a PhD in Statistics from Simon Fraser University (2020), an MSc in Actuarial Science from the same institution (2014), and a BSc in Statistics from Jilin University (2011). PhD in Statistics, Simon Fraser University, 2020 MSc in Actuarial Science, Simon Fraser University, 2014 BSc in Statistics, Jilin University, 2011 His research centers on sports analytics, functional data analysis, and nonparametric statistics, with strong applications in machine learning and data science. He applies statistical methodologies to understand sports performance, player behavior, and game dynamics. His work also extends to theoretical developments in sparse modeling and functional regression. The recent publications highlight a clear trend toward integrating advanced statistical techniques with real-world sports and entertainment data. His work combines functional data analysis, machine learning, and probabilistic modeling to extract insights from complex longitudinal and high-dimensional datasets. Topics span soccer, rugby, football, and movie reviews, demonstrating interdisciplinary reach. While no formal scientific awards are listed in the provided text, his publications in high-impact journals such as Annals of Applied Statistics and Statistics and Computing reflect strong academic recognition. Tianyu Guan actively advises multiple graduate students at both MSc and PhD levels, primarily at Brock and Simon Fraser Universities. His teaching portfolio includes advanced courses in nonparametric statistics, sampling theory, and experimental design at the undergraduate and graduate levels. He has not received external grant information in the provided text, but his research output suggests active engagement in funded or independent research projects. He leads methodological and applied research in sports analytics, often co-supervising students with colleagues across institutions. His lab or research group appears focused on developing and applying statistical tools for performance analysis and decision-making in sports, supported by computational implementations such as the R package ngr .

Ruben Loaiza Mayaمشاهده پروفایل

دانشیار

• Copula Modelling
• Bayesian Estimation Methods
• Time Series Analysis
• +۴ مورد دیگر

Ruben Loaiza-Maya is an Associate Professor (Research) in the Department of Econometrics and Business Statistics at Monash University. He holds a PhD in Econometrics from the University of Melbourne and an undergraduate degree in Economics from Universidad Nacional de Colombia (Medellin). His research focuses on Copula Modelling, Bayesian Estimation Methods, Time Series Analysis, and Macroeconomic/Financial Forecasting. Key contributions include advancements in variational inference, state space models, and robust forecasting techniques under model misspecification. He leads the active project 'Variational Inference for Intractable and Misspecified State Space Models' (2023–2026), funded as a Primary Chief Investigator. His work contributes to UN Sustainable Development Goals through methodological advancements in economic and financial analysis. Recent research emphasizes scalable Bayesian methods, hybrid variational approaches, and efficient computational techniques for high-dimensional models. Publications span prestigious journals like the International Journal of Forecasting, Journal of Econometrics, and Journal of Business and Economic Statistics. Notable collaborations include studies on copula-based time series forecasting and robust approximate Bayesian computation. His work bridges theoretical econometrics with practical applications in risk management and macroeconomic policy.

Eetu Mäkeläمشاهده پروفایل

استاد

• Digital Humanities
• Computational History
• Text Reuse Analysis
• +۳ مورد دیگر

Eetu Mäkelä is a Professor in Digital Humanities at the University of Helsinki, affiliated with the Helsinki Institute for Social Sciences and Humanities (HSSH). He holds a Doctor of Science in Computer Science and a Title of Docent in Computer Science. He supervises doctoral programs in History and Cultural Heritage, and Theology and Religious Studies. His research focuses on computational methods applied to humanities, including text reuse analysis, historical discourse studies, and digital cultural heritage. He leads the Helsinki Computational History Group (COMHIS) and participates in projects like CASCADE (computational semantic change analysis) and HPC-HD (high-performance computing for historical discourse analysis). Key research areas include computational analysis of historical texts, formulaic language in oral poetry, and linked open data applications in cultural heritage. Notable projects involve developing digital infrastructures for Finnic oral poetry and analyzing WWII data through linked open systems. Awards include the Best Paper Award at DHN 2020 and the Open Data Prize for the WarSampo system. Projects: CASCADE (EU Horizon Europe), HPC-HD (Academy of Finland), COMHIS (ongoing since 2018) Supervision: Doctoral programs in History, Cultural Heritage, and Theology Labs/Teams: Helsinki Computational History Group (COMHIS), leader of digital humanities initiatives