جست‌وجوی استاد و پژوهشگر

• Requirements Engineering
• Conceptual Modeling
• Software Engineering
• +۴ مورد دیگر

Maria Dolors Costal Costa is an Associate Professor in the Department of Service and Information Systems Engineering at the Facultat d'Informàtica de Barcelona, Universitat Politècnica de Catalunya (UPC). She is a key member of the GESSI and inSSIDE research groups, focusing on software and service engineering. Her research interests include: Requirements Engineering Conceptual Modeling Model-Driven Development Non-Functional Requirements Open Source Software Ecosystems Goal-Oriented Requirements Engineering Her recent publications (2019–2024) reflect a strong focus on conceptual modeling, requirements engineering, and software quality, particularly in agile and ML-based systems. She frequently contributes to top-tier conferences like ER and CAiSE, and her work integrates empirical methods with modeling frameworks. She has received recognition for her research, including the Best Paper Award at CIbSE 2021. Her involvement in numerous competitive R&D+i projects demonstrates sustained research funding and leadership. She actively mentors and collaborates with researchers such as Javier Franch and Cristina Gómez. Her work is supported by participation in EU and national research initiatives like HORIZON 2020 and Plan Estatal de Investigación. She is involved in several research labs and teams, including: GESSI - Group of Software and Service Engineering inSSIDE - integrated Software, Services, Information and Data Engineering inLab FIB

Anurag Purwarمشاهده پروفایل

دانشیار

• Robotics Design
• Kinematic Analysis
• Machine Learning in Engineering
• +۳ مورد دیگر

Dr. Anurag Purwar is an Associate Professor of Mechanical Engineering at Stony Brook University, directing the Computer-Aided Design and Innovation Lab and serving as PI for NSF I-Corps. He holds a Ph.D. from Stony Brook (2005) and a B.Tech. from IIT Kanpur (1995). His research merges rigid body kinematics with machine learning for mechanism and robot design, yielding 107+ peer-reviewed publications and patents licensed to industry. Key projects include the sit-to-stand walker assistive device (SAE Top 100 Award) and MotionGen software tools. Education: Ph.D., Stony Brook University (2005); B.Tech., IIT Kanpur (1995) Awards: A.T. Yang Award (2017), SAE Top 100 Award (2016), ASEE Distinguished Teaching Award (2021) Leadership: Program Chair (ASME 2014), Conference Co-Chair (IDETC 2016), NAI Senior Member Research focuses on machine learning-driven design of mechanisms, robotics, and assistive technologies. His labs develop algorithms for path synthesis, generative design, and kinematic analysis. He actively commercializes innovations through industry partnerships and has spun off startups like MotionGen.io.

Erik Brunvandمشاهده پروفایل

استاد

• Computer Architecture
• VLSI Systems
• Asynchronous Circuits
• +۳ مورد دیگر

Erik Brunvand is a Professor at the School of Computing , University of Utah, and holds an Adjunct Professor position in the Department of Electrical and Computer Engineering. He was a University Professor from 2014–2016 and is currently on leave at the National Science Foundation (CISE/CNS division) (Fall 2019–2021). His research focuses on computer architecture, VLSI systems, asynchronous circuits, and graphics processing, particularly GPU architectures for ray tracing. Teaching includes courses like Digital VLSI Design , Embedded Systems and Kinetic Art , and interdisciplinary classes like Making Noise: Sound Art and Digital Media . He has organized the ASYNC international symposium series and contributed to projects such as TRaX (ray tracing architecture) and ACK (asynchronous design framework). Grants include NSF awards for GPU architectures, ray tracing applications, and microengine-based control systems. His work spans hardware design, sustainable computing, and arts/technology collaborations, including kinetic art installations and educational initiatives like circuit bending.

• Formal Methods
• Satisfiability (SAT)
• Satisfiability Modulo Theories (SMT)
• +۱۱ مورد دیگر

Enric Rodríguez Carbonell is a faculty member at the Department of Computer Sciences within the Faculty of Computer Science at Universitat Politècnica de Catalunya (UPC). He is a key member of the LOGPROG - Lògica i Programació research group, focusing on formal methods, automated reasoning, and combinatorial optimization. Research Interests: His work centers on satisfiability (SAT), satisfiability modulo theories (SMT), and their applications in program verification, constraint solving, and optimization. He investigates techniques such as conflict-driven learning, invariant generation, and Max-SMT for proving termination and safety. His research bridges theoretical foundations with practical applications in software analysis and industrial problem-solving. Publication Trends: His recent publications (2020–2024) show a sustained focus on enhancing SAT and SMT solvers, particularly in pseudo-Boolean reasoning, integer linear programming, and multi-conflict analysis. Earlier works established contributions in non-linear arithmetic, termination proofs, and efficient encodings for cardinality constraints, reflecting a long-term commitment to foundational and applied aspects of automated reasoning. Scientific Awards: Best student paper award at SAT 2024 Advising and Grants: Rodríguez Carbonell has contributed to multiple competitive R+D+i projects under Spain’s State Research Plans, indicating active grant involvement. He has co-authored doctoral theses and educational initiatives like Jutge.org, demonstrating engagement in academic supervision and pedagogical innovation. Labs and Teams: He is a core researcher in the LOGPROG group at UPC, which specializes in logic and programming, with strong collaborations across formal methods, verification, and constraint technologies.

• Computer Science
• formal methods
• Security
• +۶ مورد دیگر

Marc Frappier is a full professor at Université de Sherbrooke with over 25 years of academic experience. His research focuses on formal methods , security , and software synthesis . He holds a PhD from the University of Ottawa (1995), a Master's (1990) and Bachelor's (1986) from Université de Sherbrooke. Research Areas: Formal specification/verification, intrusion detection, access control, ASTD/TASTD modeling, automotive systems Grants: NSERC, MITACS, PSEPC, CSE Canada, Natural Resources Canada (total over $2.5M) Selected Publications highlight formal methods in automotive systems, security policy verification, and real-time modeling. His work spans cross-domain collaborations including healthcare, industrial systems, and cybersecurity. Scientific Awards: Distinguished Service Award 2019 (Cs-Can | Info-Can) Committee Roles : Program Committee member for 15+ conferences (2012-2021), including ABZ, ICFEM, HASE, and RAMiCS.

Joanna Endter-Wadaمشاهده پروفایل

استاد

• Water Policy
• Natural Resource Management
• Human Dimensions of Environmental Change
• +۳ مورد دیگر

Joanna Endter-Wada serves as Professor of Natural Resource Policy and Social Science in the Department of Environment and Society at Utah State University. She leads the WaterMAPS™ program and co-directs the National Environmental Policy Act (NEPA) Graduate Certificate Program, focusing on interdisciplinary approaches to natural resource governance and human-environment interactions in arid regions. Her educational foundation includes: PhD in Social Ecology from University of California at Irvine MS in Planning from University of California at Irvine Dr. Endter-Wada's research examines water policy frameworks and human dimensions of natural resource use through multiple lenses: Great Salt Lake ecosystem management and policy development Urban landscape water conservation strategies and behavioral drivers Human adaptation to drought and climate change impacts Wetland protection mechanisms in water-scarce environments Social-ecological system interactions in arid landscapes Analysis of her recent publications (2020-2025) reveals intensifying focus on Great Salt Lake policy documentation for legislative action (2023-2025), integration of land-water planning for community health, and innovative water management strategies like banking systems. Her work consistently bridges social science methodologies with practical water conservation applications in western U.S. contexts. No specific scientific awards are documented in the provided materials. Dr. Endter-Wada mentors students through the NEPA Graduate Certificate Program while directing interdisciplinary research initiatives. Her WaterMAPS™ program develops analytical tools for municipal water use assessment, and she co-directs federal policy training that prepares students for environmental regulatory careers. Current projects address water security challenges through stakeholder-engaged approaches across Utah's diverse landscapes. She directs the WaterMAPS™ program which creates software for urban water management analysis and co-directs the NEPA Graduate Certificate Program that trains future environmental policy professionals. These initiatives operate within Utah State University's broader ecosystem of water research centers focused on arid region sustainability.

R. Iris Baharمشاهده پروفایل

استاد

• Computer Architecture
• Low Power Design
• Machine Learning
• +۵ مورد دیگر

R. Iris Bahar is a Professor of Computer Science and Engineering at Colorado School of Mines, where she serves as Department Head of Computer Science since 2022. Previously, she held dual appointments as Professor of Engineering and Computer Science at Brown University for 26 years. Her research focuses on energy-efficient and reliable computing across system-level to device-level domains, with applications in near-data processing, robust machine learning for robotics, and noise-immune nanoscale circuit design. Research Interests include computer architecture, low-power design, and robotic system optimization. She pioneers hybrid generative-discriminative inference techniques for robot scene perception, achieving 40% accuracy improvements in occluded environments through FPGA-based Monte-Carlo sampling implementations. Her work on subthreshold CMOS noise modeling provides 1000x simulation speedups over SPICE-based methods. Near-Data Processing Architectures Approximate Computing Hardware/Software Co-design Nanoscale Noise Modeling Robust AI for Robotics Scientific Awards include the 2024 IEEE Undergraduate Teaching Award, 2019 Marie R. Pistilli Women in Engineering Achievement Award, and NSF CAREER award. She is an IEEE Fellow and ACM Distinguished Scientist. Funded Research spans NSF grants on thermal noise effects ($360k), durable data structures ($500k), and Brown SEED grants for autonomous robotics. Her lab trains 12+ students in hardware acceleration and probabilistic computing.

James Morizioمشاهده پروفایل

استاد مدعو

• Analog CMOS Microelectronics
• Neural Interfaces
• Acoustofluidics
• +۴ مورد دیگر

James Morizio serves as an Adjunct Professor in the Department of Electrical and Computer Engineering at Duke University, leveraging 35+ years of expertise in analog CMOS microelectronics for biomedical applications. His research bridges electrical engineering with neuroscience through disruptive sensor interface technologies for neural recording/stimulation and ultrasonic microfluidics. His educational background includes a Ph.D. in Electrical Engineering from Duke University (1995) M.S. in Electrical Engineering from University of Colorado, Boulder (1984) B.S. in Electrical Engineering from Virginia Polytechnic Institute and State University (1982) Morizio's research focuses on developing high-performance neural interfaces and acoustofluidic systems. Key areas include wireless neural instrumentation for closed-loop electrophysiology, CMOS-based ultrasonic transducers for microfluidic manipulation, and low-power VLSI design for implantable devices. His work emphasizes translating microelectronics innovations into biomedical solutions for neuroscience and diagnostics. His publication portfolio demonstrates consistent contributions to neural engineering and microfluidics, with recent trends showing increased focus on acoustofluidic diagnostics (e.g., AIMDx chip) and osseointegrated neural interfaces for prosthetic control. The research spans fundamental circuit design to translational applications in cancer metabolism and neuroprosthetics. Scientific recognition includes 15-year service award from Triangle BioSystems International/Harvard Bioscience Inc. (2016) Current research is supported by major grants including Neuro-CROWN (ultra-flexible electrode arrays), digital acoustofluidic systems for biomedical automation, and osseointegrated neural interfaces for prosthetic control. His teaching portfolio spans advanced VLSI design and special topics courses, though specific advising roles are not documented. Collaborative work involves interdisciplinary teams in neuroscience and biomedical engineering, particularly through partnerships with Triangle BioSystems International and translational projects using ovine models for neural interface validation.

• Digital Health
• Design Science Research
• Human-Computer Interaction
• +۷ مورد دیگر

David Walter is a researcher at the Department of Information Systems and Business Modeling , University of Hildesheim, focusing on digital health, design science research, and socio-technical systems. He holds a Master's degree in Business Information Systems from the University of Hildesheim (2021) and a Bachelor's in the same field (2019). Education : Master's (2021): Business Information Systems, University of Hildesheim Bachelor's (2019): Business Information Systems, University of Hildesheim His research revolves around informal caregiving support applications , technostress management , and unlearning support systems , with notable contributions to AI readiness assessments and anthropomorphic conversational agents. Recent work includes systematic analysis of informal care apps' real-world features and frameworks for unlearning ineffective knowledge structures. Key scientific awards include the 2023 Best Research-in-Progress Paper at WI23, 2022 Best Prototype at DESRIST, and the 2022 Sebastian Thrun Prize for computer science excellence. His publications span conferences like ECIS, WI, and HCI International, addressing digital health, agile unlearning, and technostress in education.

• Automata Theory
• Formal Verification
• Logic in Computer Science
• +۳ مورد دیگر

Christof Löding , currently an Adjunct Professor at the Lehrstuhl für Logik und Theorie diskreter Systeme (Informatik 7) department of RWTH Aachen University , is a leading researcher in Automata Theory , Formal Verification , and Logic in Computer Science . His work bridges theoretical foundations with practical applications in software verification, automata minimization, and game theory. Research Interests include automata theory, formal verification, logic, tree automata, game theory, and computational models. Publications span topics like Finite-valued Streaming String Transducers , Deterministic Parity Automata , and Stochastic Game Strategies . Collaborations with researchers like Emmanuel Filiot , Sarah Winter , and León Bohn highlight his contributions to automata and verification. Email : loeding@informatik.rwth-aachen.de He has actively published in venues such as ICALP , LICS , and STACS , focusing on deterministic automata, transducers, and logic-based computational systems. His work on Hyperlogic for Strategies in Stochastic Games (2025) and Minimal History-Deterministic Automata (2025) showcases his ongoing influence in formal methods and automata theory.

• Evidence Synthesis
• Systematic Review Methodology
• Health Informatics
• +۳ مورد دیگر

Ian Shemilt is an Associate Professor at the University College London (UCL) , affiliated with the EPPI-Centre within the Institute of Education . As an Associate Director of the EPPI Centre , he contributes to advancing evidence synthesis methods and co-leads key research initiatives. Education : BA (Hons) in Philosophy from the University of East Anglia. Collaborations : Cochrane Collaboration, Campbell Collaboration, GRADE Working Group, and International Collaboration for Automation of Systematic Reviews (ICASR). Research interests include developing and applying automation tools for systematic reviews, transitioning evidence synthesis workflows from document-based to dataset-driven processes, and enabling computable, living evidence syntheses. His work leverages technologies like OpenAlex and large language models to enhance efficiency in health and social care evidence production. The articles highlight his focus on systematic review methodology , automated study identification , and health equity analysis in public health interventions. Projects span living evidence syntheses , machine learning applications , and GRADE framework extensions for policy decision-making. Key contributions include: Developing EPPI-Reviewer software tools for OpenAlex integration. Co-investigating Microsoft Academic Graph for automated study identification. Advancing living systematic reviews through dynamic datasets. Collaborating on ICASR to automate evidence synthesis workflows. His affiliations span multiple institutions, including University of East Anglia (Senior Research Associate since 2005) and University of Cambridge (2011–2015). He has held leadership roles in the Campbell & Cochrane Economics Methods Group and GRADE Working Group .

• 3D printing
• Materials science
• Electromagnetic compatibility testing
• +۶ مورد دیگر

Pererik Andreasson is a Lecturer at the Academy of Information Technology , Halmstad University. His research focuses on 3D printing, materials science, electromagnetic compatibility testing, and wireless communication. Key contributions include optimizing 3D-printed radar lenses, advancing phase-change material characterization via femtosecond x-ray diffraction, pioneering augmented reality methods for electromagnetic field visualization, and developing substrate integrated waveguide antennas for IoT devices. 3D printing of optical components Dynamic processes in phase-change materials Augmented reality for electromagnetic testing IoT antenna design His recent work on frequency-adjustable SIW antennas (2024) and AR-based EMC visualization (2021) demonstrates cross-disciplinary innovation. While no scientific awards are documented, his 15+ publications since 2007 highlight sustained expertise in material science and wireless technologies.

Yuying Xieمشاهده پروفایل

دانشیار

• Single-cell data analyses
• Spatial data analysis
• statistical Machine Learning
• +۴ مورد دیگر

Yuying Xie is an Associate Professor holding dual appointments in the Department of Computational Mathematics, Science and Engineering and the Department of Statistics & Probability at Michigan State University. Her research bridges statistical theory, machine learning innovation, and biological discovery, with a focus on developing computational frameworks for high-dimensional biological data analysis. Education: B.S. in Biology, Fudan University, China (2005) Ph.D. in Genetics and Molecular Biology, University of North Carolina at Chapel Hill (2010) Ph.D. in Statistics, University of North Carolina at Chapel Hill (2015) Research Interests: Dr. Xie pioneers methodologies in single-cell data analyses , spatial transcriptomics , and statistical machine learning for biological applications. Her work addresses critical challenges in high-dimensional data analysis through graphical models and QTL/eQTL mapping , with emphasis on biological interpretability and computational efficiency. Current projects integrate deep learning with immunology and cancer biology to decode complex disease mechanisms. Recent Publications: Her 2023-2025 output reveals a strategic focus on transparent single-cell analysis tools (DANCE 2.0), tumor microenvironment modeling (MARVEL, SpatialCTD), and immune-microbiome interactions in disease. Key themes include graph neural networks for spatial data, generative models for biological imaging, and mechanistic studies of immune responses in Crohn's disease, food allergy, and cancer immunology, demonstrating consistent innovation at the statistics-biology interface. Academic Service: Dr. Xie contributes to computational biology through software development (DANCE framework) and large-scale dataset curation (SpatialCTD), enabling reproducible research in immuno-oncology and single-cell genomics.

Michael Williamsمشاهده پروفایل

پژوهشگر ارشد

• Gravitational Wave Physics
• Neutron Stars
• Black Holes
• +۳ مورد دیگر

Dr. Michael Williams is a Research Fellow at the Institute of Cosmology & Gravitation under the Faculty of Technology , University of Portsmouth. His work focuses on gravitational wave physics, neutron star dynamics, and black hole binaries through collaborations with LIGO, Virgo, and KAGRA detector networks. Active in gravitational wave detection and multi-messenger astronomy Developing AI algorithms for telescope targeting and signal processing Recipient of the IOP Trusted Reviewer status (2025) His recent research includes premerger characterization of black hole binaries , continuous wave searches from pulsars , and gravitational wave-FRB counterpart detection . He contributes to open-source tools like nessai and bayesbeat , with 25 datasets released. Williams participates in conferences like the European AI for Fundamental Physics Conference and workshops on milli-hertz gravitational wave astrophysics. Key collaborations: LIGO, Virgo, KAGRA, GEO600 Technical expertise: matched filtering , Bayesian inference , normalizing flows

James Floryمشاهده پروفایل

دانشیار

• Pharmacoepidemiology
• Diabetes Management
• Clinical Trials
• +۳ مورد دیگر

James Flory is an Associate Professor of Population Health Sciences at Weill Cornell Medical College , Cornell University. With an MD and MSCE from the University of Pennsylvania (2009) and a BA from Columbia University (2002), he specializes in pharmacoepidemiology and clinical research related to diabetes management, drug safety, and healthcare policy. Education: M.D., University of Pennsylvania School of Medicine, 2009 M.S.C.E., University of Pennsylvania School of Medicine, 2009 B.A., Columbia University, 2002 His research focuses on the intersection of diabetes pharmacology , cardiovascular risk , and health services research . He has contributed extensively to understanding drug safety (e.g., sulfonylureas, SGLT2 inhibitors, TRK inhibitors), medication adherence , and clinical decision-making in diabetes and oncology settings. His methodological work includes instrumental variable analysis , pragmatic trial design , and real-world data validation . James Flory's recent publications examine temperature-related diabetes complications , AI in clinical decision support , and policy impacts on medication utilization . His work combines epidemiological methods with health informatics to address critical questions in diabetic care , drug safety surveillance , and health equity .