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Valeria PannunzioView profile

Researcher

• Health Systems Design
• Digital Health
• Remote Patient Monitoring
• +3 more

Dr. Valeria Pannunzio is a researcher affiliated with Delft University of Technology's Industrial Design Engineering department under the Design, Organisation and Strategy group. She focuses on health systems design, digital health innovation, and systemic resilience. Her work bridges healthcare technology, implementation science, and stakeholder collaboration, with projects like the CardioLab exploring smart technologies for cardiovascular disease management. Teaches courses on technology strategy and design methodologies Board member in healthcare committees since 2020 Adjunct faculty at CentraleSupelec (2025-2026) Her research emphasizes remote patient monitoring, system resilience, and interdisciplinary approaches to healthcare challenges. Recent studies include exploring indicators for health systems resilience and designing family-centered telehealth interventions. Recognized with top awards at the 2024 International Design Conference, including an Excellence in Design Science Paper Award and a Reviewer's Favourite Award for impactful contributions to health systems design. Active in collaborative projects such as the Knowledge Exchange Event for Implementation Scientists and leading the CardioLab initiative to reduce cardiovascular disease burdens through smart technologies.

• Cloud Computing
• Big Data Pipelines
• Machine Learning
• +4 more

Mihhail Matskin is a Professor at the Royal Institute of Technology (KTH) within the Department of Software Logic & Computer Systems. He specializes in cloud computing, big data pipelines, machine learning, and distributed systems. His work emphasizes optimizing cloud resource allocation, developing graph-based cost models, and advancing AI-driven systems like SQL recommendation engines and relation extraction frameworks. He actively contributes to KTH's educational mission through roles as examiner and course manager in advanced computer science and engineering courses, including Distributed AI, Cloud Storage Optimization, and Big Data Workflow Design. His research spans over two decades, focusing on scalable data management solutions, edge computing applications in healthcare, and semantic analysis of social media. Notable projects include the DataCloud initiative for big data pipeline orchestration and the DEF-PIPE DSL visualization framework. Matskin’s work bridges theoretical advancements with practical implementations, addressing challenges in reproducibility of LLM-based systems, containerized edge computing, and constraint programming for robotics. His academic contributions include pioneering studies on cloud cost modeling, rule-based storage tiering, and contrastive learning for NER tasks. He has advised numerous advanced-level degree projects across computer science, embedded systems, and communication technologies. Matskin’s lab focuses on innovative solutions at the intersection of distributed systems, AI, and data engineering.

Rianne Appel-MeulenbroekView profile

Associate Professor

• Corporate Real Estate
• Workplace Strategy
• Hybrid Work Environments
• +4 more

Rianne Appel-Meulenbroek is an Associate Professor of Corporate Real Estate and Workplaces at Eindhoven University of Technology's Department of the Built Environment. She researches corporate real estate as a strategic resource, focusing on: 1) Hybrid workplace management across corporate offices, co-working spaces, and home environments, and 2) How design choices impact employee health, productivity, and innovation. She employs innovative methods including choice experiments, experience sampling, and sensor-based measurements. With an MSc in Real Estate Management, Appel-Meulenbroek has extensive industry experience as a consultant for Buck Consultants International and DHV. She chairs the Transdisciplinary Workplace Research (TWR) network and co-edits the academic book series Transdisciplinary Workplace Research & Management. Research Focus: Her work addresses critical workplace challenges: Strategic management of hybrid work environments Impact of physical workspace on mental health and cognition Location choice behaviors and workplace preferences Knowledge-sharing ecosystems in science parks Business case development for healthy offices Recent articles demonstrate strong emphasis on post-pandemic workplace strategies, mental health considerations in office design, and measurement methodologies for workspace effectiveness. Her studies frequently integrate perspectives from real estate, psychology, and organizational behavior. Awards and Leadership: Multiple best paper awards from EuroFM and Healthy Buildings conferences Editor of the Journal of Corporate Real Estate Board member for Smart Workplace and Center for Humans & Technology Research leadership in multinational projects on workplace mental health She supervises graduate research on workplace satisfaction metrics and hybrid work models. Her Erasmus+ Space project develops frameworks for evaluating workspace effectiveness across European contexts.

• Healthcare Operations
• Operations Research
• Queueing Theory
• +3 more

Rene Bekker is an Associate Professor in the Department of Mathematics at the Vrije Universiteit Amsterdam (Faculty of Science). His research focuses on healthcare operations, stochastic modeling, and optimization techniques applied to healthcare logistics and scheduling. He actively collaborates with Tonos Care as a partner since 2019, bridging academic research with practical healthcare challenges. Key research interests include queueing theory, appointment scheduling systems, home healthcare routing, and capacity planning in nursing homes. Notable contributions involve integrating queueing-based approaches with optimization algorithms to address complex healthcare operational problems. Recent work emphasizes adaptive strategies for resource allocation and staffing in multitasking service systems. His publications often explore the intersection of mathematical modeling and real-world healthcare systems, addressing issues like patient preference allocation, reduced waiting times, and efficient staff scheduling. While his profile does not explicitly mention awards, his extensive contributions to healthcare operations research are evident through over 45 peer-reviewed articles and supervised PhD theses. Bekker’s teaching spans courses such as Applied Stochastic Modeling and Stochastic Modelling, reflecting his expertise in connecting theoretical frameworks with practical applications. Ancillary activities and collaborations highlight his commitment to translating academic research into actionable solutions for healthcare institutions.

• Distributed Systems
• Cloud Computing
• Big Data Processing
• +4 more

Ignacio Martín Llorente is a Full Professor (Catedrático) at the Universidad Complutense de Madrid (UCM), leading the Distributed Systems Architecture Research Group and the Data-intensive Cloud Lab . He holds visiting positions at Harvard University as a Visiting Professor in the John A. Paulson School of Engineering and Applied Sciences (SEAS) and as a Visiting Scholar in FAS Research Computing. He earned a Ph.D. in Computer Science from UCM and an Executive MBA from IE Business School. His research focuses on distributed systems, cloud computing architectures, big data processing, edge computing, and federated networking. He pioneered projects like OpenNebula (a cloud management system) and contributed to EU initiatives such as RESERVOIR (cloud virtualization), StratusLab (grid-to-cloud integration), and BEACON (federated networking). He has authored over 169 publications and serves on editorial boards for IEEE Transactions on Cloud Computing and Journal of Grid Computing . He has secured over €100M in EU grants, leading 10 major projects. His work emphasizes transferring research into open-source technologies and commercial products. He advises OpenNebula Systems and has been a consultant for governments and companies like Microsoft. His teaching spans 67 courses in distributed systems, cloud computing, and high-performance computing.

• Infrastructure Management
• Transportation Engineering
• Optimization Algorithms
• +2 more

Josia Meier serves as a Lecturer at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering, specializing in optimization methodologies for transportation infrastructure systems. His work bridges theoretical algorithm development with practical applications in road and railway network management. Education: Master's degree in Spatial Development and Infrastructure Systems (ETH Zurich) Bachelor's degree in Civil Engineering (ETH Zurich) Research Focus: Meier develops computational frameworks for optimizing infrastructure intervention programs, particularly examining how algorithmic solutions can enhance maintenance scheduling and resource allocation in transportation networks. His thesis demonstrated practical implementation for Swiss regional railways using custom optimization tools from ETH's Chair of Infrastructure Management. Professional Background: Prior to academic work, he completed vocational training as a Civil CAD designer. Recent activity includes Assistant System Engineering roles in 2023, indicating ongoing industry engagement alongside academic duties. Affiliations: Based at ETH Zurich's Institute for Construction Management and Infrastructure (IBI) in building HIL F 22.3, Stefano-Franscini-Platz 5, Zurich. Scientific Recognition: No awards or fellowships were documented in the provided materials. Academic Contributions: The available information does not reference student supervision, research grants, or laboratory affiliations. His current research appears focused on translating optimization theory into infrastructure management workflows.

Jason MarsView profile

Professor

• Computer Architecture
• Warehouse-Scale Computing
• Machine Learning Systems
• +3 more

Jason Mars is a Professor at the University of Michigan's Department of Electrical Engineering and Computer Science, leading the Clarity-Lab. His research focuses on cross-layer architectures and runtimes for future computing systems, particularly in warehouse-scale computers. He has pioneered projects like Sirius (an open voice/vision personal assistant), Protean Code (dynamic code transformations), and Adrenaline (tail latency management). His work addresses challenges in energy efficiency, resource allocation, and performance optimization in large-scale systems. Key contributions include architectural designs for AI services, thermal management strategies, and compiler techniques for approximate computing. Mars collaborates with industry leaders like IBM and has advised numerous students who have published at top conferences such as ASPLOS and HPCA. Recent research spans AI ethics, scalable programming models (e.g., Data Spatial Programming), and edge-cloud collaboration frameworks like Neurosurgeon. He has delivered invited talks at Baidu, IBM Watson, and conferences worldwide, emphasizing the societal impact of computing systems.

• Operations Research
• Computational Complexity
• Combinatorial Optimization
• +4 more

Mohammed Fazle Baki is a Professor of Management Science at the Odette School of Business, University of Windsor, where he currently serves as Associate Dean, Programs. Cross-appointed with the Mechanical, Automotive and Materials Engineering (MAME) department, his research focuses on combinatorial optimization, scheduling, and inventory management in manufacturing and healthcare systems. Ph.D. in Operations Management, University of Waterloo (1999) M.B.A. in Business Administration, University of New Brunswick (1995) M.A. in Business Administration, University of Dhaka (1991) B.A. in Civil Engineering, Bangladesh Institute of Technology (1987) His research interests span computational complexity, enumeration algorithms, flexible resource scheduling, and combinatorial optimization in manufacturing contexts. Recent work addresses hybrid additive-subtractive manufacturing planning, sustainable supply chain design, and operating room capacity allocation under uncertainty. Publications emphasize algorithm development for lot sizing, scheduling, and resource optimization problems with practical industry applications. Current research trends demonstrate cross-disciplinary impact across operations research, industrial engineering, and healthcare management. Key journals include European Journal of Operational Research , Health Care Management Science , and IEEE Transactions on Engineering Management . Collaborations extend to engineering and healthcare domains, particularly in public hospital systems optimization. 2017: Best Paper Award (International Conference on Supply Chain and Logistics Engineering) 2012: Odette Research Excellence Honourable Mention 2011: Student-nominated Professor of the Year

• Temporal Data Mining
• Biomedical Decision Support Systems
• Temporal Logics
• +5 more

Pietro Sala is an Associate Professor at the University of Verona , Department of Computer Science. His research intersects Temporal Data Mining , Biomedical Decision Support Systems , and Formal Verification of temporal logic specifications. Key Research Areas: Interval Temporal Logic and Model Checking Temporal BPMN for healthcare processes Data fusion in clinical environments Algorithm design for repetitive task automation Notable Projects: Dioxin impact analysis on cardiovascular development Open-source clinical data warehousing (DW-SAN) Real-time system verification frameworks Teaching: Lecturer for Biomedical Decision Support Systems (Master's) Instructor for Data Mining and Software Engineering courses The articles highlight his work in temporal logic verification (2025), clinical process modeling (2024-2025), and data integration for NLP pipelines (2023). His publications span theoretical computer science conferences (LICS, ICALP) and healthcare informatics journals (ICHI, CBM).

Steve EllerView profile

Lecturer

• AI in Talent Acquisition
• Talent Development and Operations

Steve Eller serves as an Adjunct Instructor at the Paul H. O'Neill School of Public and Environmental Affairs, Indiana University, contributing to academic programs with expertise in human resources technology and operational management. His instructional responsibilities include teaching SPEA 412. His academic credentials are: MBA from Indiana Wesleyan University (1987) BS in Administration from Indiana University (1984) Eller's research examines artificial intelligence and chatbot applications in modernizing talent acquisition workflows, with emphasis on algorithmic efficiency and candidate engagement. He concurrently investigates integrated talent development frameworks covering operational execution in human resources, specifically scheduling optimization and revenue cycle management within organizational talent pipelines, aiming to bridge technological innovation with practical HR implementation. His professional focus remains centered on translating emerging technologies into actionable human capital strategies through academic instruction and applied research.

Paulo FernandesView profile

Professor

• Stochastic Models
• Natural Language Processing
• Computer Science in Multidisciplinary Environments
• +4 more

Paulo Fernandes is a Program Director and Professor of Computer Science at Merrimack College. He holds a Ph.D. in Computer Science from INP Grenoble (France), an M.Sc. and B.Sc. from UFRGS (Brazil). His research focuses on stochastic models, natural language processing, and interdisciplinary applications of computer science. He teaches graduate courses in algorithms, discrete structures, and software systems. Education: Ph.D. (INP Grenoble), M.Sc. & B.Sc. (UFRGS) Teaching: Master’s courses in Algorithms, Systems & Languages, and Discrete Structures His work spans computational linguistics (e.g., PortiLexicon-UD lexical resource), stochastic modeling for software projects, and Markovian analysis in geology and engineering. He has published extensively on topics like HMM fitting, term relevance metrics, and distributed team performance. Key research contributions include: language-independent POS tagging systems, stochastic frameworks for global software development, and dimensionality reduction techniques for event forecasting. He has collaborated on tools such as PEPS and SANGE for stochastic modeling.

Leonardo Bedoya-ValenciaView profile

Researcher

• Operations Research
• Scheduling Algorithms
• Healthcare Logistics
• +4 more

Leonardo Bedoya-Valencia is a researcher affiliated with the Department of Industrial and Manufacturing Engineering at Colorado State University-Pueblo. His work focuses on the intersection of operations research, healthcare logistics, and sustainability in engineering education. His research interests include optimization algorithms for scheduling and resource allocation, simulation modeling for healthcare systems and manufacturing processes, and integrating sustainability principles into engineering curricula. He has contributed to improving emergency department workflows, powder coating facility operations, and renewable energy resource modeling. Bedoya-Valencia has published extensively on topics such as multi-objective home healthcare routing, Taguchi method applications in material science, and blended learning strategies for statistics education. His work emphasizes practical solutions for dynamic environments and educational challenges in STEM fields. Key focus areas: operations research applications, healthcare system analytics, sustainable manufacturing, and curriculum innovation Notable contributions: development of dispatching rules for flexible flow shops and triage process modeling in emergency departments His research bridges theoretical optimization techniques with real-world implementation, particularly in healthcare and sustainable energy sectors.

Bernd SchweibenzView profile

Professor

• Construction Management
• Digitalization in Construction
• Life Cycle Costs
• +3 more

Prof. Bernd Schweibenz is a Professor of Construction Operations and Management at the Department of Civil Engineering, University of Applied Sciences Potsdam. He also serves as an Academic Advisor for Civil Engineering programs and is a member of the Departmental Council. His career includes roles at Biberach University of Applied Sciences (2008–2012) and the Technical University of Munich (1999–2005). He is a certified consulting engineer specializing in construction management, supplementary claims, and organizational consulting. Research focuses on: Optimization of manufacturing and business processes Digitalization in construction management (BIM) Recruitment and personnel development in construction Life cycle cost analysis of buildings Publications span topics like Generation Y workforce expectations, PPP project frameworks, and construction documentation technologies. He actively contributes to industry standards through roles in associations like VDI and VSVI. His consulting practice addresses organizational challenges in the construction sector. Professional memberships include the Association of Consulting Engineers (VBI), Association of German Engineers (VDI), and Research Association for Road and Transport Engineering (FGSV). His career bridges academia with practical expertise in public infrastructure, audit practices, and construction technology.

Chih-Yang TsaiView profile

Professor

• Supply Chain Management
• Operations Research
• Linear and Non-Linear Optimization
• +5 more

Dr. Chih-Yang Tsai is a Professor of Operations and Decision Sciences at the School of Business, SUNY New Paltz. He earned his Ph.D. in Operations Research from New York University's Stern School of Business (1993) and an MBA from Tatung University, Taiwan. With over three decades of academic experience, he has held leadership roles including Associate Dean (2006–2013) and Interim Dean (2013–2014). His research focuses on supply chain management, optimization, and simulation, with publications in journals like Decision Support Systems and Mathematical Programming . He teaches courses such as Operations Management, Decision Modeling, and Managing Operations & IT. Notable awards include the W. Edwards Deming Scholarship (1990) and the SUNY New Paltz School of Business Distinguished Service Award (2010). His applied work includes optimizing marketing budgets for American Express and developing analytical tools for regional businesses. He is an active member of INFORMS and the Decision Sciences Institute.

Ravi MukkamalaView profile

Professor

• Data Security
• Cloud Computing
• Distributed Systems
• +5 more

Ravi Mukkamala is a Professor & Chair in the Department of Computer Science at Old Dominion University . He holds advanced degrees including a Ph.D. in Computer Science (University of Iowa, 1987) and an MBA from Old Dominion University (1993). His research focuses on security, distributed systems, cloud computing, and real-time database systems, with notable contributions to privacy-preserving data management, blockchain applications, and UAV-based healthcare logistics. Education: Ph.D. in Computer Science, University of Iowa, 1987 M.B.A., Old Dominion University, 1993 Other in Computer Systems, Indian Institute of Technology Kanpur, 1978 B.E. in Electronics and Communications, Osmania University, 1976 Research Interests: Dr. Mukkamala’s work spans cybersecurity, blockchain technology, vehicular and UAV systems, distributed databases, and aviation software. He emphasizes practical applications like secure payment systems, privacy-preserving data mining, and automated healthcare delivery via drones. Articles Overview: His recent publications address cutting-edge topics such as blockchain-based healthcare monitoring, UAV logistics for medical supplies, and privacy-preserving machine learning techniques. Earlier work includes foundational studies on distributed databases and real-time systems security. Awards: Best Paper Awards (2008–2009) Phi Kappa Phi and Beta Gamma Sigma memberships Most Inspiring Faculty Member Award (Old Dominion University) Grants & Advising: He has led over 20 grants totaling millions, including projects on airspace systems, IT infrastructure management, and STEM education. His advisory work includes aviation software testing (e.g., TDMS) and coalition-based resource sharing. Labs & Teams: Collaborates with university and industry partners on projects involving cybersecurity, UAV systems, and distributed cloud architectures.