جست‌وجوی استاد و پژوهشگر

Renata Borovica-Gajicمشاهده پروفایل

دانشیار

• Database Systems
• Machine Learning
• Artificial Intelligence
• +۱۲ مورد دیگر

Renata Borovica-Gajic is an Associate Professor in Data Analytics and an ARC DECRA Fellow at the School of Computing and Information Systems (CIS), University of Melbourne. She also serves as Associate Dean (Diversity and Inclusion) for the Faculty of Engineering and IT, demonstrating leadership in both research and academic community development. Her research lies at the intersection of database systems, machine learning, and artificial intelligence, with a vision of creating adaptive, self-driving database engines that optimize query execution in real-time. Her work spans learned indexes, query optimization, data quality, and data-driven traffic optimization, aiming to reduce costs and improve performance in data analytics. The recent publications reflect a strong trend toward integrating machine learning into core database operations—particularly through learned indexes, bandit-based tuning, and reinforcement learning for traffic systems. These works emphasize automation, provable guarantees, and real-time adaptation, showcasing a cohesive research agenda focused on intelligent, self-optimizing data systems. Her scientific excellence is recognized by numerous awards, including: L'Oréal-UNESCO for Women in Science Fellowship (2023) Victorian Young Tall Poppy (2024) Test of Time Award at SIGMOD 2022 Multiple Research and Teaching Excellence Awards from the University of Melbourne Google Research Inclusion Award (2021) She actively mentors PhD students and leads significant research projects funded by the Australian Research Council, Google, and Telstra. Her service includes roles as Associate Editor for SIGMOD Record, conference organization (e.g., aiDM, ADC, VLDB), and leadership in diversity and inclusion initiatives. She has also contributed to influential publications such as a chapter in the 7th edition of Database System Concepts . Her research lab focuses on AI-powered databases, traffic optimization via reinforcement learning, and self-healing data systems, positioning her at the forefront of next-generation data management.

Douglas G Downمشاهده پروفایل

استاد

• Stochastic Modelling
• Queueing Networks
• Scheduling Algorithms
• +۴ مورد دیگر

Douglas G Down is a Professor in the Department of Computing and Software at McMaster University . He leads the Resource Allocation and Stochastic Systems Lab (RASSL) and serves as co-PI of the Computing Infrastructure Research Centre (CIRC) . Education: Ph.D., University of Illinois at Urbana-Champaign His research focuses on stochastic modelling , scheduling , and performance evaluation of computer systems, with recent work on intelligent control of data centers , thermal-aware workload management , and data-driven resource allocation for healthcare systems. Publications span queueing theory , energy-aware scheduling , and machine learning applications in logistics. Recent scholarly trends include deep learning for pandemics (2023-2025), stochastic optimization of cooling systems (2024), and hybrid models combining queueing theory with AI (2023). He has pioneered frameworks like MGST for scheduling in heterogeneous grids and contributed to cache locality improvements in Hadoop systems. Scientific Awards: Nominated for Best Paper at MASCOTS 2013

• Business Model Innovation
• Digital Transformation
• Open Innovation
• +۷ مورد دیگر

Prof. Frank T. Piller ist Chair of Technology and Innovation Management an der RWTH Aachen University und Mitbegründer der RWTH Business School . Er forscht seit 2007 zu Disruptiver Geschäftsmodellinnovation , Industrie 4.0 und Kundenco-creation . Als Träger des ERC Synergy Grants SAFEr Grid (2025-2031) entwickelt er modulare Energienetze für die Zukunft. Lehrstuhlinhaber für Technologie- und Innovationsmanagement Gründungsdekan der RWTH Business School Internationaler Forschungskoordinator Seine Forschungsschwerpunkte umfassen: Business Model Innovation in etablierten Unternehmen AI-gestützte Wertschöpfung und digitale Plattformen Ökosystem-Governance für dezentrale Industrienetze Circular Economy Integration in massgeschneiderte Produktion Er erhielt: Co-Creation Award der PDMA Nominierung für HBR/McKinsey Innovation Award Mehrfachauszeichnung für "Flipped Classroom"-Lehre Google Scholar H-Index 73 mit >25.000 Zitierungen Als Keynote-Speaker und Executive-Education-Dozent an führenden Business Schools (MIT, IE, Vlerick) unterstützt er globalen Wandel. Sein Forschungsteam ( >30 Doktoranden ) arbeitet mit Industriepartnern wie Siemens , Vodafone und 3M .

Renata Medeiros de Carvalhoمشاهده پروفایل

استادیار

• Business Process Management
• Process Mining
• Declarative Business Processes
• +۳ مورد دیگر

Renata Medeiros de Carvalho is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with the Process Analytics and EAISI Health groups. She holds a PhD in Computer Science from Federal University of Pernambuco (Brazil), an MSc and BSc in Computer Engineering from University of Pernambuco, and has conducted postdoctoral research at UQAM (Canada). Her research focuses on adaptive and declarative business processes, with particular emphasis on healthcare and data privacy. Education: PhD in Computer Science, Federal University of Pernambuco (2015) MSc in Computer Engineering, University of Pernambuco BSc in Computer Engineering, University of Pernambuco Research Interests: Flexible business processes and Process Mining Declarative modeling (e.g., OCBC language) Healthcare process optimization GDPR compliance frameworks Key Projects: PATIENCE 2 : Patient-centric healthcare through nomadic sensing BPR4GDPR : GDPR compliance toolkit Awards: Xerox University Affairs Committee Grant NSERC Engage Grant Teaching & Leadership: Local coordinator for EIT Digital Data Science and Erasmus Mundus BDMA master programs Teaches courses like Advanced Process Mining and DBL Data Challenge

Thaleia Dimitra Doudaliمشاهده پروفایل

استادیار

• Operating Systems
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Thaleia Dimitra Doudali is an Assistant Professor at the IMDEA Software Institute in Madrid, Spain, leading the Muse research lab. She holds a PhD in Computer Science from Georgia Institute of Technology (2021), advised by Ada Gavrilovska, focusing on hybrid memory management with machine learning. Prior to her PhD, she earned a Diploma in Electrical and Computer Engineering from the National Technical University of Athens (2015). Her research interests span systems for machine learning, machine learning for systems, and computer vision applications in resource management. Her work has been recognized with awards including the 'César Nombela' (2024), 'Juan de la Cierva' (2021), and Rising Star in EECS (2020). She serves on program committees for top conferences (ASPLOS, EuroSys) and organizes workshops. Her lab's projects address cloud resource management, carbon efficiency, and sustainable computing. She advises multiple PhD and intern researchers, contributing to impactful publications in SIGMOD, EuroSys, and other venues. Notable contributions include Cronus (CV-based memory management), CaRE (carbon-efficient cloud-edge orchestration), and foundational work on ML-driven resource forecasting. Her research bridges systems and AI, aiming to optimize data center efficiency and sustainability. She actively promotes diversity in STEM through mentorship roles in ACM-W Greece and Women in HPC initiatives.

• Distributed and Network Computing
• Big Data Analytics
• Cloud Computing
• +۴ مورد دیگر

George Pallis is a Professor in the Department of Informatics at the University of Cyprus, affiliated with the School of Science. He holds a BSc and PhD from Aristotle University of Thessaloniki. His research focuses on Distributed and Network Computing, Big Data Analytics, and Cloud/Edge/Fog Computing. He leads the Master's Program in Data Science and has secured over €5.5M in research funding from the EU, Cyprus, and industry partners like Google. Education: BSc (2001), PhD (2006) from Aristotle University of Thessaloniki. Research Interests include Internet technologies, large-scale network environments, and cloud computing. He has published over 100 articles in top-tier journals and conferences (e.g., IEEE TKDE, ACM TOIT, WWW, ICDCS) and contributed to international standards (DIN, CEN). His work spans topics like fake news detection, edge computing frameworks, and energy-efficient micro-data centers. Key Achievements: Editor-in-Chief Emeritus of IEEE Internet Computing, recipient of multiple best paper awards, and contributor to projects like RAINBOW (H2020), UNICORN, and ICARUS. His research explores cutting-edge areas such as LLM manipulation, polarization detection, and carbon-aware computing. He has supervised five PhD students and served as General Chair for IEEE/ACM SEC 2024 and IEEE IC2E 2024. His work bridges academia and industry through collaborations on AI, IoT, and sustainable computing.

Mark Fergusonمشاهده پروفایل

استاد

• Supply Chain Management
• Sustainable Operations
• Pricing and Revenue Management
• +۳ مورد دیگر

Mark Ferguson serves as Associate Dean for Accreditation and Strategic Planning and Dewey H. Johnson Professor of Management Science at the University of South Carolina's Darla Moore School of Business. Previously the Steven Denning Professor at Georgia Tech's College of Management, his career spans over two decades in academia following five years as an IBM manufacturing engineer. His educational credentials include: Ph.D. in Business Administration (Operations Management), Duke University (2001) M.S. in Industrial Engineering, Georgia Tech (1994) B.S. in Mechanical Engineering, Virginia Tech (1991) Ferguson's research centers on supply chain sustainability , with pioneering work on product leasing environmental impacts , pricing-revenue management interfaces , and closed-loop supply chains . His investigations into contract design for supply chain efficiency and sustainable operations have reshaped industry practices. Recent publications demonstrate expanding expertise in healthcare operations and analytics education, maintaining theoretical rigor while addressing real-world business challenges through empirical methodologies. Analysis of his 2022-2025 publications reveals consistent focus on sustainable operations and revenue management, with growing interdisciplinary applications in healthcare, retail, and transportation. His work increasingly integrates business analytics with operational strategy, particularly in educational contexts, while maintaining strong methodological foundations in choice modeling and optimization. His scientific recognition includes: Management Science Best Operations Management Paper Award (2012-2014) for environmental impact of product leasing research Two Production and Operations Management Society (POMS) Best Paper Awards Ferguson has secured three National Science Foundation research grants and coauthored influential texts including Segmentation, Revenue Management and Pricing Analytics and Closed Loop Supply Chains . His professional leadership includes presidencies of the INFORMS Manufacturing and Services Operations Management Society, POMS College of Supply Chain Management, and INFORMS Revenue Management and Pricing Section. As Director of the Center for Applied Business Analytics, he drives analytics integration across the Moore School curriculum. His current initiatives focus on sustainable supply chain transformation through the Center for Applied Business Analytics, developing next-generation analytics competencies for business students while advancing research on operational sustainability across multiple industries.

Alejandro Laguna Sanzمشاهده پروفایل

استادیار

• Diabetes Technology
• Glucose Monitoring
• Artificial Pancreas Systems
• +۷ مورد دیگر

Alejandro Laguna Sanz is an Assistant Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His work bridges biomedical engineering and clinical diabetes care, focusing on technological solutions for glucose regulation. His research interests include diabetes technology, artificial pancreas systems, glucose monitoring accuracy, and the impact of exercise on glycemic control. He is particularly active in developing and evaluating predictive algorithms for glycemic management, especially in dynamic conditions such as physical activity and post-bariatric hypoglycemia. His work often combines control theory with clinical validation. The recent publications reveal a strong focus on real-world performance of continuous glucose monitors (CGMs), sex-specific responses in women with type 1 diabetes, and innovative interventions like elastic band resistance training and dual-hormone closed-loop systems. His research increasingly integrates population modeling, in silico studies, and virtual education platforms for artificial pancreas training. He is a member of the CLIDET research group (Clinimetry and Technological Development in Therapeutic Exercise), where he contributes to the design and clinical evaluation of advanced monitoring and control systems for metabolic diseases. Alejandro Laguna Sanz earned his PhD from Universitat Politècnica de València with a thesis on uncertainty in postprandial glucose modeling in type 1 diabetes, supervised by Dr. Paolo Rosseti and Dr. Jorge Bondía Company. He has not received any explicitly listed scientific awards in the provided text. He advises students within his research group, though no specific names are listed. His work is supported by collaborative projects in diabetes technology and engineering, particularly in the development of adaptive control systems and clinical validation of glucose monitoring devices. He is involved in both experimental and simulation-based studies.

Hampus Östh Gustafssonمشاهده پروفایل

پژوهشگر

• History of Education
• History of Humanities
• Historiography
• +۷ مورد دیگر

Hampus Östh Gustafsson is a researcher at Uppsala University's Department of History of Ideas, with affiliations at Lund University (2023–2025), KTH Royal Institute of Technology (HEOS group, 2023), and the Vossius Center (University of Amsterdam, 2022). His academic work focuses on the history of humanities, knowledge policy, university governance, and temporalities. Doctor of Philosophy (2021), Uppsala University Master's Degree in History of Ideas (2014), Uppsala University Exchange studies, University of Manchester (2011) His research examines the social legitimacy of humanities, temporal dynamics in academic governance, and knowledge circulation. Key projects include "Freedom to Research" (NetIAS program) and "Research Funding Effects" (1947–1977 Swedish humanities funding). He co-edits Högre Utbildning and contributes to the Early Career Researcher Board for Higher Education Quarterly . Recent publications analyze Swedish higher education policy, collegial governance, and comparative crisis narratives. Articles appear in Higher Education , History of Intellectual Culture , and Research in the Sociology of Organizations . Trends show focus on temporal governance, cross-disciplinary infrastructure, and humanities' societal role. Scientific awards include the Royal Swedish Academy of Sciences' Benzelius Prize (2020). Collaborations span institutions like SCAS (Uppsala), Zukunftskolleg Konstanz, and Paris IAS. He engages with academic teams including HEOS (KTH) and CIRCUS (Uppsala), contributing to debates about the humanities' value in democracies and neoliberal universities. His work bridges historical analysis with contemporary policy critique.

Yang Liمشاهده پروفایل

استادیار

• Computer Architecture
• Machine Learning
• On-Device AI
• +۴ مورد دیگر

Yang Li is an Assistant Professor of Computer Science at Iowa State University, specializing in computer architecture, machine learning, and their intersection. He holds a Ph.D. and M.S. from Carnegie Mellon University (2020), an M.S.E. from the University of Texas at Austin (2013), and a B.E. from Tsinghua University (2011). Prior to academia, he worked as a Senior Research Scientist at Meta, a Research Scientist at Meta, and a Researcher at Microsoft. His research focuses on large language models (LLM) acceleration, on-device AI, cloud infrastructure optimization, and spatiotemporal forecasting. He has contributed to over 20 peer-reviewed publications at top venues like ASPLOS, EMNLP, and ICASSP. Research Interests: Algorithmic and systems-level acceleration of LLMs On-device AI co-design and privacy Cloud memory/power management Graph-based spatiotemporal forecasting Teaching: Taught COMS 6730 (Advanced Topics in ML), COM S 321 (Computer Architecture), and guest-lectured on graph signal processing. Recent teaching scores include 4.75/5.0 (Fall 2024) and 4.67/5.0 (Spring 2025). Awards: IBM Patent Application Award (2021) and multiple patents on power management systems for data centers. Service: Program committee member for DAC 2024, NeurIPS 2024, and ICLR 2025. Reviewer for ACM TACO, IEEE TPAMI, TPDS, and others.

Wolfgang Lehnerمشاهده پروفایل

استاد

• Database technology for openData platforms - integration and consumption
• Support of advanced analytics (mining, forecasting, etc.) in database systems
• Support for realtime/righttime-analytics in data-warehouse infrastructures
• +۱ مورد دیگر

Wolfgang Lehner is a Full Professor and head of the Database Research Group at TU Dresden (since 2002/10), and a Professor in the Data Engineering, Science and Systems Group at Aalborg University (since 2024/05). He has held visiting scientist roles at SAP, Microsoft Research, IBM Almaden, and other institutions, alongside leadership as Director of the Institute of Systems Architecture at TU Dresden (2006–2020, 2022–present). Fields of Scholarship Database technology for openData platforms Advanced analytics support in databases Realtime analytics in data warehouses Main-memory database systems for mixed workloads His awards include the DFG Reinhart Koselleck Program (2021), Facebook Next-Generation Data Infrastructure Award (2021), and multiple ACM SIGMOD, SAP, IBM, and Huawei awards. He leads the TU Dresden Database Research Group and has directed the Institute of Systems Architecture since 2022/11.

• Capital Markets
• Financial Analysts
• Asset Management
• +۳ مورد دیگر

Mengqiao Du is an Assistant Professor at the NUS Business School , National University of Singapore, specializing in capital markets, financial analysts, and gender-related topics. She holds a Doctorate in Economic Sciences (summa cum laude) from the University of Mannheim (2022) and has visiting experience at UC Berkeley and the University of Miami. Primary Research Areas: Capital Markets, Financial Analysts, Asset Management, Gender Dynamics Key Contributions: Demonstrated mutual fund managers' repurchasing biases, analyzed pandemic-induced gender productivity gaps among analysts, and quantified role model influences on women's career choices Her work has been covered by Yahoo Finance , Institutional Investor , and The European , with presentations at institutions like University of Texas at San Antonio and conferences including AFA 2024 AFFECT Mentoring Event . She received the Best Paper Award in Corporate Finance at the 7th International Young Finance Scholars' Conference.

John Morrisonمشاهده پروفایل

استاد

• Parallel Distributed Computing
• Grid Computing
• Cloud Computing
• +۲ مورد دیگر

Professor John Morrison is the founder and director of the Centre for Unified Computing and co-founder of the Boole Centre for Research in Informatics at University College Cork. With qualifications including BSc, MSc, PhD, and DipTLHE, his research focuses on parallel distributed computing, grid technologies, and cloud architectures. His primary research explores: Self-organizing cloud management systems Heterogeneous computing environments Energy-efficient cloud infrastructure Grid computing middleware Professor Morrison's publications demonstrate strong focus on cloud computing optimization, distributed systems, and virtual reality applications in healthcare and education. Recent work emphasizes scalable resource management and trust systems in cloud environments. Honors include: Senior Member of ACM Senior Member of IEEE He has secured significant research funding including: €883,226 from Horizon 2020 for CloudLightning Project €379,111 from Enterprise Ireland for Cloud Computing Centre €646,604 from Higher Education Authority for Biophotonics Platform He leads the MAVRIC Research Lab focusing on immersive computing technologies and serves on editorial boards for multiple journals including Journal of SuperComputing.

Graham Rileyمشاهده پروفایل

مدرس

• High Performance Computing
• Scientific Computing
• Parallel Computing
• +۴ مورد دیگر

Graham Riley is a Lecturer in the School of Computer Science at the University of Manchester and holds a part-time position in the Scientific Computing Department (SCD) at STFC, Daresbury. His research focuses on high performance computing (HPC), software engineering for scientific computing, and performance modeling for parallel machines. Key areas include techniques for developing HPC applications, software architectures for coupled modeling, and performance control in distributed systems. His work emphasizes collaboration with computational scientists in domains such as Earth System Modelling (e.g., UK Met Office), computational chemistry, and biology. He has contributed to projects like the EuroExa architecture for exascale computing and the LFRic weather/climate model porting to FPGAs. Riley's research also explores energy efficiency in HPC systems and FPGA acceleration strategies for scientific workloads. Notable contributions include studies on parallelization strategies, FPGA-based acceleration of climate models, and optimizing OpenCL for heterogeneous architectures. His work aligns with UN Sustainable Development Goals, particularly through contributions to climate modeling and sustainable computing practices. Riley collaborates with institutions like the Met Office and the ESM community in Europe/US. His academic profile reflects a balance between theoretical research and practical application, with a strong focus on bridging computational science and engineering challenges.

Jayanth Raghothamaمشاهده پروفایل

دانشیار

• Healthcare Informatics
• Complex Systems Modeling
• Simulation and Gaming in Policy Design
• +۳ مورد دیگر

Jayanth Raghothama is an Associate Professor at KTH Royal Institute of Technology, affiliated with the School of Computer Science and Communication (CBH) and the Digital Futures Faculty. He is part of the Division of Health Informatics and Logistics, focusing on healthcare systems, complex systems modeling, and simulation-based decision-making. His academic role includes co-leading the Digitalization Platform and serving as a Vice-Director. Education: PhD in Complex Systems from KTH (2017). Prior experience includes software industry roles and work with a think tank in Bangalore. Research Interests: Healthcare logistics, complex systems analysis, participatory simulations, AI/ML ethics, and the philosophy of games and simulations. His work bridges computational models with real-world applications in healthcare, urban planning, and disaster management. Recent Projects: Co-Principal Investigator of the 'Data-driven Improvement of Work-Flows at the Karolinska University Hospital' project. Active in AI-based colorectal cancer detection in primary care (AIDCCIP project). Teaching: Courses on Applied Machine Learning, Simulation Methods, and Healthcare Logistics at Bachelor, Master, and PhD levels. Modules include AI/ML ethics and Agent-Based Modeling. Publications: Over 20 peer-reviewed articles focusing on healthcare simulation models, real-world data analysis in oncology, and hybrid modeling techniques. Notable works include patient flow optimization algorithms and frameworks for risk stratification in lung cancer studies.