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Gagan AgrawalView profile

Professor

• Parallel Computing
• High-Performance Computing (HPC)
• Data Analytics
• +5 more

Gagan Agrawal is the UGA Foundation Professorship in Computing and a Professor at the School of Computing, University of Georgia. He serves as Director of the School and is affiliated with the Franklin College of Arts & Sciences. Agrawal holds a PhD and MS in Computer Science from the University of Maryland (1994-1996). His research focuses on high-performance computing, parallel algorithms, compiler optimization for deep learning, GPU acceleration, and interdisciplinary applications in health informatics. Notable contributions include frameworks like ForensiBlock (blockchain for data forensics) and DELITE (tensorized instruction compilation). Agrawal has secured over $2.5M in NSF grants for projects addressing extreme-scale computing challenges. Recent grants include: SHF: Small: Memory Hierarchy Optimizations Meet Transformers (MITTEN) ($600K, 2024-2027) DELITE compilation system for deep learning models ($600K, 2023-2026) Publications span parallel computing methodologies, cybersecurity frameworks, and health outcomes analysis. His work on social determinants of health in cancer survival has been systematically reviewed in top-tier medical journals. Agrawal leads UGA's computing initiatives, emphasizing interdisciplinary research and student mentorship in HPC and AI domains.

Ehat ErcanliView profile

Teaching Professor

• Computer Architecture
• Embedded System Design
• System Verification
• +3 more

Ehat Ercanli is an Associate Teaching Professor at Syracuse University, serving as the Associate Chair of Education and Operations. He holds a Ph.D. in Computer Engineering from Case Western Reserve University. His research focuses on optimizing embedded systems, computer architecture, system verification, and VLSI design automation. He has contributed to advancements in memory management, compiler optimization, and energy-efficient computing. Key research interests include embedded system design, task recomputation techniques for memory utilization, and database systems optimization. His work emphasizes practical applications in multi-core systems, low-power electronics, and compiler-driven performance improvements. His publications highlight trends in system-on-chip (SoC) optimization, shared private memory management, and energy consumption reduction strategies. Notably, his 2007 paper was ranked #3 in the ACM Digital Library’s Most Popular Papers. Dr. Ercanli’s contributions also extend to automated code generation for database applications and custom processor synthesis for image processing.

Stefano FerilliView profile

Professor

• Machine Learning
• Artificial Intelligence
• Data Mining
• +6 more

Stefano Ferilli is a Professor of Computer Science at the University of Bari, Italy, where he leads the ARA (Apprendimento e Ragionamento Automatico) research lab within the Department of Computer Science. His academic roles include former Director of the Interdepartmental Center for Logic and Applications (CILA) and current head of the Artificial Intelligence & Intelligent Systems node in the CINI national laboratory. He holds a PhD in Computer Science and has been a key figure in advancing machine learning, logic programming, and digital library technologies. Education: Laurea (MSc equivalent) in Information Sciences (1996), Specialist Laurea in Computer Science (2003), and PhD in Computer Science (2001). His research focuses on foundational aspects of machine learning, multi-strategy reasoning, process mining, and applications in cultural heritage, bioinformatics, and smart environments. Research Contributions: Developed frameworks like INTHELEX (incremental theory learner), WoMan (process mining), and DoMInUS (document management). Over 370 publications, including a Springer monograph and multiple award-winning papers. Active in organizing conferences like ECML-PKDD, ICDM, and IRCDL, and serves on editorial boards of journals like Information Sciences . Projects: Led or participated in over 30 national and European projects, including EU-funded initiatives on digital libraries (COLLATE, DELOS) and AI applications. Collaborates with industries like Samsung and institutions like the Italian Police for traffic analysis and cultural heritage preservation. Awards: Recognized for outstanding peer review (MDPI, ECMLPKDD), best paper awards, and contributions to AI education and cultural heritage. Member of prestigious associations like AI*IA (Italian AI Society) and AICA (Italian Computing Society).

• Information Processing Systems
• Internet of Things (IoT)
• Edge Computing
• +4 more

Marcello Pietri is a Researcher (td art. 24 c. 3 lett. A) and Contract Professor at the Department of Engineering Sciences and Methods (DISMI) at the University of Modena and Reggio Emilia. His work focuses on Information Processing Systems, with expertise in IoT, Edge Computing, and Digital Twins. He teaches courses like 'Sistemi Informativi' (Information Systems) for the Engineering Management program, emphasizing database design, SQL, and web application development with Python. His research explores advanced topics including Digital Twin integration in Industry 5.0, Fluid Computing in IoT ecosystems, and Smart City data fusion using 5G MEC architectures. He collaborates with institutions like the DIPI Lab (Distributed and Pervasive Intelligence Group), contributing to projects on telecom security, energy forecasting, and human-centric manufacturing systems. Recent publications highlight innovations in operator digital twins for workplace well-being, distributed data mesh models for IoT-edge-cloud systems, and adaptive monitoring algorithms for large-scale cloud environments. His work bridges theoretical advancements with practical implementations, addressing challenges in scalability, real-time data processing, and interdisciplinary collaboration.

• Databases
• Information Systems
• Data Management
• +9 more

Johann Eder is a full professor for Information and Communication Systems at the Department of Informatics Systems, University of Klagenfurt, Austria, and currently serves as Deputy Head of Department. He previously held positions at the Universities of Linz, Hamburg, Vienna, and Klagenfurt, and was Vice President of the Austrian Science Funds (FWF) from 2005-2013. He was also a visiting scholar at AT&T Shannon Labs, NJ. Educational Background: Diplom-Ingenieur, University of Linz Doctor of Technical Sciences, University of Linz Johann Eder's research focuses on databases, information systems, and data management for medical research, including temporal information modeling, process evolution, and workflow systems. His work spans temporal data warehousing, exception handling in workflows, and application interoperability, with a particular emphasis on privacy and quality in medical data lakes and federated biobanks. Recent publications highlight trends in temporal reasoning for business processes, medical data quality, and service composition optimization. His editorial roles include positions at ACM Transactions on Database Systems and IEEE Transactions on Knowledge and Data Engineering . He leads the Information and Communication Systems Research Group at AAU, contributing to projects like federated biobank integration and blockchain-based smart contracts.

Enrico FranconiView profile

Professor

• Knowledge Representation
• Artificial Intelligence
• Semantic Technologies
• +6 more

Enrico Franconi is a tenured full Professor in the Faculty of Engineering at the Free University of Bozen-Bolzano, Italy. He is the founder and director of the KRDB Research Centre for Knowledge-based Artificial Intelligence, established in 2002. His research focuses on applying database, AI, and semantic technologies to address challenges in information systems design, data integration, and big data analysis. He holds leadership roles including former Vice-Rector for Research (2005-2006) and director of the European Masters Program in Computational Logic (2004-2019). His academic contributions span Description Logics, knowledge representation, and ontology engineering, with a strong emphasis on theoretical foundations and practical applications. He has led numerous EU-funded projects, including ONTORULE and SeWAsIE, and contributed to international conferences as a program committee member and keynote speaker. His work bridges theory and practice, aiming to translate foundational results into real-world solutions. He is a prolific author with an h-index of 42 and has mentored researchers in areas like semantic web technologies and conceptual modeling. Key achievements include advancing ontology-driven data integration, developing tools like ICOM for conceptual modeling, and contributing to standards for semantic web languages. He is affiliated with the Computational Logic community and actively participates in international research networks such as CAIRNE. His research has been recognized through ANVUR evaluations ranking his department among Italy’s top computer science faculties.

• Remote Sensing
• GIS
• Ecology
• +6 more

Dr. Harm Bartholomeus is an Assistant Professor of Remote Sensing at the Department of Geo-information Science and Remote Sensing, Wageningen University & Research. He received his MSc in Physical Geography (2000) and a Geography teaching degree (2001) from Utrecht University. His career includes part-time PhD research (2004–2009) on soil property estimation via spectral measurements and vegetation influence. Since 2009, he has focused on remote sensing techniques like imaging spectroscopy, LiDAR, and UAV-based methods applied to forestry, soil science, and climate studies. In 2012, he co-founded the Wageningen UR Unmanned Aerial Remote Sensing Facility (UARSF), advancing UAV research in environmental studies. His expertise spans Ecology, Geographical Information Systems (GIS), Remote Sensing, Soil Science, Spectroscopy, and 3D analysis. He teaches courses such as Advanced Earth Observation, Remote Sensing and GIS Integration, and MSc thesis supervision in Geo-information Science and Remote Sensing. His work integrates cutting-edge technologies for environmental monitoring, including terrestrial laser scanning and drone-based sensing. Research interests include vegetation-soil interactions, UAV applications in agriculture and ecology, and climate resilience. He collaborates on projects like the UARSF and contributes to global initiatives like the IDEAS-QA4EO network. No scientific awards are explicitly mentioned, but his contributions to UAV and LiDAR methodologies are widely recognized. He advises MSc students on thesis and internship projects in remote sensing and geo-information science.

• Structural Bioinformatics
• Protein Stability Prediction
• Machine Learning in Biology
• +3 more

Emidio Capriotti is an Associate Professor at the Department of Pharmacy and Biotechnology, University of Bologna. He leads the Second Cycle Degree in Bioinformatics and holds a PhD in Physical Sciences. His research focuses on predicting protein stability changes due to genetic variations using machine learning, with applications in personalized medicine. He develops tools like DDGun and PhD-SNPg for variant interpretation. Teaching includes courses on Bioinformatics, Biophysics, and Lab Techniques for Bioinformatics. His work bridges computational methods and biological problems, particularly in cancer genomics and protein structural analysis. Education: PhD in Physical Sciences from the University of Bologna. Research interests include structural bioinformatics, protein folding, and the interplay between genomic variations and disease. He collaborates with initiatives like CAGI challenges and ELIXIR-IT to advance genomic data infrastructure. Publications emphasize protein stability prediction, federated learning in clinical settings, and benchmarking computational methods. His lab contributes to open-source tools and standards for reproducible machine learning in biology.

• Database Systems
• Distributed Systems
• Cloud Computing
• +4 more

Dr. Kenneth Salem is a Professor at the University of Waterloo, Canada , with a distinguished career spanning over three decades in database systems, distributed computing, and data management. His work has significantly influenced transaction processing, replication, and scalability in modern databases. Institution: University of Waterloo Collaborations: Frequent co-author with Hector Garcia-Molina, Ashraf Aboulnaga, Umar Farooq Minhas, Khuzaima Daudjee Research Interests: Dr. Salem’s research focuses on database systems, particularly in transaction processing , distributed databases , cloud computing , and energy-efficient data storage . He has pioneered techniques for schema design in NoSQL , adaptive caching , and RDMA-based data transfer . His work often addresses challenges in high availability , workload-aware optimization , and cardinality estimation . Recent Article Trends: His latest publications (2023-2025) explore ad hoc transactions , eventual durability , and summary-based cardinality estimation , emphasizing practical solutions for real-world database scalability and consistency. Earlier works (2018-2022) covered memory power optimization , RDMA abstractions , and workload-aware CPU scaling , reflecting a sustained focus on performance and efficiency. Advising and Collaborations: Dr. Salem has mentored numerous co-authors in database research, including Ashraf Aboulnaga, Umar Farooq Minhas, and Khuzaima Daudjee. His collaborative projects span Apache Spark caching , RemusDB high availability , and DimmStore memory optimization . Labs and Teams: He has been a key contributor to the DaMoN and Versatile Database Systems workshops, focusing on hardware-aware database design. His work with teams at Waterloo and collaborations with institutions like ETH Zurich and MIT has advanced self-managing databases and edge replication technologies.

Olaf HartigView profile

Associate Professor

• Database Systems
• Semantic Web
• Data Management
• +5 more

Olaf Hartig is a Senior Associate Professor at Linköping University's Department of Computer and Information Science (IDA), affiliated with the Database and Information Techniques (ADIT) division. He is also an Amazon Scholar collaborating with the Neptune graph database team. His research focuses on data management, semantic web technologies, graph databases, and distributed data systems. Hartig holds a PhD from Humboldt-Universität zu Berlin and is a Docent at Linköping University. He has received numerous awards, including the SWSA Distinguished Dissertation Award and eight best paper awards, and was selected as a Wallenberg Academy Fellow in 2024. Education: PhD in Computer Science (Humboldt-Universität zu Berlin), Docent (Linköping University). Research interests span query processing for Linked Data, federated systems, RDF and GraphQL semantics, and knowledge graph construction. He leads research groups in Database and Web Information Systems and Semantic Web Technologies at IDA. Key achievements include pioneering traversal-based query execution, developing Triple Pattern Fragments, and contributions to standards like RDF* and SPARQL*. His work has been recognized through grants, patents (e.g., on graph acceleration techniques), and leadership roles in conferences like ISWC and ESWC. Teaching: Course leader for database technology courses (TDDD12, TDDD37) and advanced topics like big data analytics and bioinformatics databases. Active in curriculum design and interdisciplinary education. Labs/Teams: Database and Web Information Systems Group, Semantic Web Research Group, Sports Analytics Group (IDA) Grants: Wallenberg Academy Fellowship, Swedish Research Council funding

Russell SchwartzView profile

Professor

• Cancer Genomics
• Tumor Evolution
• Computational Phylogenetics
• +3 more

Russell Schwartz is Professor of Biological Sciences and Computational Biology at Carnegie Mellon University, with courtesy appointments in Computer Science and Machine Learning. He serves as Head of the Ray and Stephanie Lane Computational Biology Department and Co-Director of the Joint CMU-University of Pittsburgh PhD Program in Computational Biology. His research develops computational models for complex biological systems, focusing on cancer genomics and macromolecular assembly. Key areas include reconstructing tumor clonal evolution through integration of bulk and single-cell sequencing data, developing algorithms for stochastic simulation of self-assembly systems, and creating optimization methods for fitting models to experimental data. Recent publications demonstrate advancements in single-cell lineage tracing, circulating tumor DNA analysis, and generative AI for biological databases. His team's BrM-Phylo software enables phylogeny reconstruction from matched transcriptome data in breast cancer brain metastases. NSF CAREER Award Alfred P. Sloan Research Fellowship Schwartz leads multiple NIH-funded projects on tumor evolution modeling and mentors students in computational cancer research. His laboratory develops open-source tools including FISHtrees for tumor phylogenetics and TUSV for integrating structural variants in clonal reconstruction.

Dimitrios ZekkosView profile

Associate Professor

• Geotechnical Engineering
• Earthquake Engineering
• Landslide Dynamics
• +4 more

Dimitrios Zekkos is an Associate Professor at the University of Michigan's College of Engineering, Department of Civil and Environmental Engineering. He holds affiliations with the Center for South Asian Studies (CSAS) as faculty and serves as Founder & CEO of ARGO-E LLC, a geotechnical consultancy. His expertise spans geotechnical engineering, natural hazards, and remote sensing applications. Education: PhD (2005), MS (2002) – University of California, Berkeley; Ptychion (2001) – University of Patras, Greece. Research focuses on landslide dynamics, seismic ground response, UAV-enabled disaster assessment, and waste management systems. His work integrates field observations with advanced computational methods to address challenges in infrastructure resilience and environmental sustainability. Key projects include: Regional landslide hazard modeling in Nepal/Puerto Rico Co-seismic landslide mobility prediction Flood impact analysis in mountainous regions Structural health monitoring of civil infrastructure Zekkos' contributions to geotechnical engineering include novel liquefaction assessment procedures for gravelly soils and innovative applications of unmanned aerial vehicles for post-disaster reconnaissance. His research has been supported by NSF, NASA, and international collaborations.

• Sustainable Waste Conversion
• Thermochemical Conversion
• Biochemical Conversion
• +5 more

Dr. Tosin Somorin is a Chancellor's Fellow/Lecturer in Energy at the University of Strathclyde's Department of Chemical and Process Engineering. His research focuses on sustainable waste conversion, energy systems, and biogenic carbon sequestration, contributing to UN SDGs 7, 11, and 13. He holds a PhD in Gas Turbine Engineering from Cranfield University and has extensive experience in environmental consulting and interdisciplinary research. Education: PhD in Gas Turbine Engineering, Cranfield University (2011–2015) BSc in Microbiology and Biotechnology, University of Hertfordshire (2009–2010) Research Interests: Sustainable waste-to-energy processes, thermochemical/biochemical conversion, circular economy strategies, and environmental impact assessment. Specific areas include gasification, anaerobic digestion, and engineered biochar for carbon capture. Teaching: Contributes to modules such as CP538 (Environmental Engineering for Industrial Challenges), CP407 (Chemical Engineering Design), and 18530 (Chemical Engineering Project). Supervises students in wastewater treatment, resource recovery, and sustainable agri-food systems. Projects: Principal Investigator: 'Geo-Project - Next Generation Wastewater' (2023–2024) Co-Investigator: EU Horizon-funded 'REFINE' project (2023–2027) for solar fuels Awards: 2023 Strathclyde Medal for the 'Sustainable Impact by Design' Team. Labs/Teams: Leads research groups focused on experimental design, process modeling, and feasibility studies for innovative energy technologies.

Ashly CabasView profile

Assistant Professor

• Seismic Hazards
• Geotechnical Engineering
• Earthquake Ground Motions
• +5 more

Ashly Cabas is an Assistant Professor in the Department of Civil, Construction and Environmental Engineering at North Carolina State University (NC State). She leads the GEOHAZARDS AND EARTHQUAKE ENGINEERING (GEOQUAKE) RESEARCH LAB , focusing on geotechnical aspects of earthquake engineering, including seismic hazard assessment, ground motion modeling, and liquefaction-induced ground deformations. Her work integrates geospatial analytics, numerical modeling, and probabilistic frameworks to enhance infrastructure resilience against seismic risks. Research interests include: Predictive modeling of liquefaction-induced lateral spreading Regional seismic velocity modeling for coastal plains Geostatistical analysis of ground motion data Impact of fluvial geomorphology on seismic hazards Advances in site response analysis methodologies Her research team examines large-scale ground motion databases (e.g., KiK-Net, DesignSafe) and collaborates on projects like the 2023 Gulf/Atlantic Coastal Plains Seismic Model . Key recent contributions involve improving input ground-motion selection protocols and developing databases for hazard mitigation. Grants & Awards: She leads a NSF CAREER Award (2022) focused on probabilistic seismic site response modeling under uncertainty. Her work emphasizes reproducible research practices, as highlighted in publications advocating for open data/code sharing. Labs/Teams: Directs the GEOQUAKE Lab, which bridges geotechnical engineering and computational methods to address societal risks from earthquakes. Collaborations include global case studies (e.g., 2011 Christchurch earthquake, 2018 Anchorage earthquake).

• Database Systems
• Healthcare Information Systems
• Artificial Intelligence
• +5 more

Carlo Combi is a Full Professor at the Department of Computer Science, University of Verona. He serves as Department Director and holds roles in various academic committees, including the Faculty Board of PhD in Computer Science and the Computer Science Teaching Committee. His research focuses on databases, healthcare information systems, temporal data mining, and business process management. He leads the STARS laboratory and has contributed to projects like PREPARE (prostate cancer evaluation) and EDIPO (neuroimaging genetics). His teaching spans courses on biomedical databases, software engineering, and Python programming. Combi's work integrates ethical considerations into process models and addresses challenges in healthcare workflows, temporal analytics, and AI applications in medicine. Education: Not explicitly listed in provided texts. Research Projects: Includes 30+ projects since 2008, emphasizing healthcare informatics, temporal systems, and data warehousing. Labs/Teams: STARS (Semistructured Temporal clinical Geographical Systems) and collaborations with CBMC (Computational Biomedicine Center). Grants: Multiple national/international grants, including funding for temporal data mining and healthcare process modeling. Awards: None explicitly mentioned, though his leadership roles and extensive publications highlight academic recognition. His research bridges clinical processes, temporal databases, and AI, with applications in acute kidney injury prediction, BPMN extensions for healthcare, and explainable AI in medical systems. Combi actively contributes to open-source solutions for clinical data analysis and integrates ethical frameworks into process management.