Find Academic Supervisors

Umakishore RamachandranView profile

Professor

• Distributed Systems
• Edge Computing
• Sensor Networks
• +5 more

Umakishore Ramachandran is a Professor in the School of Computer Science at Georgia Institute of Technology's College of Computing, where he directs the Embedded Pervasive Lab. He received his Ph.D. from the University of Wisconsin-Madison in 1986 and has led transformative initiatives including the Online MS in Computer Science (OMSCS) program. His research spans distributed systems, edge computing, and real-time sensor networks, with applications in smart surveillance and connected vehicles. His research interests include architectural design of parallel/distributed systems, large-scale situation awareness using camera networks, cloud-edge continuum optimization, and latency-sensitive applications for geo-distributed infrastructures. Recent work focuses on elevating edge computing to parity with cloud resources. His publications show strong emphasis on edge computing innovations (MicroEdge, FogStore), real-time video analytics (EVA, ClairvoyantEdge), and adaptive mobile systems (Foresight). Trends include multi-tier architectures, quality-of-experience optimization, and scalable processing for IoT workloads. Major Awards: IEEE Fellow (2014) NSF Presidential Young Investigator (1990) ACM/IFIP Middleware Best Paper (2022) 3x College of Computing Dean's Awards He has advised 40+ PhD students, with recent graduates at Google, Microsoft, and academia. Current NSF/CPS grants support his work on geo-distributed latency-sensitive applications. He co-leads the STAR Center and Samsung-funded embedded software programs. His Embedded Pervasive Lab develops systems like Stampede (stream processing) and DFuse (sensor fusion), with testbeds in the Aware Home and transportation networks. Teams collaborate with Intel, Microsoft, and Bosch on edge-AI deployments.

• Entity Resolution
• Record Linkage
• Privacy-Preserving Record Linkage
• +3 more

Dimitrios Karapiperis serves as an Academic Scholar at the School of Science and Technology, International Hellenic University (IHU), specializing in Entity Resolution and Privacy-Preserving Record Linkage. Previously, he held a post-doctoral position at the Hellenic Open University. He earned his PhD from the Hellenic Open University and his MSc from the University of York (UK). His doctoral thesis was featured in the IEEE Intelligent Informatics Bulletin of August 2017, highlighting its significance in the field. Dr. Karapiperis' research centers on developing advanced algorithms for entity resolution, including similarity measures, data structures, and scalable distributed solutions using randomization techniques. His work extends to privacy-preserving methods for record linkage with applications in electronic health records, cryptocurrency analysis, and social media sentiment. He has made significant contributions to efficient record linkage in data streams and spatio-temporal data through innovative blocking techniques and approximation schemes. His recent publications (2020-2022) reveal a consistent focus on scalable and privacy-aware record linkage, with increasing applications in financial technology and affective computing. Collaborations with prominent researchers like V.S. Verykios have resulted in numerous publications in top venues including IEEE Big Data and IEEE TIFS, demonstrating expertise in both theoretical foundations and practical implementations. Scientific Recognition Doctoral thesis featured in IEEE Intelligent Informatics Bulletin (2017) Research Projects University of York: Development of Java servlets for converting VisioXML into GSML within the High Integrity Systems Engineering research group University of Macedonia: Standardization of distance learning systems University of Macedonia: Establishment of a data bank for the fur sector in Kastoria University of Macedonia: System for organizing business processes of the Ministry of Macedonia and Thrace Dr. Karapiperis has collaborated with research teams across multiple institutions, contributing to diverse projects from healthcare data integration to government business process optimization, while maintaining active research in scalable entity resolution methodologies.

Marie-Christine ROUSSETView profile

Professor

• Knowledge Representation
• Information Integration
• Ontology-based data access
• +7 more

Marie-Christine ROUSSET is a Professor of Computer Science at the University of Grenoble Alpes (UGA) in France, where she is a member of the LIG (Laboratoire d'Informatique de Grenoble) in the SLIDE group. Previously affiliated with Paris-Saclay (LRI), she has established herself as a leading researcher in Knowledge Representation and Information Integration. She holds the distinguished position of Senior member of the Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) and serves as co-responsible for the chair Explainable and Responsible AI within MIAI Grenoble Alpes. Her research focuses on ontology-based data access, logic-based mediation between distributed data sources, query rewriting using views, data linkage, and distributed reasoning for the Semantic Web. She skillfully combines artificial intelligence and database techniques to address complex information integration challenges, with applications spanning biomedical informatics, educational technology, and trustworthy AI. Her work demonstrates consistent innovation from foundational research to practical implementations, as evidenced by her co-authorship of the book 'Web Data Management' published by Cambridge University Press. Professor ROUSSET's recent publications (2019-2022) reveal a growing emphasis on data privacy, RDF graph anonymization, and interactive ontology engineering, while maintaining her strong contributions to semantic web technologies and knowledge representation. Her research shows increasing attention to trustworthy AI concerns, aligning with her leadership roles in relevant projects. Scientific Recognition Senior member of Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) Junior member of Institut Universitaire de France (IUF) from 1997 to 2002 Chevalier de l'Ordre National du Merite (July 11, 2011) EurAI Fellow (nominated ECCAI Fellow in 2005) Best Paper Award at AAAI'96 for 'Verification of Knowledge Bases based on Containment Checking' Professor ROUSSET maintains an active role in the scientific community through editorial work and organizational leadership. She serves on the Editorial Board of Communications of the ACM (CACM) and has held significant roles including PC chair of EGC 2019, Workshops co-Chair of WWW 2018, and Area Chair of IJCAI 2017. Her consistent service on program committees of major international conferences demonstrates her standing in the field. Her laboratory, the SLIDE group within LIG, focuses on semantic web technologies, knowledge representation, and data integration. The group maintains strong connections with the international research community and participates in collaborative projects addressing cutting-edge challenges in artificial intelligence and data management, with particular emphasis on trustworthy and explainable AI systems.

• Geosensor Networks
• Wireless Sensor Networks
• Sensor Data Streams
• +5 more

Dr. Silvia Nittel is an Associate Professor in the School of Computing and Information Science at the University of Maine. She serves as the Director of the UMaine Data Science and Engineering program and the Graduate Program Coordinator for 7 Graduate programs in the Spatial Computing group. Dr. Nittel directs the Geosensor Networks Lab and has held significant leadership roles including Computer Science Undergraduate Coordinator (2013-2018) and member of the executive committee of the Sensor Science, Engineering and Informatics IGERT (2005-2012). Dr. Nittel received her Ph.D. in Computer Science from the University of Zurich in 1994, followed by postdoctoral research at UCLA Computer Science Department (1995-1998), where she later became Co-Director of the UCLA Data Mining Lab (1998-2001). She joined the University of Maine faculty in 2001. Her research focuses on extending data management technology for geosensor networks with five primary thrusts: Decentralized in-network data collection algorithms for geosensor networks Real-time analytics of spatially distributed sensor data streams (processing up to 250K updates/sec) Field Data Type Hierarchy for Stream Data Models and spatio-temporal interpolation Integration of sensor network data with ontologies for event understanding Blockchain applications for healthcare data privacy and access control Dr. Nittel is a recipient of the prestigious NSF Early CAREER award, and her research has been funded by multiple agencies including NSF, NGA, NASA, and the Maine National Guard. As a thought leader, she co-founded the 'Geosensor Networks' conference series, authored two foundational books on the subject, and contributed to encyclopedia entries in four different publications. Her highly cited 2009 Sensors journal article established key concepts in environmental monitoring through sensor networks. Dr. Nittel teaches graduate courses in Spatial Information Science and Engineering and MSIS programs, mentoring students through the Geosensor Networks Lab where they engage with cutting-edge research and industry collaborations with organizations like GE.

Arne SolliView profile

Associate Professor

• Historical Demography
• Urban History
• Historical GIS
• +5 more

Arne Solli is an Associate Professor in History at the Department of Archaeology, History, Cultural Studies and Religion, University of Bergen. His academic work bridges historical scholarship with digital methodologies, with a particular focus on historical demography, urban history, and GIS applications in historical research. Dr. Solli's research spans multiple interconnected domains including historical demography, urban development of Bergen, historical GIS applications, and the evolution of property registration systems. His work often combines microhistorical approaches with macrohistorical perspectives, creating innovative frameworks for understanding historical population patterns. He has made significant contributions to the study of 19th century cholera epidemics in Norway, examining how factors like topography, social status, and water supply affected mortality rates. His research demonstrates a consistent focus on spatial and temporal analysis of historical phenomena, with particular attention to Bergen's urban development over centuries. Dr. Solli has pioneered the integration of GIS technology with historical research through his development of BerGIS, a map portal for historical maps of Bergen that has become an essential resource for urban historians. Historical demography and population structures Urban history and development of Bergen Historical GIS applications Property registration systems through time 19th century Norwegian social and health history Cholera epidemiology and public health Dr. Solli has received recognition for his innovative approaches to historical research, particularly in developing digital tools that transform how historical data can be analyzed and visualized. His work on BerGIS has provided valuable resources for researchers studying urban development patterns over time. As an educator, Dr. Solli has contributed to the development of digital history methodologies and has supervised numerous students in historical research. His publications span from the 1990s to present, demonstrating a sustained commitment to advancing historical scholarship through technological innovation.

Tamara Ilieva-TsvetkovaView profile

Assistant Professor

• Geodetic measurements
• Spatial databases
• CAD and GIS systems
• +5 more

Tamara Ilieva-Tsvetkova is a Senior Assistant Professor at the Department of Geodesy and Geoinformatics within the Faculty of Geodesy at the University of Architecture, Civil Engineering and Geodesy (UACEG) in Sofia, Bulgaria. She also serves as a Technical Associate at the Center for Quality and Accreditation and maintains her office in Cabinet 411P, with reception hours on Mondays from 11:30-12:30 during the winter semester of the 2025-26 academic year. Her educational background includes: Master's degree in Geodesy from UACEG, Sofia (2007) Master's degree in Marketing with specialization in "Advertising Management" from UNWE, Sofia (2015) Doctorate in "General, Higher and Applied Geodesy" from UACEG, Sofia (2019) Tamara Ilieva-Tsvetkova's research focuses on geospatial technologies and methodologies, with particular expertise in geodetic measurements, spatial databases, CAD and GIS systems development, engineering project management, and coordinate systems. She is proficient in English (excellent level) and Russian (basic level), and possesses extensive technical skills in AutoCAD, ArcGIS, QGIS, PostgreSQL with PostGIS, and web mapping libraries like Leaflet and OpenLayers. Her recent publications (2021-2024) show a strong trend toward web-based GIS applications, indoor positioning systems, climate change monitoring using geospatial data, and the integration of artificial intelligence with geospatial technologies. Her work spans practical applications in urban planning, transport infrastructure risk assessment, real estate management, and environmental monitoring, with a particular focus on Bulgarian territories. She is an active member of professional organizations: Chamber of Engineers in Investment Design Chamber of Engineers in Geodesy European Geosciences Union (EGU) Tamara Ilieva-Tsvetkova has participated in numerous research and construction projects: Upgrading information systems for AGKK (2013-2014) Information platform for environmental research and modeling at UACEG (2018-2019) Center of Excellence "Heritage BG" (2018-2023) Geodetic surveying for the South Stream gas pipeline Cadastral mapping for multiple Bulgarian villages and regions Geodetic survey for Sofia Metro expansion Geodetic survey for Sofia Airport infrastructure Her technical expertise spans multiple domains including geodetic measurement processing, GIS system development, spatial database management, and programming for geospatial applications using C#, SQL, JavaScript, and various GIS APIs.

• Mobility Data Analytics
• Big Data
• Machine Learning
• +8 more

Dr. Omid Isfahani Alamdari serves as Assistant Professor in the Master of Data Analytics program at the University of Niagara Falls Canada, bringing expertise in mobility data analytics and big data systems developed through international research experience. Education PhD in Computer Science, University of Pisa, Italy MSc in Computer Engineering - Software (Distributed Systems), Iran University of Science and Technology BSc in Computer Engineering - Software, Urmia University, Iran Research Focus His research centers on developing efficient trajectory analysis methods and advanced indexing techniques for massive mobility datasets. Key applications include sustainable transportation solutions (electric vehicle adoption, carpooling optimization) and explainable event prediction systems combining historical patterns with real-time data streams. He actively explores generative AI applications for mobility challenges and time series analysis. Publication Trends Publications from 2018-2023 reveal consistent contributions to transportation analytics, with dominant themes in trajectory processing (40%), sustainable mobility (30%), and prediction systems (30%). His work appears in top transportation venues (IEEE Transactions on ITS) and data science conferences (IEEE BigData, SIGSPATIAL), featuring strong international collaboration patterns. Academic Activities Teaching: Agile Software Development, Python for Data Analytics, SQL Databases, and Data Analytics Case Studies Research: Currently leads EU-inspired projects on sustainable mobility and event prediction Specialization: Trajectory analysis, spatio-temporal indexing, EV simulation, graph embedding