Find Academic Supervisors

Paola NassisiView profile

Researcher

• Internet of Things
• Data Analysis
• Scientific Computing
• +1 more

Paola Nassisi serves as Director of the Advanced Digital Innovation Center (ADIC) and Deputy Director of the Advanced Scientific Computing (ASC) Division at the CMCC Foundation, where she operates as a Researcher specializing in climate-focused data infrastructures. Her work integrates Internet of Things (IoT), data analysis, and scientific computing to address climate change challenges through community-driven data services, with active involvement in national and international projects since 2012. She holds an M.Sc. degree cum laude in Computer Engineering from the University of Salento. Her research spans critical domains in climate informatics: Development of IoT-enabled environmental monitoring systems (e.g., irrigation management) Scientific computing for climate data analysis and modeling Provenance tracking in climate science workflows Design of interoperable data infrastructures and science gateways These efforts converge on creating scalable solutions that bridge computational innovation with real-world climate applications. Analysis of her publications reveals consistent themes in climate data management, including operational platforms for fire monitoring (OFIDIA2), CMIP6 data distribution networks, and user-centric gateways like BioClimate and SeaConditions. Her work emphasizes practical implementations that enhance accessibility of climate data for diverse stakeholders while advancing technical frameworks within the European Open Science Cloud ecosystem. Nassisi leads strategic initiatives such as INDIGO-DataCloud and EUBrazilCloudConnect, demonstrating expertise in securing and managing large-scale research projects. Her coordination of operational networks for climate data distribution highlights leadership in collaborative international efforts. She directs the Advanced Digital Innovation Center within CMCC's Data Science research unit and participates in an amateur astronomy group, reflecting interdisciplinary engagement beyond her professional climate informatics work.

• Artificial Intelligence
• Machine Learning
• Pattern Recognition
• +6 more

Professor Jean-Christophe Nebel is a Professor of Computer Science at Kingston University , Faculty of Science, Engineering and Computing, Computing and Information Systems Department. He holds a PhD in Computing Science from the University of St-Etienne (1997), an MSc in Computing Science (University of Lyon), an MScEng in Electronics & Signal Processing (CPE Lyon), and a Postgraduate Certificate in Higher Education Learning & Teaching. His research focuses on Artificial Intelligence, Machine Learning, Pattern Recognition, Computer Vision , and Bioinformatics , with applications in renewable energy , ecology , and genomics-inspired surveillance . PhD in Computing Science, University of St-Etienne MSc in Computing Science, University of Lyon MScEng in Electronics & Signal Processing, CPE Lyon Postgraduate Certificate in Learning & Teaching, Kingston University His work bridges AI and interdisciplinary domains , including protein structure prediction, human action recognition, and AI-driven environmental monitoring. Key projects include a stochastic context-free grammar framework for proteomics, manifold-based modeling of multivariate sequences, and game-theoretic optimization for smart grids and PPE management during the pandemic. Recent articles explore deepfake detection , air pollution analytics , and honeybee health monitoring via acoustic signals. Notable scientific awards include the IEE Reeve Premium (2004) , Senior Fellow of the Higher Education Academy (SFHEA) , and Senior Member of the IEEE . He led an Innovate UK-funded Knowledge Transfer Partnership (KTP) with Instinet Global Services, achieving the highest "Outstanding" grade. At REF2014, he contributed to a 3* Impact Case Study on pedestrian tracking technology commercialized by Ipsotek and BAe Systems, benefiting entities like the London Eye and the Australian Government. As Director of Kingston University’s Knowledge Exchange & Research Institute for Cyber, Engineering & Digital Technologies , he coordinated the REF2021 submission for Computer Science & Informatics, which achieved 73% world-leading/internationally excellent research. He serves on editorial boards of BMC Bioinformatics , PLOS ONE , and Pattern Analysis & Applications , and evaluates proposals for the EPSRC , NSERC , and international councils.

Judah M. DiamentView profile

Professor

• Distributed Systems
• Middleware
• Software Engineering
• +3 more

Judah M. Diament is a Professor and Chair of the Computer Science department at Yeshiva University, located in New York. He holds a Master of Science from New York University (2000). Prior to academia, he spent 14 years at IBM's T.J. Watson Research Center (2000–2014), focusing on middleware and distributed systems, resulting in 13 patents and numerous publications. From 2014–2016, he served as Vice President of Finance Engineering at Goldman Sachs, developing a custom language and toolchain to streamline application updates. He returned to Yeshiva University in 2016 to mentor students toward similar career success. His research interests span distributed systems, middleware, software engineering, and finance technology. He teaches courses such as Distributed Systems, Introduction to Computer Science, and Data Structures. His work emphasizes practical application and innovation, as reflected in his quotes on learning through experimentation and Drucker’s focus on external results. Education: Master of Science, New York University, 2000 Research Interests: Professor Diament’s work bridges academic research and industry application. His expertise includes designing robust distributed systems, optimizing middleware frameworks, and applying computational methods to finance. He is passionate about creating tools that reduce development time, such as his Goldman Sachs project, and advancing educational strategies to prepare students for tech careers. Articles & Patents: His publications focus on middleware systems, distributed architectures, and business process automation. Notable works include innovations in data replication, temporal artifact management, and dynamic middleware assembly. His 13 patents highlight contributions to software infrastructure and decision modeling systems. Grants & Labs: While specific grants aren’t detailed, his industry collaborations at IBM and Goldman Sachs reflect significant applied research funding. He leads the Computer Science department’s initiatives in cutting-edge systems development and curriculum design. Labs/Teams: He oversees Yeshiva’s Computer Science departmental projects, fostering student engagement in distributed systems and software engineering through coursework and research opportunities.

• Relational Databases
• Speculative Query Execution
• Distributed Computing
• +5 more

Anna Sasak-Okoń is a Lecturer at the Department of Information Systems Software within the Institute of Informatics and Mathematics , Maria Curie-Skłodowska University (UMCS). Her academic work focuses on database systems, speculative query execution, and distributed computing, with a particular emphasis on graph-based modeling techniques.

• Databases
• Software Engineering
• Data Warehousing
• +6 more

Breiman Alexander Davidovich is an Associate Professor at the Department of Software Engineering, Faculty of Computer Science at the National Research University Higher School of Economics (HSE) in Moscow. He began working at HSE in 2010 and has 30 years of scientific and teaching experience. Previously, he served as an Associate Professor at the Department of Personal Computers and Networks at the Moscow State University of Instrument Engineering and Informatics from 1994 to 2013. He also works as a Senior Lecturer at the Luxoft Training Center since 2013 and as Head of the IT Department at Titan Meta LLC since 1996. National Research University Higher School of Economics (2010-present): Associate Professor/Invited Lecturer Moscow State University of Instrument Engineering and Informatics (1994-2013): Associate Professor Luxoft Training Center (2013-present): Senior Lecturer Titan Meta LLC (1996-present): Head of IT Department His educational background includes a Candidate of Technical Sciences degree (equivalent to PhD) from Moscow State Academy of Instrument Engineering and Computer Science in 1998, with a dissertation on "Database software for training systems with multimedia elements," and a degree in Computer Science from Moscow Institute of Instrument Engineering in 1994, specializing in "Computers, Complexes, Systems and Networks." Professor Breiman's research focuses on databases, software engineering, data warehousing, information systems, and knowledge engineering. His work spans theoretical database design, practical implementations of database systems, and educational applications of information technology. He has published extensively on database architecture, reliability engineering, and distributed systems, with a particular emphasis on practical applications in educational and business contexts. His teaching covers database systems, distributed databases, data warehouses, and advanced database topics across multiple programming languages and platforms. His publications reveal a consistent focus on database technologies, evolving from foundational database concepts to modern distributed and big data systems. He has explored specialized areas including embedded databases, social network analysis, process mining, and stream data processing systems, demonstrating both theoretical depth and practical application. Gratitude from the Faculty of Computer Science, HSE (July 2025) Best Teacher award (2021-2024) Best Teacher award (2016-2019) Best Teacher award (2013) Best Teacher award (2011) Professor Breiman has supervised numerous student theses at both bachelor's and master's levels, covering diverse topics in database systems, software engineering, and information systems. His students have developed applications ranging from distributed content delivery systems to health monitoring systems for diabetes patients. He teaches a variety of courses including Databases, Advanced Databases, Distributed Databases and Data Warehouses, and Database Construction, in both Russian and English. His teaching spans multiple campuses of HSE including Moscow, Perm, and Nizhny Novgorod. While not explicitly mentioning specific labs or research teams in the provided information, his work with students on practical implementations suggests active engagement with applied research projects, particularly in database technologies and their real-world applications.

• Digital Preservation
• Information Systems
• Workflow Automation
• +2 more

Ingemar Andersson is a Lecturer at Luleå University of Technology in the Department of Computer Science, Electrical and Space Engineering, affiliated with the Digital Services and Systems division. He has taught programming, software architecture, and databases since 2002. Concurrently, he researches at the LDP Centre (Sweden's national digital preservation competence center), where he began as a software/test engineer in 2008 on projects PROTAGE and Test Platform. His industry background includes 8 years as a software developer and project manager. His research centers on digital preservation systems , specifically designing e-services to facilitate the transfer of digital collections to Open Archival Information Systems (OAIS). Key focuses include improving Submission Information Package (SIP) quality, workflow automation for pre-ingest processes, and context-aware preservation management. He developed six novel design principles for pre-ingest systems through EU projects (ENSURE, ForgetIT), emphasizing adaptive SIP generation and policy-aware workflows. Recent publications explore AI applications in education and digital preservation automation, reflecting interdisciplinary work bridging information systems and archival science. No awards or grants are documented.

Jon MunsonView profile

Professor

• Programming Education
• Cloud Computing
• Telematics
• +3 more

Jon Munson serves as a Professor of Computer Science at Manhattanville University, a position he has held since 2013. Prior to his academic career, he spent fifteen years as a Research Staff Member at IBM's T.J. Watson Research Center, where he contributed to projects in collaboration systems, digital rights management, location-based services, telematics, and cloud computing. His industry experience also includes a role as an Applications Engineer at Applied Dynamics International, working on simulation of physical systems such as aircraft engines. At Manhattanville, he teaches foundational courses including Computer Programming I and II, Data Structures and Algorithms, Database Systems, and Interactive Media - System Design. Education: Bachelor of Arts in Religion/Ancient Civilization from Hope College Master of Science in Mechanical Engineering from the University of Michigan Doctor of Philosophy in Computer Science from the University of North Carolina Chapel Hill Research Interests: Dr. Munson's research trajectory spans from mechanical engineering simulations to diverse areas of computer science. His early work at IBM focused on practical systems for telematics, location-based services, and ubiquitous computing. In his academic role, he has increasingly concentrated on computer science education, investigating challenges faced by novice programmers. His recent publications address the timely assessment of programming skills, the interpretation of compiler error messages by beginners, and the development of models to identify struggling students early in their learning process. He also expresses a strong interest in integrating computational thinking with the liberal arts. Publication Trends: An analysis of Dr. Munson's publications reveals two distinct phases. From 2002 to 2007, his research centered on mobile and ubiquitous computing, producing work on location-based notification, in-vehicle user interfaces, and rule-based telematics services. More recently (2015-2018), his focus has shifted to computing education, with multiple papers presented at the SIGCSE conference and published in the Journal of Computing Sciences in Colleges, addressing pedagogical challenges in introductory programming. Advising and Grants: The available information does not specify any graduate students advised by Dr. Munson or details of research grants he may have secured.

• Cloud Computing
• Grid Computing
• Health Informatics
• +5 more

David Levine serves as an Associate Professor in the Computer Science and Engineering Department within the College of Engineering at The University of Texas at Arlington. His academic career spans decades with continuous teaching and research contributions, evidenced by his ongoing course instruction through Fall 2025 and active grant leadership. Levine's research spans cloud and grid computing, health informatics, bioinformatics, pervasive computing, and secure programming. His work integrates computational techniques with practical applications in healthcare (Smart Hospital for Elderly Care), high-energy physics (Fermilab collaborations), and accessibility infrastructure. He has pioneered curriculum development in emerging fields including Cloud Computing, Secure Programming, Mobile Computing, and Data Mining, with courses consistently reaching maximum enrollment capacity and establishing distance learning records within the engineering college. His publication portfolio demonstrates significant interdisciplinary impact across IEEE Supercomputing, health informatics, genetics, and pervasive computing. Recent work focuses on spatial data visualization for public health (2022), hardware simulation platforms (2017), and scalable notification frameworks for healthcare systems (2011). His research has secured over $5 million in funding from NSF, NIH, DoE, and industry partners including Luminant Power. Computer Science Department Teaching Award recipient Student teams won ATT University Challenge, Nokia Symbian Challenge, and Department of Energy Challenge ($200k+ total) Levine has mentored 4 PhD students as co-supervisor, chaired 6 Master's theses, and advised numerous undergraduate researchers. His laboratory work focuses on grid computing applications for high-energy physics and bioinformatics, with current projects including the GAANN Doctoral Fellowships in IoT and Smart Hospital infrastructure development. He serves as NTT Hiring Committee Chair and Faculty Senate Chair, demonstrating significant institutional leadership.

Vana KalogerakiView profile

Professor

• Distributed Systems
• Real-Time Systems
• Participatory Sensing
• +8 more

Prof. Vana Kalogeraki is a Professor leading the Distributed and Real-Time Systems research group at Athens University of Economics and Business. Previously, she held faculty positions at the University of California, Riverside, and was a Research Scientist at Hewlett-Packard Labs. She earned her PhD from UC Santa Barbara in 2000, with earlier degrees from the University of Crete. Her research focuses on distributed systems, real-time computing, participatory sensing, and edge computing. She has published over 100 papers and co-authored the CORBA Dynamic Scheduling Standard. She has received notable awards including the Marie Curie Fellowship and best paper recognitions at IPDPS and SAINT conferences. Her work is supported by grants from the ERC, EU, NSF, and industry partners like SUN and Nokia. She has organized major conferences and serves on editorial boards for journals such as Transactions on Mobile Computing and Peer-to-Peer Networking. Education: PhD in Computer Science, University of California, Santa Barbara (2000) M.S. in Computer Science, University of Crete (Greece) B.S. in Computer Science, University of Crete (Greece) Research Interests: Prof. Kalogeraki explores distributed systems, real-time processing, and edge computing applications. Her work emphasizes resource management, fault-tolerance, and sensor network middleware. Recent projects include serverless computing optimizations, privacy-preserving mobile cloud frameworks, and anomaly detection in IoT environments. She also contributes to diversity initiatives in database conferences. Awards and Honors: Marie Curie Fellowship Best Paper Awards at IPDPS 2009 and SAINT 2008 Best Student Paper Award at SAINT 2011 UC Regents Fellowship Award ERC Starting Independent Researcher Grant Grants and Collaborations: Her research is funded by the European Union (including Thalis and Aristeia grants), NSF, and industry partnerships. She has led projects on edge AI, serverless pipelines, and participatory sensing systems. Labs and Teams: She directs the Distributed and Real-Time Systems Lab at Athens University, focusing on real-time distributed applications and edge computing innovations.

Michael GrossniklausView profile

Professor

• Data Management
• Information Systems
• Stream Processing
• +3 more

Michael Grossniklaus is Professor for Databases and Information Systems at University of Konstanz's Department of Computer and Information Science. His research develops data management and processing technologies supporting data science applications, with emphasis on stream processing, context-aware systems, and web engineering solutions. Key research areas: Continuous query processing for streaming data Context-aware mobile data management Machine learning for database optimization Multi-channel web information systems Semantic web and RDF stream processing Publications demonstrate sustained contributions to database query processing, with recent work focusing on cardinality estimation using geometric deep learning and cloud database optimization. Developed C-SPARQL language extension for continuous RDF stream queries.

• Information Security
• Blockchain Technology
• Middleware Systems
• +7 more

Rebecca Montanari is a Full Professor at the University of Bologna's Department of Computer Science - Science and Engineering since 2020, and currently serves as Vice-Rector for Digital Transformation. Her research focuses on information security, middleware for mobile/pervasive systems, blockchain applications in supply chains (agri-food, manufacturing, fashion), and security systems for Industry 4.0. She holds a PhD in Electronic and Computer Engineering (2001) from the University of Bologna. Key contributions include leadership in projects like SACHER (Smart Architecture for Cultural Heritage), CHIMERA, and IPPODAMO, emphasizing blockchain integration, IoT security, and federated learning. She coordinates initiatives such as IDEHA (data processing in Cultural Heritage) and SmartChain (interoperable industrial supply chain systems). Montanari also serves on editorial boards for journals like Security and Communication Networks and Electronics , and actively reviews for top-tier conferences in her field. Her work bridges academia and industry through collaborations on edge computing, cyber-physical systems, and privacy-aware technologies. Current efforts emphasize trustworthy federated learning frameworks and decentralized identity solutions for IoT ecosystems.

Apostolos ZarrasView profile

Professor

• Software Architecture
• Software Design
• Software Evolution
• +7 more

Apostolos Zarras is a Professor in the Department of Computer Science & Engineering at the University of Ioannina, Greece. He has been with the institution since 2002, progressing from Visiting Professor to full Professor in 2022. His academic journey includes a Ph.D. from the University of Rennes 1, France (2000), an M.Sc. from the University of Crete (1996), and a B.Sc. from the same institution (1994). Education: Ph.D. in Computer Science, University of Rennes 1, France (1996–1999) M.Sc. in Computer Science, University of Crete, Greece (1994–1996) B.Sc. in Computer Science, University of Crete, Greece (1990–1994) His research centers on software engineering, with a focus on software architecture, design patterns, software evolution, middleware, and service-oriented computing. He explores quality aspects of software systems, including refactoring, schema evolution, and dependable systems. His work often bridges theoretical models with practical applications in distributed and pervasive environments. The recent publications reflect a strong trend in software evolution, particularly schema evolution in databases, refactoring patterns, and the empirical study of design patterns (e.g., GoF patterns) in real-world systems. Themes such as anti-patterns, tool support for refactoring, and naming conventions in SQL are recurrent, indicating a deep interest in improving software quality through structured design and evolution practices. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: Apostolos Zarras has supervised over 17 B.Sc. theses, more than 12 M.Sc. theses, and one Ph.D. thesis. He has served as a principal investigator in several EU and national R&D projects, including the ForeverSOA INRIA project and the CHOReOS FP7 ICT IP project. His professional service includes extensive reviewing for top journals (IEEE TSE, CACM, etc.) and participation in program committees of major conferences (ICSE, FSE, Middleware, ER). Labs and Teams: He has collaborated with the ARLES Group at INRIA Rocquencourt, France, during multiple visiting researcher stays (2005–2008). His research is conducted within the Department of Computer Science & Engineering at the University of Ioannina, where he contributes to graduate studies and academic dissemination.

Sandro PedrazziniView profile

Adjunct Professor

• Software Engineering
• Programming Languages
• Natural Language Processing
• +5 more

Sandro Pedrazzini is an Adjunct Professor in Software Engineering and the Head of the Bachelor's Program in Computer Engineering at the Department of Innovative Technologies (DTI) of SUPSI. He holds an M.Sc. in Computer Science from ETH Zurich and a Ph.D. in Natural Sciences from the University of Basel. His research focuses on Software Engineering methodologies, Programming Languages, Natural Language Processing, and Information Retrieval. He has extensive experience in both academia and industry, co-founding companies like Canoo AG and Karakun AG. His teaching responsibilities include courses on computer graphics, programming paradigms, and software engineering practices. Research Interests: Software Engineering: Agile methodologies, continuous integration, and project-based learning Natural Language Processing: Term extraction, morphological analysis, and e-learning tools Web Technologies: 3D interfaces, enterprise systems, and middleware architectures Publications reflect a blend of theoretical and applied research, with contributions to enterprise search systems, semantic analysis, and educational technologies. His work emphasizes practical applications of academic research in real-world contexts. Professional Experience: Co-founder of Canoo AG (2000) and Karakun AG (2018) Head of Computer Science Bachelor Program since 2012 Supervisor for multiple academic projects and courses Labs/Teams: Active in SUPSI’s DTI department, leading projects like 3D MMA (3D interface design) and TicinoTurismo II (web-based tourism platform).

Hamid MukhtarView profile

Associate Professor

• Deep Learning
• Natural Language Processing
• Health Informatics
• +7 more

Hamid Mukhtar is an Associate Professor in the School of Computer Science at the University of Birmingham, Dubai campus. His academic work spans research, teaching, and industry collaboration in computer science with a focus on intelligent systems and healthcare applications. His educational background includes: PhD in Computer Science, 2009 (National Institute for Telecommunications, France) MSc in Computer Science (French), 2006 MSc in Computer Science, 2005 BSc in Computer Science, 2003 Dr. Mukhtar's research interests center on deep learning, natural language processing, health informatics, and human behaviour modelling in pervasive environments . His work integrates machine learning with real-world applications in healthcare, wellness, and intelligent user interfaces. He has published extensively on topics including persuasive technology, IoT for health monitoring, and NLP for social and medical data. The recent trend in his publications shows a strong focus on applying AI to public health challenges—such as diabetes prediction, depression detection, and pandemic response—using data from electronic records, wearables, and social media. His interdisciplinary approach bridges computer science with healthcare and behavioral science. He actively supervises master's students and has engaged in industry collaborations and consultancy in data science, software usability, and mobile technologies. He also conducts professional workshops on NLP, Android development, and web technologies. Dr. Mukhtar has taught a wide range of computer science courses including operating systems, AI, NLP, databases, web engineering, and professional ethics.

Zheng SongView profile

Assistant Professor

• Distributed Systems
• Edge Computing
• Middleware
• +7 more

Zheng Song is an Assistant Professor in the Department of Computer and Information Science at the University of Michigan–Dearborn College of Engineering and Computer Science . He holds two PhDs: one in Distributed Systems and Software Engineering from Virginia Tech (2020) and another in Wireless Networking and Mobile Computing from Beijing University of Posts and Telecommunications (2015). His research focuses on middleware solutions for edge computing , service-oriented architecture , and distributed systems . PhD, Virginia Tech (2020) PhD, Beijing University of Posts and Telecommunications (2015) MS, China Agricultural University (2009) BS, China Agricultural University (2007) Zheng's research spans edge computing , distributed systems , privacy-preserving algorithms , and computer science education . His work includes QoS-consistent edge services , microservice orchestration , and AI-driven birdwatching applications like Robin , which was featured in multiple 2025 publications. Recent publications highlight Zheng's expertise in machine learning (IEEE SMC'25), web service integration (Empirical Software Engineering, 2025), and edge computing frameworks (IEEE Edge'19 Best Paper, NSF CRII grant 2021). His 15 most recent works demonstrate leadership in QoI-aware systems , privacy , and innovative teaching methodologies . NSF CRII Research Grant (2021) Best Paper Award, IEEE Edge 2019 Distinguished Paper Award, IEEE ICDCS 2024 2nd Place, ACM Student Research Competition 2015 CECS Teaching Excellence Award 2025 Zheng mentors students in MQTT middleware , serverless computing , and generative AI in education . His Pervasive Computing Lab has produced impactful projects like Robin (Best Senior Design Project 2025) and Blaze (fire safety system). Former students have been admitted to Georgia Tech , University of British Columbia , and UM-Ann Arbor .