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Ana MilanovaView profile

Professor

• Programming Languages
• Compilers
• Software Engineering
• +6 more

Dr. Ana Milanova is a Professor in the Department of Computer Science at Rensselaer Polytechnic Institute, where she has been since 2003. Her research focuses on programming languages, compilers, and software engineering, with emphasis on static program analysis, security, and applications in Android app taint analysis, secure cryptographic protocols, and machine learning library verification. Research Interests: Her work addresses challenges in secure software development, privacy-preserving techniques, and static analysis methodologies. Recent projects include federated learning frameworks, Python-based static analysis tools, and secure computation protocols. She has contributed to tools like Submitty for automated programming assignment grading and frameworks for secure MapReduce applications. Scientific Awards: NSF CAREER Award, Google Faculty Research Award Grants: SaTC: CORE grants for secure computation and multi-party optimization Labs/Teams: Leads research in secure computation, federated learning, and static analysis tool development. Collaborates on open-source platforms for educational grading systems (Submitty).

• Big Data Analytics
• Cloud Computing
• Data Stream Processing
• +4 more

Yanlei Diao is a Professor of Computer Science at École Polytechnique (France) with a joint appointment at the University of Massachusetts Amherst. She received her PhD from UC Berkeley in 2005. Her research focuses on scalable data systems, particularly in big data analytics, cloud computing optimization, and real-time stream processing. Research Interests: Her work spans cloud infrastructure optimization (UDAO project), explainable anomaly detection in data streams (EXAD), interactive data exploration (AIDEme), genomic data analysis (GESALL), and uncertain data management (CLARO). She leads the CEDAR team at Inria/LIX focusing on cloud-scale data exploration. Awards & Honors: ERC Consolidator Grant (2017-2023) CRA-W Borg Early Career Award (2013) NSF CAREER Award (2008) Keynote speaker at ACM DEBS 2021 and SWIFT 2023 AI Forum Best Paper Award at SIGMOD 2011 ACM SIGMOD Dissertation Honorable Mention (2005) Advising & Leadership: Mentored over 20 PhD students and postdocs, currently supervising 7 researchers. Served as PVLDB PC Co-Chair (2025-2026) and ACM SIGMOD Editor-in-Chief (2014-2019). Leads multiple projects with industry partners including Alibaba Cloud.

Jennifer Wong-MaView profile

Teaching Professor

• Computer Science Education
• Undergraduate Education Tools
• Wireless and Distributed Embedded Systems
• +3 more

Jennifer Wong-Ma is an Associate Teaching Professor at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information and Computer Sciences and the Computer Science Department. She joined UCI in 2018, previously serving as teaching faculty at Stony Brook University. Her roles include Vice Chair of Undergraduate Studies and advisor for organizations like Women in Information and Computer Sciences (WICS). She holds a Ph.D. in Computer Science from UCLA, with prior research focused on wireless systems and hardware IP protection. Education: Ph.D., Computer Science, University of California, Los Angeles, 2006 Research & Teaching Interests: Development of learning and teaching tools for CS education Alternative assessment strategies and pedagogical innovation CS education equity and retention initiatives Integration of theater techniques in classroom engagement Key Contributions: Co-founded the Coffee Meets Teaching program to foster faculty collaboration Member of UCI’s inaugural Faculty Academy for Teaching Excellence (FATE) Advocate for women in technology through WIT@UCI and WICS mentorship Awards: CS Department Award for Undergraduate Education (2012) CS Department Award for Major Contributions to Undergraduate Education (2016) Honored at 2023 ICS Awards Celebration Her work emphasizes community-building in education, bridging academia and industry, and leveraging technology to enhance student success. Current projects include optimizing grading infrastructure and predictive modeling for academic retention.

Mirel CosulschiView profile

Associate Professor

• Algorithms and Complexity
• Software Engineering
• Web Data Management
• +13 more

Mirel Cosulschi is an Associate Professor in the Department of Computer Science at the University of Craiova, Romania, where he has been a faculty member since 1997. He is affiliated with the Faculty of Automation, Computers and Electronics and teaches courses in Graph Algorithms, Software Engineering, Web Data Management, and Fundamentals of Programming at both undergraduate and master's levels. PhD in Computer Science, University of Craiova, 2006 MSc in Artificial Intelligence, University of Craiova, 1998 BSc in Computer Science, University of Craiova, 1997 His research interests include algorithms and complexity, software engineering, web data management, semantic web, distributed programming, and cloud computing. He has supervised numerous BSc and Master’s theses focusing on web applications, mobile development, data processing, and software modeling. His teaching emphasizes algorithmic thinking, structured programming, and modern software development practices. While no formal scientific publications are listed, his academic contributions include authored textbooks such as Algoritmica grafurilor si aplicatii (2014) and Practica programarii in C (2014), indicating active engagement in curriculum development and educational materials. He is involved with the MSDN Academic Alliance and utilizes tools like Windows Installer MSI and Advanced Web Ranking. Mirel Cosulschi has advised over 100 students in thesis projects related to software development, data management, and web technologies. Although no external grants or awards are mentioned, his long-standing academic career and consistent supervision reflect sustained scholarly activity. He maintains a professional web presence at http://inf.ucv.ro/~mirel and can be contacted via email at mirelc@central.ucv.ro . He is currently active in teaching and academic supervision, with no indication of retirement or part-time status.

• Computer Networking
• Software-Defined Networking (SDN)
• Distributed Systems
• +3 more

Mario Baldi is a researcher affiliated with the Polytechnic University of Turin, Italy , with significant contributions to computer networking , distributed systems , and software-defined networking . Key research themes: network function virtualization , programmable dataplanes , time-driven scheduling , and traffic analysis . Recent work focuses on RDMA-enabled compute offloading (2023) and DNN inference in network data planes (2023). Longstanding expertise in multicast routing , voice/data packet efficiency , and XML-based protocol parsing (2000–2006). Collaboration network includes Yoram Ofek , Fulvio Risso , and Han Hee Song , with 99+ publications spanning 1994–2023.

• Parallel algorithms
• Distributed databases
• MapReduce model
• +5 more

Mostafa BAMHA is an Associate Professor (Maître de Conférences) at the University of Orleans, affiliated with the LIFO Laboratory (Laboratoire d'Informatique Fondamentale d'Orléans). He leads research in parallel and distributed computing, focusing on MapReduce optimization , data skew handling , and scalable graph processing . Member of the PRV team (Parallelism, Virtual Reality, System Verification) Active in projects: HPIAF (High Performance computing for AI in Finance) INEx (Cloud Computing experiments) Girafon (Graph & BigData processing) Research Trends His publications from 2018–2024 show focus on: MapReduce optimizations for join operations and LSH similarity joins Graph processing challenges in Pregel with high-degree vertices Skew-insensitive algorithms across distributed architectures Academic Contributions Co-author in 15+ peer-reviewed publications (2000–2024) including International Journal of Parallel Programming , DEXA , and HLPP conferences. Key collaborators: Sébastien Rivault , Mohamad Al Hajj Hassan , Sophie Robert .

Roland YAP Hock ChuanView profile

Associate Professor

• Artificial Intelligence
• Constraints
• Data Analytics
• +4 more

Roland YAP Hock Chuan serves as an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS), and previously held the role of assistant director at The Logistics Institute Asia Pacific (TLI-AP). His academic foundation was built at Monash University, Australia, where he earned comprehensive qualifications in Computer Science. Education: Ph.D. in Computer Science, Monash University, Australia M.Sc. in Computer Science, Monash University, Australia B.Sc. (Honours) in Computer Science, Monash University, Australia Research Focus: Renowned for pioneering the CLP(R) system that revolutionized Constraint Programming, Prof. Yap's work now spans artificial intelligence, security, programming languages, and social networks. His research bridges theoretical rigor with real-world applications, particularly in data analytics and knowledge compilation for industrial systems. Publication Evolution: His scholarly output reveals a strategic progression from foundational constraint logic programming (1990s) to cutting-edge security mechanisms and AI-driven solutions (2010s). Recent works demonstrate expertise in robust search algorithms, memory protection systems, and social network defense strategies, reflecting continuous adaptation to emerging computational challenges. Scientific Recognition: Best student paper award at SCA 2011 for social network research Best student runner-up paper at CIKM 2009 1995 Australian Computer Science Ph.D. Prize (1996) Praxa Computer Prize for theoretical computing achievements (1985) Academic Leadership: Prof. Yap directs the Tier 1 research project 'Investigating Product Configuration as Knowledge Compilation,' developing accelerated industrial solvers through innovative KC integration. His teaching portfolio includes advanced security courses (CS4239/5439/6231), shaping next-generation cybersecurity expertise. Mentoring excellence is evidenced by multiple student award-winning publications in top-tier conferences. Collaborative Infrastructure: Through his leadership role at TLI-AP, he contributes to NUS's interdisciplinary logistics research ecosystem, connecting computer science with supply chain innovation and operational optimization challenges.

• Algorithms
• Complexity Theory
• Optimization
• +5 more

Ioannis Milis is a Professor at the Department of Informatics, Athens University of Economics and Business (AUEB), part of the School of Information Sciences and Technology. He holds a BS in Electrical Engineering from Democritus University of Thrace (1983) and a PhD in Computer Science from AUEB (1989). His research focuses on algorithms, computational complexity, and optimization for computer/communication networks, combinatorial optimization, graph theory, and game theory. He has conducted postdoctoral research at LRI (1992-94), INRIA-Sophia Antipolis (1994-95), and NTUA as a Marie Curie fellow (1995-96). His teaching includes courses on Algorithms, Advanced Algorithms, and Topics in Algorithms at both undergraduate and graduate levels. He co-authored a textbook on Distributed Systems with Java (2005). His conference involvement includes organizing the Athens Colloquium on Algorithms and Complexity (ACAC) since 2006, the Euro-Par 2012 conference, and the ISCO 2012 symposium. His research has addressed scheduling algorithms, energy-efficient computing, and combinatorial optimization problems in networks.

Pradip K SrimaniView profile

Professor

• Parallel and Distributed Computing
• Interconnection Networks
• Self-Stabilizing Systems
• +2 more

Pradip K Srimani is a Professor at the School of Computing , Clemson University , with research focus on Parallel and Distributed Computing , Self-Stabilizing Systems , and Graph Theory Applications . He is an IEEE Life Fellow and ACM Distinguished Scientist with over 250 publications. Research Interests Self-stabilizing algorithms for network graphs Ontology-based biomedical information retrieval High-performance computing resource management Biologically inspired distributed algorithms Network topology computation Recent publications demonstrate expertise in token circulation protocols, genome assembly frameworks, and semantic similarity measurement. He has served on program committees for APDCM , GPC-2018 , and IEEE BigMM conferences, while maintaining editorial roles at International Journal of High Performance Computing and Journal of Big Data . Scientific Awards IEEE Life Fellow ACM Distinguished Scientist

Kyoung-Don KangView profile

Professor

• Real-time embedded systems
• Cyber-physical systems
• Internet of Things
• +4 more

Kyoung-Don (KD) Kang is a Professor in the School of Computing at Binghamton University, State University of New York. He specializes in real-time embedded systems, cyber-physical systems, and IoT security. His research focuses on enhancing real-time data services' timeliness and power efficiency, supported by NSF grants and industry collaborations. Education: BS, MS (Kyungpook National University); MS, PhD (University of Virginia). Research Interests: Real-time embedded systems, cyber-physical systems, IoT, security, edge computing, and wireless sensor networks. His work emphasizes control-theoretic approaches, feedback mechanisms, and adaptive algorithms for real-time systems. Grants & Projects: NSF-funded projects include 'Enhancing Timeliness of Real-Time Data Services' and 'QoS-Aware Data Management.' He leads the Real-Time Embedded Systems Laboratory, developing frameworks like Chronos and RTMR. Awards: Best Paper nominations (DCOSS'19), NSF grants, and patents in surveillance systems. Over 16 MS students and 9 PhD students have graduated under his mentorship, many joining top tech firms. Labs & Teams: Director of the Real-Time Embedded Systems Lab, focusing on edge computing, real-time stream processing, and secure IoT applications. Collaborates with industry partners like Samsung and Intel.

Chatziantoniou DamianosView profile

Professor

• Big Data Systems
• Business Intelligence
• Large-Scale Analytics
• +5 more

Professor Chatziantoniou Damianos holds a position at the Athens University of Economics and Business (AUEB) within the Department of Management Science and Technology (DMST), School of Business. He earned a B.Sc. in Applied Mathematics from the National & Kapodistrian University of Athens (1991), M.Sc. from New York University's Courant Institute of Mathematical Sciences, and a Ph.D. from Columbia University. His research focuses on big data systems, business intelligence, query processing, and real-time data analysis, with contributions influencing commercial database systems like Microsoft SQL Server and Oracle. As Director of AUEB's Master’s program in Business Analytics and Big Data, he previously served as an Assistant Professor at Stevens Institute of Technology (1997–1999). His industry collaborations include co-founding Panakea Software and VoiceWeb SA, and consulting roles at Aster Data Systems (now Teradata). He leads big data projects for companies like Cosmote, Piraeus Bank, and HEDNO. His research has been published in top venues including VLDB, ICDE, and SIGMOD, emphasizing practical applications in large-scale analytics and OLAP systems. He advises on strategic partnerships for the MSc program and maintains an active role in academic administration, including steering committees and quality assurance initiatives.

Michela TauferView profile

Associate Professor

• Heterogeneous Computing
• Cloud Computing
• Volunteer Computing
• +4 more

Michela Taufer is the David L and Beverly JC Mills Chair of Computer and Information Sciences and an Associate Professor at the University of Delaware. She earned her Masters degrees in Computer Engineering from the University of Padova (Italy) and her doctoral degree in Computer Science from the Swiss Federal Institute of Technology (Switzerland). Her research interests include scientific applications and their advanced programmability in heterogeneous computing (i.e. multi-core and many-core platforms, GPUs); performance analysis; modeling and optimization of multi-scale applications on heterogeneous computing; cloud computing and volunteer computing; numerical reproducibility and stability of large-scale simulations on multi-core platforms; and big data analytics and MapReduce. Dr. Taufer has published research on protein folding, molecular dynamics, and workflow execution on cloud and grid platforms. Her work often focuses on performance characterization and optimization of scientific applications on distributed and parallel systems. From 2003 to 2004 she was a La Jolla Interfaces in Science Training Program (LJIS) Postdoctoral Fellow at the University of California San Diego (UCSD) and The Scripps Research Institute (TSRI) From 2005 to 2007, she was an Assistant Professor at the Computer Science Department of the University of Texas at El Paso (UTEP) She joined the University of Delaware in 2007 as an Assistant Professor and was promoted to Associate Professor with tenure in 2012

Charles ReissView profile

Assistant Professor

• Computer Science Education
• Computer Systems
• Cloud Computing
• +3 more

Charles Reiss is an Assistant Professor in the Computer Science Department at the University of Virginia, focusing on teaching and research in computer systems and education. He holds a PhD from UC Berkeley (2016) and has a strong background in computer architecture and distributed systems. His research interests include computer science education methodologies, cloud computing, and systems optimization. Education: B.S. Computer Science (Georgia Tech, 2008), M.S. Computer Science (UC Berkeley, 2011), Ph.D. Computer Science (UC Berkeley, 2016). Teaching: Reiss has taught courses such as CS 3130 (Computer Systems and Organization), CS 3330 (Computer Architecture), and CS 4630 (Defense Against the Dark Arts). His courses emphasize hands-on learning with tools like HCLRS, an educational hardware description language. Awards: Winner of the SoCC 2021 Test of Time Award for work on Google cloud trace analysis. Contributions: Developed educational software like HCLRS and CPU cache exercises. Active in curriculum design for computer systems and security education.

• Logic Programming
• Knowledge Representation
• Graph Databases
• +7 more

Ana Edelmira Pasarella Sanchez is a Professor in the Department of Computer Sciences at the Faculty of Mathematics and Statistics, Universitat Politècnica de Catalunya (UPC). She is a member of the ALBCOM research group, focusing on algorithms, bioinformatics, complexity, and formal methods. Her work bridges theoretical computer science with practical data systems. PhD in Computer Science, Universitat Politècnica de Catalunya Her research centers on logic programming, knowledge representation, and graph databases. She explores how formal methods can enhance data processing, particularly through dynamic pipelines and trust-aware access control. Her work integrates Datalog, semantic reasoning, and big data frameworks to improve scalability and correctness in knowledge systems. She has contributed to foundational semantics of logic programs and their applications in security and data integration. Her recent publications highlight a trend toward efficient, adaptive data processing systems, especially for graph analytics and knowledge graphs. She compares paradigms like MapReduce and pipelining, advocating for dynamic, functional approaches to big data. Her work increasingly addresses real-world challenges in federated knowledge graphs and access control. SACMAT 2017 Best Paper Award Pasarella has been involved in multiple competitive R&D+i projects, such as 'Modelos y Técnicas para el Procesamiento de Información a Gran Escala' and 'Modelos y métodos basados en grafos para la computación en gran escala,' indicating sustained funding and collaborative leadership. She advises on research direction within her group and mentors through collaborative publications. She has served on the scientific committee of the Latin American Informatics Conference (CLEI), contributing to the broader academic community. She is part of the ALBCOM research group and collaborates extensively with researchers like Fernando Orejas, Maria-Esther Vidal, and Elvira Pino, working on logic-based frameworks for data and security systems.

İBRAHİM RIZA HALLAÇView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Parallel and Distributed Systems
• +3 more

İbrahim Rıza Hallaç is an Assistant Professor at RAFET KAYIŞ FACULTY OF ENGINEERING, Department of Computer Engineering. He holds a PhD (2021), Master's (2014), and Bachelor's (2011) in Computer Engineering from Firat University, with doctoral research on social media analysis using deep learning methods under advisor Galip Aydın. His research focuses on: Artificial Intelligence and language models Machine learning for distributed systems Big data analytics and cloud computing Natural language processing applications Social media sentiment analysis Radar-based object detection systems His publications (2015-2024) demonstrate consistent focus on machine learning applications across diverse domains including social network analysis, distributed computing, Turkish NLP, and sensor data processing. Recent works emphasize radar-based multi-target detection (2024), credit scoring models (2023), and wind speed estimation (2023), reflecting expertise in scaling AI solutions for real-world problems. He has led four national R&D projects: Deep Learning-Based Face Recognition Authorization System (2017-2019) DEĞİRMEN Big Data Analysis Platform for Turkish Armed Forces (2017-2021) KOSGEB Innovation Program for Face Recognition Systems (2017-2019) Cloud-Based Social Media Reputation Analysis System (2015-2017) No students, awards, or contact emails are documented in available records.