جست‌وجوی استاد و پژوهشگر

Shiva Jahangiriمشاهده پروفایل

استادیار

• Big Data Management Systems
• Databases for AI/ML
• Knowledge Graphs
• +۶ مورد دیگر

Shiva Jahangiri is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University's School of Engineering. His research focuses on Big Data Management Systems, Databases for AI/ML, and Query Optimization. He leads the DBIS Lab, which explores database internals, vectorized data processing, and open-source projects like Apache AsterixDB. Education: Ph.D. in Computer Science from the University of California, Irvine; M.S. in Computer Science (Data Science) from the University of Southern California. Current courses taught include Advanced Programming, Advanced Database Systems, and Introduction to Database Systems. He advises Ph.D. and Master’s students on topics like Vector Databases, Query Scheduling, and Resource Management. Recent research trends involve optimizing group-by/aggregation operators, schema inference for semi-structured data, and memory management in complex join queries. His work bridges theoretical advancements with practical implementations in open-source systems. DBIS Lab activities include student participation in senior design projects, directed research, and volunteer roles. The lab emphasizes industry collaboration for hands-on experience in database systems development.

Farah Kamwمشاهده پروفایل

استادیار

• Information Visualization
• Visual Analytics
• Spatial-Temporal Data Analysis
• +۴ مورد دیگر

Farah Kamw is an Assistant Professor in the Department of Computer Science at Wayne State University. With a PhD in Computer Science (2019) from Kent State University, her expertise spans 18 years of software development, academic teaching, and research in information visualization and database management. Education : PhD (Kent State), MSc (University of Zakho), BSc (University of Baghdad) Her research focuses on Information Visualization and Visual Analytics of spatial-temporal data, particularly through 8 publications (2013-2021) addressing urban mobility patterns, trajectory analysis, and geospatial data integration. She has developed several open-source visual analytics tools including TrajAnalytics and SparseTrajAnalytics, applying both document and graph database techniques. Farah teaches core Computer Science courses such as Algorithm Design , Programming Languages , and Database Systems . Her technical skills include Python, C++, Java, SQL, NoSQL databases, and GIS technologies.

Pascal Bizarroمشاهده پروفایل

دانشیار

• Accounting Information Systems
• IT Auditing
• Information System Assurance & Control
• +۷ مورد دیگر

Pascal Bizarro, Ph.D., is an Associate Professor in the Department of Accounting and Information Systems at Bowling Green State University (BGSU), part of the Schmidthorst College of Business. He holds a Ph.D. and M.Acc. from the University of Alabama and a B.B.A. in Commercial Engineering from HEC, Liège, Belgium. A Certified Information Systems Auditor (CISA), he specializes in IT Auditing, Accounting Information Systems, and emerging technologies like blockchain. He advises BGSU's Information System Audit and Control (ISAC) programs and serves as president of the Northwest Ohio ISACA Chapter and academic board member of the Northwest Ohio IIA Chapter. Dr. Bizarro's research focuses on cybersecurity, audit technology, data privacy, and blockchain applications in accounting. His work has been published in leading journals such as ISACA Journal , Internal Auditing , and The CPA Journal . Notable contributions include studies on phishing attacks, IoT security, AI in auditing, and XBRL implementation. He has received awards including the Schmidthorst Leadership Council Faculty Excellence Award (2015) and the Primrose Family Professorship (2013–present). His professional certifications and academic leadership roles reflect his expertise in bridging accounting practices with information systems innovation.

• Big Data Analytics
• Machine Learning
• Data Mining
• +۷ مورد دیگر

Dr. Sikha S Bagui is a Distinguished University Professor in the Department of Computer Science at the Hal Marcus College of Science and Engineering, University of West Florida . She served as the former Chair of Computer Science and was the Founding Director of the Center for Cybersecurity . Her research spans database design, Big Data analytics, machine learning, and cybersecurity . Research Focus: Machine Learning, Data Mining, Network Traffic Analysis, Graph Databases, and Resampling Techniques for Imbalanced Data Awards: Askew Fellow (2018–2021), multiple Excellence in Teaching and Distinguished Research Awards (2001–2024) Contributions: Authored books on databases/SQL (translated internationally), developed the UWF-ZeekData datasets for cybersecurity research, and served as Associate Editor for multiple journals Tools & Frameworks: Active in Hadoop, Spark, Memgraph, and MITRE ATT&CK-based threat modeling Publication Trends: Recent work focuses on MITRE ATT&CK datasets , graph-based cybersecurity , resampling rare attacks , and educational impacts in computing . Her research bridges theoretical and applied domains, including clinical decision support systems and K-12 computer science education. Scientific Awards: Askew Fellow (Reubin O’D. Askew Institute for Multidisciplinary Studies, 2018–2021) Excellence in Teaching and Advising Award (UWF, 2012) Distinguished Research and Creative Activities Award (UWF, 2007, 2012) Excellence in Undergraduate Teaching and Advising Award (UWF, 2001–2006) Leadership & Service: Directed the Center for Cybersecurity, contributed to journals as Associate Editor, and engaged in initiatives like NCWIT Aspirations in Computing and the Association for Women in Computing.

Joydeep Banerjeeمشاهده پروفایل

استاد مدعو

• Observability
• Distributed Computing
• Cloud Migration
• +۸ مورد دیگر

Joydeep Banerjee is an Adjunct Professor in the Department of Data Sciences and Operations at the Marshall School of Business, University of Southern California. He combines academic expertise with extensive industry experience as a Senior Technical Leader at Red Hat, former technology strategist at The Walt Disney Studios, and key project leader during his tenure at IBM. Current focus areas: Observability, Far Edge & Scalability at Red Hat Pioneered cloud migration and microservices implementation at Disney Studios Expertise in distributed computing, streaming analytics, and J2EE technologies from IBM experience His research interests center on applying AI/ML methodologies to observability challenges, while advocating for DevOps transformation and agile development practices. As an instructor, he teaches SQL and NoSQL database systems for business analytics, covering relational databases, distributed database architectures, and data manipulation techniques. Current course: DSO-552 SQL Databases for Business Analysts Previous course: DSO-553 NoSQL Databases in Big Data

Heikki Topiمشاهده پروفایل

استاد

• Systems Analysis & Design
• Data Management
• IS Education
• +۲ مورد دیگر

Dr. Heikki Topi is a Professor of Computer Information Systems at Bentley University. He serves as Associate Dean of Business and holds a Ph.D. in Management Information Systems from Indiana University. His research spans systems analysis, computing education, IoT, and usability. He co-authored foundational texts like Modern Database Management and contributes to global curriculum initiatives (e.g., IS2010, MSIS2016). Recent publications focus on agile methodologies, IoT research agendas, and competency-based IS education reform. No awards or student advisements are noted.

Shirley Cohenمشاهده پروفایل

استادیار

• Databases
• Data Warehousing
• Data Integration
• +۷ مورد دیگر

Shirley Cohen serves as an Assistant Professor of Instruction in the Department of Computer Science within the College of Natural Sciences at The University of Texas at Austin. She maintains an active concurrent position as Solutions Architect Manager at Google, demonstrating strong industry-academia connections. Dr. Cohen holds an M.S. in Computer Science from the University of Pennsylvania (2007) and an M.B.A. in Information Technology from Dalhousie University (2004). Her academic journey reflects a blend of technical expertise and business acumen. Her research and teaching interests center on practical database systems and data engineering, with particular focus on SQL, data warehousing, ETL processes, and cloud-based data solutions. She has developed and taught multiple courses including CS 327E (Elements of Databases), CS 329E (Elements of Data Integration), and CS 378 (Foundations of Data Warehousing) across numerous semesters from 2016 through projected 2025 offerings. Her pedagogical approach emphasizes hands-on learning with modern cloud technologies, particularly Google Cloud Platform services including BigQuery, Firestore, and Dataflow. She integrates contemporary tools like dbt, Lucidchart, and various NoSQL databases into her curriculum. Dr. Cohen's courses consistently incorporate active learning techniques, with students working in pairs on substantial projects that build comprehensive data pipelines from raw data ingestion through to visualization and analysis.

Michael Miorمشاهده پروفایل

استادیار

• NoSQL database design
• Data integration
• Schema management
• +۲ مورد دیگر

Michael Mior is an Assistant Professor in the Department of Computer Science at Rochester Institute of Technology's (RIT) Golisano College of Computing and Information Sciences, where he has served since 2018. He directs the Data Unity Lab and teaches core courses including Principles of Data Mining, Introduction to Big Data, and Advanced Database Skills for NoSQL/NewSQL systems. His educational background includes: BS in Computing Science, University of Ontario Institute of Technology (Canada) MS in Computer Science, University of Toronto (Canada) PhD in Computer Science, University of Waterloo (Canada) Dr. Mior's research centers on schema design and management and data integration for non-relational data , with expertise in NoSQL database optimization. He develops open-source tools like NoSE (automated schema design), JSONoid (schema discovery for JSON), and ESON (denormalized database normalization), addressing challenges in database evolution and semantic data understanding. His recent publications (2020-2023) reveal a strong focus on practical database tooling, with trends including schema evolution for NoSQL systems (CoDEvo), educational applications for relational theory (Relational Playground), and machine learning techniques for semantic data analysis. This work bridges theoretical database concepts with real-world big data scalability requirements. As director of the Data Unity Lab, Dr. Mior leads research on data management tooling while mentoring student projects. His GitHub activity (247 repositories, 5k+ stars) demonstrates active contributions to open-source database projects including Apache Calcite and JSON Schema tools. The Data Unity Lab develops key projects such as Locomotor (Redis script automation) and contributes to industry standards through affiliations with Sourcemeta Research and JSON Schema organizations.

Antonio E Badiaمشاهده پروفایل

دانشیار

• Database Systems
• Query Optimization
• Data Mining
• +۶ مورد دیگر

Antonio E Badia is an Associate Professor in the Department of Computer Science and Engineering at the University of Louisville's J.B. Speed School of Engineering. He holds a B.S. and M.S. in Computer Science from the Polytechnic University of Catalonia (1988, 1990) and a Ph.D. in Computer Science from Indiana University (1997). His research focuses on database systems, query optimization, data mining, and decision support systems. He has published extensively on topics such as JSON document algebra, SQL extensions for data science, and NoSQL system evaluation. Key research areas include query optimization frameworks, integration of unstructured data, and semantic technologies. His work bridges database systems with modern data science practices, emphasizing practical implementations and performance analysis. Notable contributions include pioneering work on generalized quantifiers in query languages and frameworks for data analysis in command-line environments. Dr. Badia's publications span over three decades, addressing challenges in data warehousing, information integration, and security-aware database design. Though no specific awards are listed, his prolific and impactful research contributions are evident through his sustained output in top venues. He has advised numerous students (none explicitly listed) and contributed to course development in computer science and engineering. His recent work explores the intersection of databases and emerging technologies like JSON processing, while maintaining a focus on foundational issues such as functional dependencies and query semantics. Ongoing projects likely involve advancing database architectures for modern analytical workloads.

Michael McGuireمشاهده پروفایل

استادیار

• Computer Science
• Data Mining
• Environmental Informatics
• +۳ مورد دیگر

Michael McGuire is an Assistant Professor in the Department of Computer and Information Sciences at Towson University's College of Science and Mathematics. He holds a Ph.D. in Information Systems from the University of Maryland, Baltimore County (2010), with supporting degrees in Information Systems (MS, 2005) and Geography & Environmental Planning (BS, 1996). Education: Ph.D. & MS in Information Systems (UMBC), BS in Geography (Towson) Department: Computer and Information Sciences School: College of Science and Mathematics Email: mmcguire@towson.edu His research focuses on spatio-temporal data mining , sensor database systems , and environmental informatics applications. Current work examines deep learning approaches for climate prediction , including convolutional neural networks for tornado day forecasting and transformer models in hurricane intensity analysis. Earlier publications explore information visualization through eye-tracking studies and multi-criteria decision systems for route planning. Recent publications highlight machine learning applications in environmental contexts, with 2024 studies on knowledge graphs and 2023 work on federated learning . The 2022 tornado prediction papers demonstrate CNN capabilities in meteorological modeling, while 2021 eye-tracking research shows feature engineering approaches for visual processing tasks. Dr. McGuire's technical expertise spans distributed database systems , cloud computing architectures , and human-computer interaction through eye gaze analysis. His 2018-2020 publications compare SQL/NoSQL storage for climate data and develop safe route planning algorithms using Fuzzy TOPSIS and other decision frameworks.

Fatemeh Ahmadi Abkenariمشاهده پروفایل

استاد مدعو

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۴ مورد دیگر

Fatemeh Ahmadi Abkenari is an Adjunct Professor in the Department of Computer Science at New York Tech , Vancouver campus. Her expertise spans Machine Learning , Deep Learning , Natural Language Processing , and Cybersecurity . With over a decade of teaching experience, she has instructed undergraduate, graduate, and doctoral students in computer engineering courses. Joined New York Tech: 2024 Education: Ph.D. Her research focuses on enhancing opinion spam detection in tourism reviews and improving Intrusion Detection Systems via hybrid machine learning models. She also explores domain-specific web search engines, aspect elicitation in customer reviews, and software quality compliance for health systems. Recent publications address topics such as overfitting mitigation , feature reduction in cybersecurity, and clickstream-driven web crawling . She is proficient in Python/R programming , AWS Cloud Security , SQL/NoSQL databases , and tools like Power BI and Tableau . Abkenari serves as a reviewer for journals such as Springer Neural Processing Letters and IEEE Access . She has contributed to projects involving sentiment mining , web page ranking optimization , and network protocol simulation , reflecting her interdisciplinary expertise in AI and cybersecurity.

• Database Systems
• Information Integration
• Service-Oriented Computing
• +۳ مورد دیگر

Michael Carey is a Professor specializing in database systems and distributed computing. His research focuses on database systems, information integration, service-oriented computing, middleware, and performance evaluation. He has contributed to projects like Apache AsterixDB, a scalable open-source database management system. Education: Ph.D. in Computer Science from UC Berkeley (1983), M.S. in Electrical Engineering (Computer Engineering) from Carnegie-Mellon University (1981), and B.S. in Electrical Engineering and Mathematics from Carnegie-Mellon University (1979). Research interests include next-generation databases, data mining, big data management, and declarative data processing. His recent work emphasizes optimizing big active data systems, memory management in join queries, and scalable NoSQL benchmarks. Notable projects include SQL++ language enhancements and the CH3 benchmark for NoSQL systems. He has received the 2016 IEEE TCDE Impact Award for contributions to data engineering. His grants include NSF-funded projects on big data systems and collaborative research in scalable analytics. Key contributions include Apache AsterixDB, a community-driven platform for big data research, and frameworks for large-scale machine learning integration with databases. His work bridges theory and practice, addressing challenges in distributed systems and real-time data processing.

Kulsawasd Jitkajornwanichمشاهده پروفایل

استادیار

• Computational Communication
• Social Media Analytics
• Natural Language Processing
• +۴ مورد دیگر

Kulsawasd Jitkajornwanich is an Assistant Professor in the Department of Professional Communication at Texas Tech University's College of Media and Communication. He holds a Ph.D. in Computer Science from the University of Texas at Arlington, with research focused on computational and data science applied to social media, environmental monitoring, and disaster management. His work integrates GIS, NOSQL databases, and AI techniques to address challenges in crisis communication, precision agriculture, and health misinformation detection. Education: Ph.D. in Computer Science, University of Texas at Arlington (2014) M.S. in Computer Science, University of Texas at Arlington (2009) B.S. in Computer Science, Chulalongkorn University (2004) Research Interests: Computational communication, social media analytics, NLP, big data visualization, and AI-driven solutions for environmental and health crises. His interdisciplinary approach bridges computer science with communication studies to foster impactful research in crisis management and science communication. Awards: 2021 Community Outreach Award for 'Tawai For Health' 2019 National Dissertation Award (Thailand) 2018 Faculty Research Visibility Award (KMITL) Teaching & Grants: Teaches courses like Big Data Analytics and Media Insights. Co-PI on a €93K EU grant (Erasmus+) for educational automation in Thailand. Advises graduate and undergraduate students across 2 PhD, 14 master’s, and 15 undergraduate projects, including a 'Best Paper Award' winner. Labs/Teams: Founded Texas Tech's Media Insights Lab (2023), focusing on computational communication and data-driven media strategies. Collaborates with Thai government agencies on disaster management and health initiatives.

Doina Carageaمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Data Science
• +۷ مورد دیگر

Doina Caragea is a Professor in the Department of Computer Science at Kansas State University, affiliated with the Carl R. Ice College of Engineering. She holds the Don and Linda Glaser Keystone Research Scholar title and is actively engaged in research and teaching in machine learning, deep learning, and data science. Education: Ph.D. in Computer Science, Iowa State University, 2004 M.S. in Computer Science, University of Bucharest, 1997 B.S. in Computer Science, University of Bucharest, 1996 Her research focuses on machine learning and data mining with applications in text analytics, bioinformatics, digital agriculture, and security informatics. She has made significant contributions to semi-supervised learning and domain adaptation, especially in scenarios with limited labeled data. Her interdisciplinary work bridges computer science with life sciences and social sciences to solve real-world challenges. The recent publication trend highlights her focus on deep learning architectures, particularly transformer models and contrastive learning, applied to disaster image classification—indicating a growing interest in crisis informatics and multimodal AI for humanitarian applications. Scientific Awards: Iowa State University Research Excellence Award IBM Fellowship (2002, 2003) Don and Linda Glaser Keystone Research Scholar Doina Caragea has secured over $12 million in external funding as PI, co-PI, or senior personnel from NSF and industry sources. She has advised four doctoral students and more than 25 master’s students, demonstrating a strong commitment to graduate education and mentorship. She teaches graduate and undergraduate courses, including CIS831/CIS532: Deep Learning (offered Fall 2017, 2019–2023) and CIS761: Database Management Systems (designed in 2013, offered Spring 2016–2024). Her courses cover foundational and advanced topics in deep learning, neural networks, relational databases, SQL, and NoSQL systems.

Ching-yu Huangمشاهده پروفایل

دانشیار

• Bioinformatics
• Data Mining
• Image Processing
• +۶ مورد دیگر

Ching-yu Huang is an Associate Professor in the Department of Computer Science and Technology at Kean University within the College of Science, Mathematics and Technology. With a Ph.D. in Computer and Information Sciences from NJIT, he bridges industry experience in Finance, Telecommunications, and Biotechnology with academic roles, focusing on data mining, image processing, and educational technology. Education : Ph.D. (NJIT, 1998), M.S. (NJIT, 1993), B.Eng. (Tamkang University, 1990) Research Interests span bioinformatics (SNP genotype calling), data mining, image processing, GIS, and cyber-learning. His work integrates machine learning with practical applications in medical imaging, social media analysis, and educational tools. Publication Trends show expertise in data analytics for public health, geospatial systems, and educational technologies, with recent studies on pandemic impacts, blockchain, and AI-driven visualization tools. Collaborations with students highlight real-world problem-solving. Scientific Awards : NSF Grant Co-PI (2025-2029) Kean Presidential Excellence in Teaching (2023) NSF DUE Grant Co-PI (2021-2026) Multiple SpF and STEMPact Awards (2017-2023) Teaching & Grants : Courses include Data Mining, Database Systems, and Unix Programming. He has secured significant NSF funding for cybersecurity and data science education, mentoring over 20 students in research initiatives. Labs & Teams : Faculty advisor for Code Samurai peer-tutoring Collaborator in NIH UMDNJ research Co-PI in NSF grants for educational innovation