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Patrick FloranceView profile

Senior Lecturer

• Geographic Information Systems (GIS)
• Geospatial Technology
• Crisis & Humanitarian Mapping
• +7 more

Patrick Florance is the Director of Research Technology at Tufts University, where he leads Tufts Technology Services’ support for High-Performance Computing, research storage, scientific instrumentation, and data science. He is concurrently an affiliate of the Department of Urban & Environmental Policy & Planning in the School of Arts and Sciences and a senior instructor at the Fletcher School of Law and Diplomacy. Education Bachelor of Arts, University of Oregon, Eugene, United States Master of Arts, Geography – Geographic Information Science, City University of New York – Hunter College, New York, United States Research & Scholarly Interests Florance’s scholarship and service converge on the design, deployment, and governance of open-source geospatial infrastructures. His work encompasses: Global and humanitarian mapping, crisis mapping, and geospatial support for disaster response Development of the Open Geoportal (OGP) Federation — a Sloan-funded collaborative platform for sharing geospatial data across universities 3D GIS, remote sensing, UAV/drone workflows, and spatial data infrastructures for urban modeling Digital humanities, natural language processing, and data-mining approaches to historical and textual geodata Geospatial pedagogy, open-data advocacy, and capacity-building in the developing world Publications & Intellectual Trajectory Across more than two decades, Florance has authored or co-authored scholarly articles, software reviews, and special journal issues that advance both technical architectures and sociotechnical practices for geospatial information curation. His writings trace a trajectory from foundational concerns of GIS collection development in academic libraries to contemporary challenges of real-time, open, and ethical crisis mapping. Scientific Awards & Grants Alfred P. Sloan Foundation – Open Geoportal Cloud (OGP) Federation (US$ grant, 2013) University Service & Leadership Patrick chairs or serves on multiple university committees driving data-intensive research strategy: Data Analytics Steering Committee, School of Arts & Sciences Digital Humanities Steering Committee, Tufts University Data-Intensive Scholarship Center (DISC) Advisory Committee on Infrastructure and Services (ACIS) GIS Steering Committee Research Data Services Committee Labs, Teams & Infrastructure He directs the Tufts Data Lab , a campus hub for GIS, statistics, visualization, and machine-learning services, and oversees the Open Geoportal Project , a multi-institutional consortium providing federated discovery and access to geospatial data sets. His team supports thousands of researchers university-wide with high-performance compute clusters, research storage arrays, and discipline-specific scientific instrumentation.

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).

Virendra BhavsarView profile

Research Professor

• Natural Language Processing
• Cognitive Informatics
• Distributed Systems
• +3 more

Virendra Bhavsar is an Honorary Research Professor and Professor Emeritus in the Department of Computer Science at the University of New Brunswick (UNB). He holds a PhD in Computer Science and is affiliated with UNB's Fredericton campus, located in Gillin Hall GE109A. His research focuses on natural language processing (especially for Hindi and other Indian languages), cognitive informatics, distributed systems, and bioinformatics. Bhavsar has also contributed to projects involving virtual reality in education, parallel computing, and machine translation systems. Education: PhD in Computer Science Research Interests: Development of NLP tools for free-word-order languages Optimization of in-memory data processing systems on NUMA architectures Cognitive learning environments using virtual reality Tree-based parsing algorithms for linguistic analysis High-performance spatial and spatio-temporal data systems Recent Work Trends: His articles from 2017–2022 highlight advancements in Hindi language processing, distributed computing optimizations, and cognitive informatics applications. Notable areas include improving data skew resilience in hash joins and developing visualization systems for language learning. Awards: No specific scientific awards listed in available materials. Advising & Grants: No formal advisee list or grant details provided in current data. His collaborations include work on grid computing frameworks like GARUDA and HPGC initiatives. Labs/Teams: Involved in projects related to distributed in-memory systems (e.g., DISTIL) and cognitive informatics research groups.

Xiwen LuView profile

Assistant Professor

• Teaching Chinese as a Second Language
• Learning Sciences and Technology
• Computer-Based Language Education
• +3 more

Xiwen Lu is an Assistant Professor in Chinese at Brandeis University, serving as Director of the Chinese Language Program, Undergraduate Advising Head, Study Abroad Liaison, and Co-Director of the Master of Arts Program in Chinese Language and Culture (Language Track). She holds a Ph.D. (Candidate) in Learning Sciences and Technology from Worcester Polytechnic Institute, an MA from Beijing Language and Culture University, and a BA from PLA University of Foreign Languages. Her research focuses on Teaching Chinese as a Second Language (TCSSL) , with specialties in Learning Sciences and Technology , Computer-Based Language Education , and Secondary Chinese Curriculum Design . She has developed innovative online platforms and textbooks, including Journeys (启程) and a computer-based advanced intermediate Chinese course pack. Dr. Lu has received significant recognition, including the 2019–2020 Provost’s Teaching Innovation Grant and multiple teaching fellowships. She teaches a broad range of courses from foundational to advanced levels, emphasizing conversation, composition, pedagogy, and practicum in the Chinese language curriculum. Her publications explore topics like handwriting efficiency in language learning, feedback mechanisms in online assignments, and bridging K-12 to college curricula. She has contributed to conferences globally, including the ACM Conference on Learning at Scale and the International Conference on Computer Supported Education.

• Natural Language Processing
• Machine Learning
• Biomedical Informatics
• +7 more

Jianlin Shi is an Assistant Professor in the Department of Internal Medicine at the University of Utah , with an adjunct appointment in Biomedical Informatics . His academic journey includes a PhD from University of California, Irvine , medical training at West China Medical Center , and residency at Sichuan University . Primary: Internal Medicine Adjunct: Biomedical Informatics Dr. Shi's research focuses on Natural Language Processing (NLP) in clinical settings , particularly for genetic testing criteria identification , medication disposition extraction , and clinical decision support systems . He has developed medspaCy , a Python NLP toolkit for healthcare, and created hybrid NLP frameworks integrating LLMs with rule-based systems to enhance disease screening and data privacy tools . His recent work spans 2025-2022 , emphasizing applications in surgical infection detection , dementia identification , and clinical cohort generation . While no formal awards are listed, his 15 most recent publications demonstrate sustained contributions to clinical NLP , medical decision support , and health data standardization .

Bernardino Casas FernándezView profile

Adjunct Professor

• Quantitative Linguistics
• Natural Language Processing
• Polysemy
• +3 more

Bernardino Casas Fernández is an Adjunct Professor at the Departament de Llenguatges i Sistemes Informàtics (LSI) of Universitat Politècnica de Catalunya (UPC). He holds offices at both the Vilanova i la Geltrú campus (EPSEVG-VG1, Room 120) and the Barcelona campus (Campus Nord-Edifici Omega, Room 224). His research focuses on quantitative linguistics, natural language processing, polysemy analysis, and computational linguistics. He has contributed to open-source tools like FreeLing and projects such as CARPANTA for email summarization. Recent work explores semanticity in Catalan using large language models and ethical implications of generative AI in education. He maintains active involvement in computational linguistics and child language development studies. Education details are not explicitly listed, but his academic career spans from 2003 (earliest article) to 2024. He collaborates with initiatives like LAPPS (Language Acquisition and Processing Systems) and has participated in projects involving churn prediction systems and entropy estimation techniques.

Mustafa OcalView profile

Teaching Professor

• Artificial Intelligence
• Natural Language Processing
• Data Science
• +4 more

Mustafa Ocal is an Assistant Teaching Professor in the Department of Computer Science at Florida International University (FIU), part of the College of Engineering and Computing. He holds both a PhD (2022) and MS (2021) in Computer Science from FIU, focusing on Artificial Intelligence and Natural Language Processing. His research emphasizes temporal analysis, TimeML, and timeline extraction, leading to publications, patents, and software libraries like pyTLEX and jTLEX. Education: Ph.D., Computer Science, Florida International University (2022) M.S., Computer Science, Florida International University (2021) Research Interests: Ocal’s work centers on AI applications in temporal analysis, including automated timeline extraction, TimeML corpus validation, and narrative duration estimation. His contributions address core challenges in natural language processing and data science, with applications in computational linguistics and information extraction. Publications reflect a focus on temporal modeling, corpus evaluation, and algorithm development. His work spans theoretical advancements in timeline extraction to practical tools like Python/Java libraries. Notable Achievements: Holds a US patent for an AI model and co-authored a Cambridge University Press book. His research has been recognized through peer-reviewed articles at top conferences and publishers. Teaching & Mentoring: Ocal actively mentors students at both undergraduate and graduate levels, emphasizing effective communication of complex AI concepts. He teaches across various universities, contributing to the next generation of computer scientists.

• Software System Quality
• Software Architecture Design and Evaluation
• Software Visualization and Reverse Engineering
• +8 more

Wilhelm Hasselbring is Professor of Software Engineering at the School of Electronics and Computer Science, University of Southampton. His research focuses on software system quality, architecture design, and distributed systems with emphasis on fault-tolerance and monitoring. Software System Quality Architecture Design and Evaluation Microservices and DevOps Digital Twins and Prototyping Open Science Practices Current research explores digital twin prototypes for smart farming applications, metamorphic testing methodologies, and scalable microservice architectures. His work bridges theoretical frameworks with industrial applications in middleware and cloud systems. Recent awards include the Ernst Denert Award for Software Engineering (2019-2020). Publications span topics from JavaBERT language models to MQTT bridge evaluations, emphasizing software visualization and reverse engineering techniques. Contact: W.Hasselbring@soton.ac.uk

LIANG ZhenkaiView profile

Associate Professor

• system and software security
• Web security
• mobile security
• +6 more

Dr. LIANG Zhenkai is an Associate Professor and Chairman of the Department of Computer Science at the National University of Singapore's School of Computing. He also serves as the Lead Principal Investigator for the National Cybersecurity R&D Lab (NCL). With extensive experience in academic leadership and cybersecurity research, Dr. Liang has established himself as a prominent figure in the field of system and software security. Dr. Liang received his Ph.D. in Computer Science from Stony Brook University in 2006 and his B.S. degrees in Computer Science and Economics from Peking University in 1999. His dual background provides a unique perspective on security challenges that bridges technical expertise with economic understanding. Dr. Liang's research focuses on system and software security , with particular emphasis on security in emerging platforms including Web, mobile, and Internet-of-Things (IoT) systems. His specific research interests include program analysis, Web and IoT system security, and virtualization. As the leader of the Curiosity Research Group, his team pursues missions centered around "Understanding systems (理解系统), abstracting knowledge (提炼知识), and connecting facts (参悟规律)". This philosophical approach to security research has yielded numerous significant contributions to the field. Dr. Liang's recent publications demonstrate a strong evolution from fundamental security mechanisms to sophisticated solutions addressing AI security, blockchain, and advanced vulnerability analysis. His work increasingly integrates machine learning techniques with traditional security approaches, focusing on developing robust defenses against sophisticated attacks while maintaining system usability. The trend shows a progression toward addressing contemporary challenges in large language models, secure system observability, and vulnerability propagation analysis. Dr. Liang has received numerous prestigious awards recognizing his research excellence: Outstanding Paper Award at ACSAC (2003) Best Paper Award at USENIX Security Symposium (2007) ACM SIGSOFT Distinguished Paper at ESEC-FSE (2009) Best Paper Award at W2SP Workshop (2014) Annual Teaching Excellence Award at NUS (2014, 2015) As an educator, Dr. Liang has taught various undergraduate and graduate courses including CS3235 Computer Security, CS5231 Systems Security, and CS5321 Network Security. His teaching philosophy, which he has published on in "Tool, Technique, and Tao in Computer Security Education," emphasizes both technical expertise and philosophical understanding of security principles. He has successfully mentored numerous students and researchers in the cybersecurity field. Dr. Liang leads the Curiosity Research Group, which actively seeks curious minds to join their exploration of security systems. The group maintains strong connections with industry and government cybersecurity initiatives, particularly through the National Cybersecurity R&D Lab (NCL). Their research environment encourages innovative thinking with the requirement that "Curiosity is required, while mentality for repairing things (such as bicycles) is a plus."

• Data mining
• Reverse engineering
• Machine learning
• +1 more

Mohammadhossein Amouei is a researcher and lecturer affiliated with McGill University's School of Information Studies. He holds the role of Course Lecturer for INFS 691: Computer Programming for Information Professionals. His primary research interests span data mining, reverse engineering, machine learning, and cybersecurity. He is affiliated with research labs including the Data Mining & Security Lab and the Accessible Computing Technology Research Group Lab. His educational background includes PhD candidacy at McGill University. Recent research focuses on reinforcement learning-driven vulnerability discovery in cybersecurity and natural language generation for assembly code documentation. He has contributed to federated learning security through game-theoretic frameworks. Advising and grants information is not explicitly detailed in available texts. He maintains an active presence on LinkedIn and GitHub, and his work bridges theoretical computer science with practical security applications.

Amir GhalamzanView profile

Associate Professor

• Robot Learning
• Robot Grasping and Manipulation
• Teleoperation
• +3 more

Amir Ghalamzan is an Associate Professor at the University of Surrey's School of Computer Science and Electronic Engineering, leading the Intelligent Manipulation Lab. His research focuses on robot learning, robotic grasping, teleoperation, and agri-food robotics. Previously, he held roles at the University of Lincoln and University of Birmingham. Education: PhD in Robot Learning (Politecnico di Milano, 2015), M.Sc. in Mechanical Engineering (Iran University of Science and Technology, 2009). Research Interests: He addresses real-world challenges like labor shortages in agriculture through robots for extreme conditions, such as strawberry picking. His work integrates advanced perception, AI, and control systems. Notable projects include developing autonomous strawberry-picking robots and haptic-guided teleoperation systems. Key Projects: Led the £310K CERES Agtech project (2020-2021) for autonomous strawberry robots, and contributed to the £1.5M Agri Open-Core project (2023-2027) for open-source harvesting software. Collaborated with institutions like Imperial College London and companies like Saga Robotics. Labs/Teams: Directs the Intelligent Manipulation Lab, focusing on tactile sensors (e.g., AST Skin) and soft robotics innovations.

Sebastian MichelmannView profile

Assistant Professor

• Cognitive Neuroscience
• Memory Processes
• Neurophysiology
• +7 more

Sebastian Michelmann is an Assistant Professor of Psychology at New York University's College of Arts and Science. His research focuses on understanding how temporal dynamic content is neurally represented and processed in episodic memory, with particular emphasis on fast-timescale memory retrieval mechanisms and their interaction with event knowledge. He employs electrophysiological methods (EEG/MEG), computational modeling, and behavioral experiments to study memory formation under naturalistic conditions. Education: PhD in Psychology from the University of Birmingham (2018), thesis awarded the Glushko Dissertation Prize (2020) Master's (Diploma) in Psychology from Julius-Maximilians-Universitaet Wuerzburg (2014) Postdoctoral research at Princeton University (2018–2023) under Professors Ken Norman and Uri Hasson Research interests include neural oscillations, event segmentation, and the role of generalized event knowledge in memory retrieval. His work bridges cognitive neuroscience with computational approaches, exploring how the brain encodes, stores, and retrieves temporally precise information. Key research directions involve studying how memory processes are embedded in continuous experience and developing tools to analyze neural data (e.g., intracranial EEG re-referencing). Recent studies explore event boundary detection using large language models and investigate the neural correlates of natural language comprehension through ECoG datasets. Scientific Awards: Glushko Dissertation Prize (2020) Laboratory activities focus on future projects combining electrophysiology with computational modeling to understand interactive dynamics of episodic memory. Collaborative efforts include developing semi-automatic alignment tools and cloud-based neuroimaging frameworks.

• Software Engineering
• Artificial Intelligence
• Chatbots
• +3 more

Dr. Ahmad Abdel Latif is an Assistant Professor in the Department of Electrical and Software Engineering at the University of Calgary. Previously, he served as a postdoctoral researcher at DASLab, Concordia University, and earned his Ph.D. in Software Engineering from Concordia under Dr. Emad Shihab. His master’s degree was obtained from King Fahd University of Petroleum and Minerals (KFUPM). His research focuses on software engineering advancements in artificial intelligence, including chatbots, software quality, and mining software repositories. Notable projects include analyzing dependency ecosystems (e.g., NPM, Maven) for security risks, developing AI-driven chatbots for code repositories, and exploring machine learning model management challenges. He also investigates ethical implications of AI-generated code and open-source collaboration dynamics. Dr. Latif teaches ENSF 381: Full Stack Web Development and actively publishes on topics such as vulnerability mitigation, LLM-based chatbots, and software bot detection. His work bridges technical innovation with practical applications in cybersecurity, open-source ecosystems, and AI integration.

Christopher LeeView profile

Professor

• Digital Preservation
• Digital Forensics
• Electronic Records Management
• +3 more

Christopher (Cal) Lee is a Professor at the School of Information and Library Science (SILS) at the University of North Carolina at Chapel Hill. He specializes in digital preservation, digital forensics, and electronic records management, with a focus on the professionalization of digital curation practices. His work includes leading projects like BitCurator and OSSArcFlow, which develop open-source tools for libraries, archives, and museums. Lee holds a PhD in Information from the University of Michigan and has been recognized with awards such as the Frances Carroll McColl Term Professorship and the Society of American Archivists Preservation Publication Award. Education: Bachelor of Arts in Philosophy (Summa Cum Laude), Albion College, 1995 Master of Science in Information, University of Michigan, 1999 PhD in Information, University of Michigan, 2005 Research Interests: Long-term curation of digital collections Diffusion of digital forensics tools into professional practice Open-source software in cultural heritage institutions Ethical and practical challenges in digital preservation Recent Articles and Projects: Lee’s recent work focuses on modeling digital curation workflows (e.g., OSSArcFlow), computer-assisted appraisal methods, and applying natural language processing to born-digital materials. His publications span topics like disk image access, automated redaction of sensitive data, and the integration of forensic tools into archival workflows. Awards and Honors: Frances Carroll McColl Term Professor (2013–2015) Poster Award, Aligning National Approaches to Digital Preservation (2013) Best Political Science Website Award for ContextMiner (2010) Grants and Leadership: Lee has led major grants including the RATOM project (reviewing appraisal of digital mail) and the BitCurator consortium. He co-edited key volumes like Aligning National Approaches to Digital Preservation and serves as a Fellow of the Society of American Archivists. Labs and Teams: He contributes to initiatives like the DataNet Federation Consortium and the DigCCurr curriculum project, fostering collaboration between academia and cultural heritage institutions.

Marianne BradfordView profile

Professor

• Accounting Information Systems
• Enterprise Resource Planning (ERP) Systems
• Data Security and Classification
• +3 more

Marianne Bradford is a Professor of Accounting at the Department of Accounting, North Carolina State University, within the Poole College of Management. She holds a Ph.D. in Accounting from the University of Tennessee (2001). Her research focuses on Enterprise Resource Planning (ERP) systems, data security and classification, audit technology, and sustainability reporting. She has contributed to studies such as 'The Critical First Step to Data Security' (2021), emphasizing the role of management accountants in defining security KPIs, and has been recognized with the Best Education Paper Award (2010). Her academic work spans ERP implementation strategies, robotic process automation governance, and the application of AI tools like ChatGPT in accounting education. She collaborates with organizations like SAP, integrating ERP modules into curricula, and has advised on ERP post-implementation maintenance and identity access management. Her engagement with industry challenges includes analyzing barriers to generalized audit software adoption and exploring stakeholder expectations in sustainability reporting. Bradford is affiliated with the Business Analytics and AI Initiative (BAI) and contributes to the Poole College's thought leadership through publications in the ISACA Journal and articles in Strategic Finance. Her teaching emphasizes ERP systems and process mapping, reflecting her commitment to bridging academic research with practical business solutions.