جست‌وجوی استاد و پژوهشگر

• Cyber Physical Systems
• Risk/Reliability Analysis
• Deep Learning
• +۳ مورد دیگر

Dr. Saptarshi Sengupta is an Assistant Professor in the Department of Computer Science at San José State University (SJSU), leading the Machine Intelligence and Complex Systems (MICoSys) Lab. He advises the ACM student club at SJSU and holds a 'Alien of Extraordinary Ability' visa (Einstein Visa) from USCIS. His work focuses on resilient cyber-physical systems, risk analysis, and deep learning applications in healthcare and industrial systems. Education: Ph.D. in Electrical Engineering, Vanderbilt University M.S. in Electrical Engineering, Vanderbilt University B.Tech. in Electronics & Communication Engineering, West Bengal University of Technology Research Interests: Cyber-Physical Systems Security Healthcare AI for Cancer and Chronic Disease Prediction Battery Prognostics and Energy Systems Machine Learning for Complex Systems Analysis Key Achievements: Dr. T.M.A. Pai Gold Medal Award for Healthcare AI contributions Recipient of multiple best paper awards at international conferences Author of over 30 peer-reviewed publications Labs & Teams: Leads the MICoSys Lab, developing AI solutions for healthcare diagnostics, industrial prognostics, and smart infrastructure systems. Collaborations include interdisciplinary projects with biomedical and engineering domains.

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Masoud Makrehchi is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, part of the Faculty of Engineering and Applied Science. His research focuses on Natural Language Processing, Artificial Intelligence, Machine Learning, and Social Computing, with a strong emphasis on applications in network science and moral AI. He holds a PhD from the University of Waterloo (2007), along with earlier degrees from Shiraz University and Iran University of Science and Technology. Prior to academia, he worked as a Senior Research Scientist at Thomson Reuters (2008–2012) and completed a postdoctoral fellowship at the University of Waterloo (2007–2008). His research expertise includes text mining, social network analysis, and network science, addressing challenges such as signed social network analysis, document classification, and crime trend prediction using social media data. He has received several awards, including the NSERC Postgraduate Scholarship and the SBP Challenge Award (2012). His work spans over 50 peer-reviewed publications in journals like Expert Systems with Applications, Social Network Analysis and Mining, and Web Intelligence, with contributions to conferences such as GECCO and IEEE/ACM. Dr. Makrehchi’s publications highlight innovations in feature selection, text segmentation, and AI-driven frameworks for requirements elicitation. His recent work explores coherence graphs for text segmentation, generative AI in education, and bias detection in medical datasets. He has also contributed to patent applications related to sentiment analysis and text extraction systems.

Veronica Grahamمشاهده پروفایل

مدرس

• Virtual Reality Art
• Experimental Comics
• Climate Change Art
• +۵ مورد دیگر

Veronica Graham is a new media artist and printmaker serving as Lecturer in Stanford University's Department of Art & Art History. Based in Oakland and Portland, she founded the design studio Most Ancient in 2010, specializing in experimental comics and exploration games. Her interdisciplinary practice bridges digital media and analog print publishing through poetic world-building that confronts contemporary environmental and social challenges. Her research centers on virtual reality narratives, climate-focused printmaking, and surrealist comics that explore internalized fictions. Key projects include the VR experience Diatribes (2024), examining fears about global warming through a haunted house framework, and the Global Warming Agitprop Posters series (2020-present) using phosphorescent materials to visualize ecological instability. She employs techniques like Wang tile systems for pattern generation and split fountain printing to stretch technical boundaries. 2025 Writer-in-Residence, Writing Space, Chicago 2024 IndieCade Impact Award Nominee for Diatribes 2022 Oculus Launch Pad Grant Recipient 2019 Best American Comics Notable Comics selection 2017 Artist’s Book Residency Grant, Women’s Studio Workshop Graham’s work appears in MoMA, NYPL, and SFMOMA collections. Her VR projects have been presented at Kala Art Institute, Printed Matter (NYC), and Sónar+D. As an educator, she lectures on virtual reality at Stanford and has conducted workshops at institutions including Tufts University and UC Berkeley. Her studio Most Ancient functions as both creative laboratory and publishing platform, supporting collaborative projects like Real Milk (2023) which examines agricultural automation through translucent book design.

Franjo Ceceljaمشاهده پروفایل

استاد

• Systems Engineering for Energy and Industrial Applications
• Optimisation and Decision Making
• Knowledge Modelling (Ontology Engineering)
• +۳ مورد دیگر

Dr. Franjo Cecelja is a Reader in the School of Chemistry and Chemical Engineering at the University of Surrey. He holds a Dipl. Eng. from the University of Zagreb, an M.Sc. from Cranfield Institute of Technology, and a Ph.D. from Brunel University. His research focuses on systems engineering for energy and industrial applications, optimization, decision making, and semantic technologies. He has led projects such as the FP7 (Marie Curie LTN) initiative on renewable energy systems engineering (£425k, 2013–2018). His work spans ontology engineering applications in biorefining, waste valorization, and sustainable processing. Notable contributions include semantic frameworks for model and data integration in biorefineries and decision support systems for industrial symbiosis. Education: Ph.D., Brunel University (Optical Sensors for Electric Fields) M.Sc., Cranfield Institute of Technology (Control & Signal Processing) Dipl. Eng., University of Zagreb (Aerospace Technology) His research interests integrate ontology engineering with process systems engineering to address challenges in biorefining, industrial symbiosis, and sustainable resource management. Recent publications emphasize semantic technologies for waste valorization, PFAS treatment, and decision-making frameworks in biorefining. Dr. Cecelja’s FP7 project demonstrated leadership in renewable energy systems, leveraging semantic networking facilities and value chain optimization. His work bridges academic research with industrial applications, emphasizing circular economy principles and model-driven decision support. Labs/Teams: His research is conducted within the University of Surrey’s School of Chemistry and Chemical Engineering facilities, collaborating with interdisciplinary teams on biorefining and process systems engineering.

Evimaria Terziمشاهده پروفایل

استاد

• algorithmic data mining
• network analysis
• recommendation systems
• +۳ مورد دیگر

Evimaria Terzi is a Professor and Department Vice Chair at Boston University (BU), affiliated with the Data Management Lab@BU. Her research focuses on algorithmic data mining with applications in network analysis, recommendation systems, ranking, and clustering. She holds a PhD from the University of Helsinki and has held prior roles at IBM Almaden Research Center (2007–2009) and the Helsinki Institute for Information Technology (HIIT) before 2007. Her work spans theoretical and applied domains, including team formation algorithms, fairness in AI, and large language model evaluation. Notable contributions include studies on LSM tree optimization, counterfactual explanations for auditing fairness, and the dynamics of memorization in LLMs. Her recent publications emphasize flexibility in database systems and ethical AI practices. Evimaria’s research has been recognized through her contributions to conferences like WSDM and KDD, where she has served in organizing roles. The themes of her work consistently bridge algorithmic innovation with real-world applications in social networks, healthcare, and collaborative systems.

Michael Foxمشاهده پروفایل

استادیار

• digital humanities
• philosophy and ethics of AI
• natural language processing
• +۵ مورد دیگر

Michael Fox is a Teaching Assistant Professor in the School of Information and Library Science (SILS) at the University of North Carolina at Chapel Hill. Prior roles include Senior Lecturer and Academic Director for the Digital Studies of Language, Culture, and History program at the University of Chicago, and Assistant Editor/Software Architect of the William Blake Archive. He holds a PhD in English and BS in Computer Science. His research bridges literary criticism and information science, focusing on digital humanities, AI ethics, and textual studies. Key areas include graph databases, network analysis, and AI methods in literary history, alongside studies of Aestheticism, poetics, and literary history. His first book examines intersections between literary and historical writing, using computational approaches like graph databases. Michael has contributed to the William Blake Archive, a pioneering digital humanities project, and serves on the editorial board of Textual Cultures . His courses span literature, information science, and their intersections (e.g., Digital Humanities, The Idea of AI). His work earned the ADE 2017 Featured Project award for the Blake Archive's redesign. Grants and advising details are pending explicit mentions in texts.

Olakunle Olayinkaمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Digital Forensics
• Gamification in Education
• +۳ مورد دیگر

Dr. Olakunle Olayinka is a Senior University Teacher and Deputy School Director of Education in the Department of Computer Science at the University of Sheffield. He is a member of the Institute of Coding and has over a decade of experience in IT and academia. Prior to his current role, he worked as a Research Assistant at the University of Gloucestershire, teaching Cybersecurity and related modules. He holds a PhD in Computing from the University of Gloucestershire, alongside an MSc in Computer Forensics and BSc in Computer Science from Babcock University and University of Glamorgan respectively. His research focuses on Cybersecurity & Gamification , Digital Forensics , and Information Systems Adoption . He has contributed to studies on generative AI in education, cybersecurity training methodologies, and digital transformation strategies for small businesses. Recent work includes exploring AI-driven approaches to web application security and IoT threat hunting using bio-inspired models. His publications span journals like Sustainability and Journal of Applied Learning & Teaching , with a focus on bridging educational technology gaps and enhancing cybersecurity practices. He has co-authored book chapters on digital transformation in Nigerian enterprises and cybersecurity frameworks. Teaching responsibilities include Cybersecurity Team Project, Cyber Threat Hunting, and Software Engineering modules. He advocates for project-based learning approaches, as demonstrated in his work on Agile methodologies in software projects.

Tony Stockmanمشاهده پروفایل

مدرس ارشد

• Human-Computer Interaction
• Auditory Displays
• Data Sonification
• +۳ مورد دیگر

Dr. Tony Stockman is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. His teaching focuses on Database Systems, Interaction Design, and Semi-structured Data Modelling across undergraduate and postgraduate programs. His research interests include Human-Computer Interaction, Auditory Displays, and Data Sonification, with a strong emphasis on accessibility and cross-modal interfaces. Dr. Stockman has contributed to over 100 publications, exploring topics such as biofeedback systems, assistive technologies for visually impaired individuals, and collaborative design methodologies. His work frequently bridges technical innovation with user-centric design principles. Notable projects include the development of non-visual navigation tools like the Audiom web-based map viewer and co-designed haptic wearables for music synchronization. His research also addresses challenges in education technology, such as dyslexia screening through serious games.

Nikole Nielsenمشاهده پروفایل

دانشیار مدعو

• Astronomical sciences
• Astrophysics
• Galaxy Evolution
• +۳ مورد دیگر

Dr. Nikole Nielsen is an Adjunct Associate Professor at Swinburne University of Technology and an Assistant Professor at the University of Oklahoma. She holds dual appointments in the Centre for Astrophysics and Supercomputing (Swinburne) and the Homer L. Dodge Department of Physics and Astronomy (OU). Her research focuses on the circumgalactic medium (CGM) of galaxies, studying gas kinematics, ionization states, and metal content to understand galaxy evolution processes like accretion and outflows. She has held roles including ASTRO 3D Fellow and Postdoctoral Research Associate at Swinburne from 2015–2024. Education: PhD in Astronomy (New Mexico State University, 2015), M.S. in Astronomy (2013), B.S. in Astrophysics (Michigan State University, 2009). Awards include the Swinburne Director's Outstanding Achievement Award (2022) and multiple recognitions for research excellence. She supervises PhD students in areas like galactic outflows and CGM dynamics. Research highlights include mapping the transition between galactic disks and CGM using emission-line data (Nature Astronomy, 2024), resolving outflow properties in starburst galaxies (Monthly Notices of the Royal Astronomical Society, 2024), and studying gas kinematics in multiphase CGM (2024). Her work bridges observations with simulations, emphasizing resolved spatial data to understand galaxy evolution. Grants include an NSF East Asia-Pacific Summer Institute fellowship (2012) and ASTRO 3D funding. Teaching includes courses on extragalactic astronomy and cosmology at OU. Outreach efforts include coordinating public astronomy events and mentoring students. Current team includes postdocs and graduate students at OU.

• Climate Change Mitigation
• Industrial Ecology
• Life Cycle Assessment (LCA)
• +۷ مورد دیگر

Francesco Cherubini is a Professor and Director of the Industrial Ecology Programme at NTNU's Department of Energy and Process Engineering. He leads multidisciplinary research on climate change mitigation, environmental sustainability, and bio-based systems. His work integrates field studies, climate models, and life cycle assessment (LCA) to evaluate energy systems, land use, and technological innovations. Education & Roles: Professor at NTNU since [year not explicitly stated, inferred from roles] Lead Author for IPBES Nexus Assessment Report and IPCC Special Report on Climate Change and Land Director of the Industrial Ecology Programme Research Focus: Climate impacts of energy systems and land use (agriculture, forestry) Sustainable bioenergy and bio-based technologies (biofuels, biorefinery) Environmental impacts of hydrogen, aviation fuels, and industrial processes Climate-smart agriculture and land management strategies Life cycle assessment methodological advancements Key Projects (2020–2027): LCA4BIO: Harmonized LCA methods for bio-based systems ICARUS: Sustainable aviation biofuels development HYDROGENi: Norwegian hydrogen innovation center AGRISCASCADE: Circular fertilizers from agricultural waste SusLand: Sustainable land management for climate mitigation Scientific Recognition: Web of Science 'Highly Cited Researcher' (top 1% by citations) Teaching: Graduate course TEP 4300: 'Climate Change Mitigation'

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Ahmed AbuRa'ed is a Researcher at the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF), Barcelona. He is affiliated with the TALN research group and the Large-Scale Text Understanding Systems Lab. His work focuses on advancing knowledge in scientific text summarization, information extraction, and machine learning. Education: PhD in Computer Science (2020), UPF, Barcelona, Spain M.Sc. in Computer Science (2015), University of Trento, Italy B.Sc. in Computer Information Systems (2007), An-Najah University, Nablus, Palestine Research Interests: Natural Language Processing (NLP), Machine Learning/Deep Learning, Semantic Web, Information Extraction, Data Mining, and Scientific Document Summarization. His projects include developing systems for automatic generation of state-of-the-art reports, scientific text summarization, and cross-document relation discovery. Publications Focus: His 15 most recent articles (2016–2021) emphasize advancements in scientific literature analysis, including citation detection, text simplification, and cross-document summarization. Notable works involve systems like LaSTUS/TALN for scientific text processing and OlloBot for Arabic health dialogue agents. Labs & Teams: Active member of the TALN research group and the Large-Scale Text Understanding Systems Lab at UPF's DTIC department. Open to collaborations in NLP, Machine Learning, and related fields via email or Skype.

Richard Boyceمشاهده پروفایل

دانشیار

• Clinical Decision Support Systems
• Pharmacovigilance
• Drug Interaction Analysis
• +۳ مورد دیگر

Richard Boyce is an Associate Professor in the Department of Biomedical Informatics at the University of Pittsburgh's School of Computing and Information. His work focuses on clinical decision support systems (CDSS), pharmacovigilance, and distributed knowledge bases. He leads research in drug interaction analysis, particularly involving natural products like cannabis, and develops machine learning tools for healthcare applications. His address is 530 DBMI Building, Pittsburgh, PA 15260, with contact email rdb20@pitt.edu. Boyce’s research integrates clinical and pharmacological data to improve patient safety through advanced analytics. Recent projects include predicting Alzheimer’s disease using EHR data, falls prediction in nursing homes, and optimizing CDSS modules for resource-limited settings. His team also develops open-source knowledge graphs for life sciences, enhancing data interoperability. Education: Details not explicitly listed in the provided text. Labs/Teams: Affiliated with the Department of Biomedical Informatics and School of Computing and Information at Pitt. Publications highlight his contributions to pharmacovigilance signal detection, machine learning in healthcare, and ontology engineering. Notable works include studies on cannabis-drug interactions and CDSS design for clinical practice.

Christopher B.R. Dillerمشاهده پروفایل

مدرس

• Collaboration Technologies
• Decision Support Systems
• Organizational Behavior
• +۳ مورد دیگر

Dr. Christopher B.R. Diller is a Lecturer in the Department of Management at the University of Nebraska Omaha's College of Business Administration. He joined the institution in Fall 2015, transitioning from the School of Interdisciplinary Informatics at UNO's College of Information Science and Technology. With over a decade of corporate experience in roles spanning marketing, strategic planning, and IT management, Dr. Diller specializes in collaboration science and group decision support systems. He holds a Ph.D. in Management Information Systems from the University of Arizona's Eller College of Management, an MBA, and an MS in Decision & Information Science from the University of Florida. His teaching focuses on Management Information Systems, Principles of Collaboration, and Negotiation Strategies. Dr. Diller's research explores dynamic collaboration, group decision support systems (GDSS), rapid screening technology, and innovation strategies. His facilitation practice spans 25 years, aiding organizations worldwide in addressing complex challenges through collaborative solutions. He is also a sought-after speaker on topics like automation, change management, and leadership.

James Bradburyمشاهده پروفایل

مدرس

• Machine Learning
• Sound Art
• Computer Music
• +۳ مورد دیگر

James Bradbury is a Music Lecturer at the Conservatorium of Music, University of Western Australia. He holds a PhD in Music Technology (2021) from the same institution. His research focuses on integrating machine learning into music creation and performance, with expertise in sound art, experimental art, and software development for creative applications. Previously, he served as a Post-Doctoral Research Fellow in Creative Coding at the University of Huddersfield (2021–2022). Education: Doctor of Philosophy in Music Technology, University of Western Australia (2021) Research Interests : Bradbury explores machine learning's role in shaping contemporary music through real-time interactive systems, sound art installations, and experimental music performance. His work emphasizes computational tools for creative processes, including the Fluid Corpus Manipulation (FluCoMa) platform, which enables novel compositional workflows. He investigates how algorithmic approaches can expand artistic expression while maintaining human creativity at the core. Research Trends : Recent works highlight interdisciplinary collaborations between music and computer science, particularly in developing open-source tools like FluCoMa. His performances and publications demonstrate a focus on non-narrative musical forms and real-time algorithmic generation. The 2025 Audible Edge performance exemplifies this through live machine learning-driven sample selection. Awards and Grants : No specific awards or grants mentioned in the provided texts. His contributions are primarily reflected in creative outputs and academic publications. Labs and Teams : Active within the Conservatorium of Music, Bradbury collaborates with institutions like the University of Huddersfield and participates in festivals such as Audible Edge. His work is closely tied to the FluCoMa research collective, emphasizing open-source software development for artistic innovation.

Carolina Ruizمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Data Mining
• +۵ مورد دیگر

Carolina Ruiz is the Associate Dean of Arts and Sciences and Harold L. Jurist Dean’s Professor of Computer Science at Worcester Polytechnic Institute (WPI). She holds a PhD in Computer Science from the University of Maryland College Park (1996) and has been at WPI since 1997, progressing from Assistant Professor to Full Professor. Her research focuses on Machine Learning, Artificial Intelligence, and Data Mining applied to medicine, health, and education. Notable projects include developing AI-driven methods for sleep analysis, behavioral health interventions like the SlipBuddy app, and interdisciplinary programs in Bioinformatics and Neuroscience. She leads the Knowledge Discovery and Data Mining Research Group and serves on WPI’s Academic Planning Committee. Ruiz has advised over 35 graduate students, 150 undergraduates, and 12 high school researchers, emphasizing vertical integration of research teams. She co-led a $1.2M NSF grant (2017-2021) bridging Biology and Computer Science education through transdisciplinary curricula. Key service roles include Associate Department Head of Computer Science and governance committees at WPI. Education: PhD Computer Science, University of Maryland (1996) MS Computer Science, Universidad de Los Andes (1990) BS Computer Science & Mathematics, Universidad de Los Andes (1988-1989) Ruiz’s research spans medical AI applications (stroke prediction, sleep modeling), educational technology (computational biology curricula), and wearable sensor analytics. Her work has been featured in media including Medical News Today and NSF-funded initiatives. She emphasizes translational research bridging academia and real-world societal challenges.