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Mohamad SoltaniView profile

Assistant Professor

• Healthcare Operations Management
• Service Operations Management
• Empirical Studies in Operations Management
• +3 more

Mohamad Soltani is an Assistant Professor of Operations Management at the University of Alberta's Alberta School of Business, Department of Accounting and Business Analytics. He holds an Honorary Fellow appointment at the University of Wisconsin-Madison's Department of Emergency Medicine. His research focuses on data-driven analysis of healthcare and service operations, emphasizing interactions between policymakers, providers, and patients to enhance care quality and system efficiency. He teaches graduate and undergraduate courses in Predictive Business Analytics and Operations Management. Education: PhD in Operations Management (University of Wisconsin-Madison, 2020), MS and BS in Industrial Engineering (Amirkabir University of Technology and Isfahan University of Technology, Iran). Research Interests: Healthcare operations, service operations optimization, empirical operations analysis, and data analytics applications. His work has been featured in Management Science, M&SOM, and media outlets like CBC and Global News. Research Contributions: Award-winning studies on healthcare policy spillovers, ED physician workload impacts, and appointment scheduling algorithms. His work bridges empirical analysis with practical healthcare delivery challenges. Teaching: OM 502 (Operations Management) and OM 620 (Predictive Business Analytics) in Winter Term 2026, emphasizing analytical tools for business decision-making.

Paul NuyujukianView profile

Assistant Professor

• Motor Systems Neuroscience
• Neuroengineering
• Brain-Machine Interfaces
• +4 more

Paul Nuyujukian serves as an Assistant Professor of Bioengineering and Neurosurgery, with courtesy appointment in Electrical Engineering at Stanford University. He is a Faculty Scholar of the Wu Tsai Neurosciences Institute, directing the Brain Interfacing Laboratory where his team develops neural interface technologies for clinical applications in stroke and epilepsy. Education: MD, Stanford University (2014) PhD in Bioengineering, Stanford University (2012) BS, UCLA (2006) Dr. Nuyujukian's research integrates motor systems neuroscience with neuroengineering to decode brain activity during movement and recovery from injury. His laboratory pioneers brain-machine interface (BMI) platforms that translate neural signals into communication and control systems, with particular emphasis on intracranial EEG recording and real-time neural decoding. Current work focuses on developing clinically viable BMI solutions for neurological conditions through both preclinical models and human trials, advancing our understanding of neural population dynamics in health and disease. Recent publications reveal strong trends in intracranial EEG acquisition systems, seizure detection algorithms using information theory, and closed-loop BMI applications for ambulatory neuroscience. His work bridges fundamental neuroscience with clinical translation, particularly in epilepsy monitoring, chronic pain management, and neural prosthetics for paralysis. A notable emphasis exists on creating scalable, minimally invasive recording platforms that reduce clinical burden while maintaining high-fidelity neural data. Scientific Awards: No specific awards listed in provided materials As director of the Brain Interfacing Laboratory, Dr. Nuyujukian mentors students and collaborators in neural engineering research while securing grant funding for BMI development. His group maintains active collaborations with Stanford's Department of Neurosurgery and Neurology for clinical translation, with current projects including real-time decision-state decoding and personalized network mapping for pain management. The laboratory operates advanced facilities for both animal and human neural recording, emphasizing seamless integration of engineering innovation with clinical neuroscience. The Brain Interfacing Laboratory comprises multidisciplinary scientists and engineers developing next-generation neural interfaces. Current initiatives include the LiCoRICE platform for ambulatory neuroscience, seizure detection systems using compression-enabled entropy estimation, and ketamine's effects on hippocampal connectivity. The team actively participates in clinical trials for BMI applications in stroke rehabilitation and epilepsy, with strong partnerships across Stanford's medical and engineering schools to accelerate technology translation.

Giulia TotiView profile

Assistant Professor

• Computer Science Education
• Ethics in Data Science
• Machine Learning
• +3 more

Giulia Toti is an Assistant Professor of Teaching in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. Her work focuses on computer science education, equity in curriculum design, and fostering inclusive learning environments. She teaches courses such as Applied Machine Learning (CPSC 330), Fairness, Accountability, Transparency, and Ethics (FATE) in Data Science (DSCI 430), and Computers and Society (CPSC 430). Her research explores diversity initiatives in CS education, mastery learning frameworks, and equitable grading practices. Notable contributions include studies on pandemic-era remote teaching impacts and the development of Agora, a tool for enhancing large-classroom engagement. Toti has received UBC Faculty Teaching Awards for her pedagogical innovations. Her interdisciplinary work spans machine learning applications in industry and healthcare, including semantic search systems for clinical data (SemEHR) and predictive analytics for energy production. She is affiliated with the ACE Lab and actively contributes to curriculum reforms addressing DEI (Diversity, Equity, Inclusion) challenges in STEM education. Grants/Awards: Faculty Teaching Awards Labs/Teams: ACE Lab (Advancing Computing Education) Advising: No explicit advisee listings found, but contributes to pedagogical research impacting teaching practices.

• Analog CMOS Design
• Circuit Design Automation
• Integrated Circuit Compilers
• +2 more

Carsten Wulff is Associate Professor at NTNU's Department of Electronic Systems, focusing on analog CMOS design automation and circuit compilers. Research: Develops software tools for automated analog IC design, including ciccreator—an open-source compiler for generating custom integrated circuits. Aims to simplify analog design workflows through programmable frameworks. Teaching: Leads courses in Advanced Integrated Circuits (AIC) with public lecture notes and YouTube resources. Current focus includes Python-based circuit design tools.

Magda El-SherbiniView profile

Associate Professor

• Middle Eastern and Islamic Studies
• Turkish Studies
• Global Information Society
• +4 more

Magda El-Sherbini is an Associate Professor and Middle East and Islamic Studies Librarian at The Ohio State University (OSU), specializing in multilingual subject access, library science, and cataloging. She holds a BA in Library Science from Cairo University and an MA in Library and Information Science from The Catholic University of America. Her career spans roles such as Head of the Cataloging Department at OSU Libraries and Middle East Cataloging Specialist, with significant contributions to library standards like RDA and BIBFRAME. El-Sherbini has been awarded two prestigious Fulbright grants: one for research at the Bibliotheca Alexandrina (2010-2011) and another for teaching/research at the American University of Kuwait (2016-2018). She has received notable awards including the ALA ALCTS Outstanding Publication Award (2014) for her book *RDA: Strategies for Implementation* and the Margaret Mann Citation (2015). Her research focuses on Arabic name authority control, multilingual thesaurus development, and linked data applications in libraries. Her professional activities include teaching courses on 'Women in Islam' and 'Image of Arabs in Western Media,' as well as workshops on cataloging standards globally. She has authored over 20 publications, including seminal works on RDA implementation, BIBFRAME, and non-Roman subject access. El-Sherbini’s work bridges cultural, linguistic, and technological divides in library systems, emphasizing global accessibility and knowledge preservation.

• Digital Creativity
• Artificial Intelligence
• Requirements Engineering
• +12 more

Neil Maiden is Professor of Digital Creativity at Bayes Business School, City, University of London, where he also serves as Director of the Centre for Creativity enabled by AI (CebAI). He co-founded the Centre for Creativity in Professional Practice and leads interdisciplinary research at the intersection of software engineering, creativity science, and digital innovation. His expertise spans digital creativity support, requirements engineering, and AI-augmented systems for professional domains. PhD in Computer Science, 1992 Tenured at School of Informatics, City, University of London, 1995 Promoted to Professor of Systems Engineering, 2003 Visiting Professor at Ca' Foscari University of Venice, 2017–2019 and 2023–2024 Neil's research focuses on two primary domains: (1) Co-Creative AI for professional work, where he develops computational tools like Sport Sparks and Design Sparks to enhance creative thinking in journalism, design, and sports coaching; and (2) Specifying and designing complex digital systems using advanced requirements engineering methods applied in sectors such as air traffic, healthcare, and defence. His work is grounded in real-world applications, with collaborations involving Rolls-Royce, IBM, NATS, Sunderland AFC, and award-winning newsrooms. The 15 most recent publications reflect a strong trend toward integrating AI and computational models into creativity support and requirements engineering. Topics include automating journalism, enhancing dementia care, and modeling quality of life goals. Keywords span journalism, AI, software engineering, and digital health, with sub-fields such as generative AI, creative problem solving, assistive technology, and co-creative systems, demonstrating a consistent focus on human-centered innovation. Neil has been recognized through numerous invited keynotes and peer awards, though specific award names are not detailed in the text. He has supervised doctoral research and advised on multiple PhD projects, though student names are not listed. His research has been funded by major bodies including UKRI, EPSRC, EU (H2020), Innovate UK, and industry partners, with over £64 million in total project value and direct management of over £10 million at City. Notable grants include CebAI (£3.36M), SCAMPI (£943K), and QUEST (€1.14M). Neil leads the Centre for Creativity enabled by AI (CebAI) and previously co-founded the Centre for Creativity in Professional Practice. His research teams have developed tools such as BrightSparks, INJECT, and Care’N’Share, and he launched the JECT.AI startup to commercialize creativity support in news and content creation.

• Visual Analytics
• Mobility Data Science
• Machine Learning
• +4 more

Natalia Andrienko is a Professor of Computer Science at City University London and Lead Scientist in the Knowledge Discovery department at Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme. Her work bridges visual analytics with mobility data science and machine learning, focusing on human-in-the-loop systems for pattern discovery and spatiotemporal data exploration. Professor, Computer Science, City University London (2013-present) Lead Scientist, Knowledge Discovery, Fraunhofer Institute (1997-present) Research interests center on visual analytics methodology for spatiotemporal data, human-centered machine learning, and mobility pattern analysis. She develops frameworks for interactive dashboards, trust visualization in ML, and semantic exploration of location-based data, with a focus on scalable and privacy-respecting techniques. Her recent publications investigate hybrid human-machine discovery of movement patterns, contextual visual analytics for multivariate events, and the integration of temporal periodization with spatial analysis. Articles emphasize applications in sports analytics, transportation systems, and collaborative visual analysis workflows. Key collaborations include work with Gennady Andrienko and Salvatore Rinzivillo. She has contributed to journals like Visual Informatics , IEEE Transactions on Visualization and Computer Graphics , and International Journal of Cartography , maintaining active research output across visual analytics, mobility science, and geospatial data modeling.

Lionel P. Robert Jr.View profile

Professor

• Autonomous Vehicles
• Human-Robot Interaction
• Collaborative Robotics
• +5 more

Affiliations & Roles Lionel P. Robert Jr. is a Professor of Information and Robotics at the University of Michigan, holding joint appointments in the School of Information and the College of Engineering's Robotics Department. He directs the Michigan Autonomous Vehicle Research Intergroup Collaboration (MAVRIC) and is an affiliate faculty member at the National Center for Institutional Diversity and Indiana University's Center for Computer-Mediated Communication. His roles include editorial board positions at journals like the Journal of Computer Information Systems and leadership in professional organizations such as ACM and IEEE. Education Ph.D. in Information Systems, Indiana University (BAT Fellow, KPMG Scholar) M.B. from Indiana University, Bloomington M.S. degrees from Clemson University and University of Louisiana, Lafayette B.S. from University of Louisiana, Lafayette Research Focus Robert's research bridges collaboration through technology, with a focus on human-robot interaction, autonomous vehicles, and virtual teams. His work addresses trust in automated systems, human-AV communication, and the sociotechnical implications of robotics in workplaces and public spaces. Recent projects explore explanations for automated vehicles, security robots' societal acceptance, and AI ethics in healthcare and labor. Key Contributions He has published over 100 peer-reviewed articles in journals like MIS Quarterly and conferences such as CHI and HRI. His research has been funded by NSF, Toyota Research Institute, and the Army Research Laboratory. Notable outcomes include frameworks for AV trust repair, models of human-robot team performance, and critiques of AI-driven labor practices. Awards & Recognition ACM Distinguished Member IEEE Senior Member Carnegie Junior Faculty Development Fellowship 3× Teaching Commendation (2006–2008) Grants & Labs Current grants include studies on explainable AI, human-AV trust dynamics, and security robot design. The MAVRIC lab focuses on AV-pedestrian interactions while the CCMC explores digital communication's societal impact.

Karim AliView profile

Associate Professor

• Programming Languages
• Static Analysis
• Software Security
• +8 more

Karim Ali is an Associate Professor of Computer Science at New York University Abu Dhabi (NYUAD), where he leads research in programming languages, static analysis, security, and compilers. He is affiliated with the Department of Computer Science within the College of Arts and Science. Prior to joining NYUAD, he served as an Associate Professor at the University of Alberta. His academic training includes a BSc from The American University in Cairo, and MMath and PhD degrees from the University of Waterloo, completed in 2014. BSc: The American University in Cairo MMath: University of Waterloo PhD: University of Waterloo (2014) His research focuses on making static analysis tools more practical by enhancing their scalability, precision, and usability. He investigates program analysis techniques applicable to real-world software, with applications in security, just-in-time compilation, and mobile app development. His work spans theoretical foundations and tool development, including the SWAN framework for Swift and contributions to secure cryptographic API usage through CogniCrypt. The recent publications reflect a strong trend in developer-centric static analysis, secure coding, energy efficiency in mobile apps, and compiler optimization. His work combines empirical studies with tool-building, emphasizing usability and integration into developer workflows. Scientific Awards: Dahl-Naygaard Junior Prize (2021) ACM SIGSOFT Distinguished Paper Award ACM SIGPLAN Distinguished Paper Award Distinguished Artifact Award, ECOOP 2014 Karim Ali has mentored numerous students and collaborated extensively with researchers worldwide. His lab has contributed tools adopted by major static analysis frameworks like Soot, WALA, and DOOP. He has secured research recognition through awards and industrial impact, including helping Symantec fix a security vulnerability. He teaches core courses such as Computer Systems Organization and supervises capstone projects, guiding students in original research. His lab conducts research on programming languages and static analysis, with projects including SWAN for Swift analysis, usability studies of static analysis tools, and development of precise pointer analysis techniques. The team works on both academic research and practical tooling for developers.

Sarah Collins RossettiView profile

Associate Professor

• Biomedical Informatics
• Nursing Informatics
• Predictive Analytics
• +3 more

Sarah Collins Rossetti is an Associate Professor of Biomedical Informatics and Nursing at Columbia University’s Vagelos College of Physicians and Surgeons. She focuses on leveraging computational tools to reduce documentation burden in EHR systems and improve patient safety through predictive analytics. PhD in Nursing from Columbia University School of Nursing Post-Doctoral Research Fellowship at Columbia’s Department of Biomedical Informatics Her research emphasizes AI-driven patient deterioration prediction , user-centered design , and interprofessional collaboration to enhance clinical workflows. She co-leads the CONCERN Early Warning System study, which reduced mortality risk by 35% and sepsis risk by 7.5%. Recent publications highlight trends in generative AI limitations in EHRs, equity in predictive systems , and healthcare process modeling . She chairs AMIA’s 25×5 Task Force to reduce documentation burden by 75% by 2025. 2019 PECASE recipient 2024 Donald A.B. Lindberg Award for Informatics Innovation 2019 FAMIA recognition Rossetti collaborates with health analytics centers and trains future researchers through NIH- and AHRQ-funded projects, blending machine learning with clinical expertise in critical care settings.

Anna WilbikView profile

Professor

• Data Fusion
• Intelligent Interaction
• Fuzzy Logic
• +4 more

Anna Wilbik is a Professor in Data Fusion and Intelligent Interaction at the Department of Advanced Computing Sciences, Faculty of Science and Engineering, Maastricht University (The Netherlands). Her research bridges data understanding and human-machine synergy in complex systems, focusing on multi-criteria decision making, explainable AI, and data fusion techniques. PhD in Computer Science (with honors), Systems Research Institute, Polish Academy of Science (2010) Postdoctoral Fellow, University of Missouri (2011) Stanford University TOP500 Innovators Program Alumnus Research Pillars: Intelligent human-machine interaction for joint decision making Data fusion methods for heterogeneous data integration Contextualized multi-criteria decision frameworks Fuzzy logic and linguistic summaries for explainability Federated learning systems Article Trends: Recent work focuses on intuitionistic fuzzy sets for knowledge-intensive processes, federated learning with uncertainty handling, and linguistic summarization techniques for interpretable AI. She actively explores explainability , collaborative business models , and driver behavior analysis through attention-based models. Professional Leadership: Vice-chair of IEEE Fuzzy Systems Technical Committee Organizer of IEEE World Congress on Computational Intelligence (2024)

Christian WeberView profile

Senior Lecturer

• Cybersecurity
• Digital Health
• Smart Environments
• +4 more

Christian Weber serves as a Senior Lecturer & Researcher at the Institute of Business Information Technology within the Zurich University of Applied Sciences (ZHAW) School of Management and Law. He directs the CAS Cyber Security program and contributes to the ZHAW Digital Health Lab, focusing on sustainable digital ecosystems and security frameworks. His educational background includes an Executive MBA in General and Entrepreneurial Management from Johannes Gutenberg-Universität Mainz/McCombs School of Business and a Dipl.-Ing in Industrial Electronics & Electrical Power Engineering from RheinMain University of Applied Sciences. His continuing education spans numerous certifications in AI, sustainability, and digital health from institutions including Hasso Plattner Institute. Weber's research centers on sustainable smart solutions for digital ecosystems, including digital health, ambient assisted living, and smart environments. His work explores computer-supported cooperative working scenarios, applications of open source systems in SMEs, and data protection, cybersecurity, compliance, and forensics as enablers for digital ecosystems. His teaching portfolio spans multiple modules in IT Security, Emerging Technologies, IoT-Data Streaming & Analytics, and Digital Transformation across BSc and MSc Business Informatics programs. His recent publications demonstrate strong interdisciplinary connections between cybersecurity, digital health, and organizational transformation, with particular emphasis on practical applications in real-world settings. His work bridges technical implementations with organizational and societal impacts of digital technologies. Best Paper Award at SMART 2018 for "Citizens as Sensors" research "Educate to lead" award from Soroptimist International Europe for STEM outreach Weber's professional experience combines academic leadership with industry expertise, having served as Managing Director of the Cisco Networking Academy since 2012 and holding previous positions as Administrative Professor and Lecturer at University of Applied Sciences Braunschweig/Wolfenbüttel. His industry background includes executive roles as CIO/CTO and IT management consulting. He contributes to the ZHAW Digital Health Lab and has led projects including the ZHAW Digital Culture Assessment and Digital Health Hackathon, focusing on practical implementations of digital health solutions and organizational transformation.

Travis B. ThompsonView profile

Assistant Professor

• Mathematical Modeling
• Scientific Computing
• Machine Learning in Medicine
• +5 more

Travis B. Thompson, Ph.D. is an Assistant Professor in the Department of Mathematics and Statistics at Texas Tech University, leading the TM4 (Texas Tech Translational and Theoretical Mathematical Modeling and Machine Learning in Medicine) research group. His academic journey includes postdoctoral work at Rice University, Simula Research Laboratory, and the University of Oxford, focusing on mathematics applied to neurodegenerative diseases. Education: Ph.D. in Mathematics from Texas A&M University (2013) Dr. Thompson develops theoretical mathematical models and applies scientific computing and machine learning to study neurological pathologies, particularly Alzheimer’s disease. His work explores complex biological processes on networks, translational healthcare applications, and nutritional security implications. Current research trends integrate neuroimaging data with finite element simulations to model tau progression , amyloid beta dynamics , and glymphatic clearance in age-related diseases. Scientific awards and honors were not explicitly mentioned in the provided materials. Dr. Thompson’s interdisciplinary approach connects computational neuroscience with biomedical engineering , utilizing techniques like diffusion tensor imaging and level set methods to analyze pathological protein spread and brain tissue mechanics . The TM4 research group focuses on network neurodegeneration , personalized medicine , and machine learning diagnostics . Their work spans from microfluidic cancer detection to computational modeling of brain clearance mechanisms , addressing challenges in both neurodegenerative diseases and biomedical engineering through rigorous mathematical frameworks.

Donald H. TaylorView profile

Professor

• Health Policy
• Elder Care
• Racial Inequality
• +7 more

Donald H. Taylor is a Professor at Duke University with dual appointments in the Sanford School of Public Policy and the Department of Family Medicine and Community Health. He serves as the Director of the Social Science Research Institute and is an Executive Core Faculty Member at the Duke-Margolis Institute for Health Policy. Additionally, he holds affiliations as an Associate of the Duke Initiative for Science & Society and an Affiliate of the Duke Global Health Institute. Dr. Taylor's educational background includes: Ph.D. in Public Health, Health Policy and Management from the University of North Carolina, Chapel Hill (1995) M.P.P. from the University of North Carolina, Chapel Hill (1992) B.S. from the University of North Carolina, Chapel Hill (1990) As a leading health policy scholar, Dr. Taylor's research has evolved through several key phases. Initially focusing on rural health and identification of underserved areas, his work expanded to examine the economics of smoking and cessation. For the past two decades, his primary focus has been on elderly care systems and their impacts on individuals, families, public programs, and inter-generational wealth. More recently, he has delved into archival research methods to illuminate the role of race in American history, and is exploring how visual art and fiction might effectively challenge cultural acceptance of various forms of inequality. His extensive publication record shows consistent focus on Medicare, Medicaid, palliative care, and end-of-life care. A significant portion of his recent work examines racial disparities in healthcare, the economics of nursing and palliative care, and the impact of policy changes on vulnerable populations including the elderly and homeless. His research often employs sophisticated economic analyses to evaluate healthcare interventions and policy changes, with particular attention to how policies affect different demographic groups. Dr. Taylor has held significant leadership roles including serving as Chair of the Academic Council (2017-2019) and Director of the Social Science Research Institute since 2019. His grant portfolio demonstrates sustained funding for projects examining palliative care, Medicare/Medicaid policy, and health disparities, with current projects spanning from 2018 to 2025. His ongoing research initiatives focus on community-based palliative care models, racial inequality in healthcare, and innovative approaches to making health policy more effective and equitable. Through his work with the Duke-Margolis Institute for Health Policy, he continues to influence health policy at both state and national levels, particularly regarding Medicare reform, Medicaid expansion in North Carolina, and addressing systemic racial disparities in healthcare delivery.

• Motor Neuron Degeneration
• Amyotrophic Lateral Sclerosis (ALS)
• Induced Pluripotent Stem Cells (iPSC)
• +3 more

Dr Lucy Farrimond is an Academic Clinical Lecturer at the Nuffield Department of Clinical Neurosciences (NDCN), affiliated with the University of Oxford and Keble College . She serves as an Honorary Neurology Registrar at Oxford University Hospitals NHS Foundation Trust and leads research within the Oxford Motor Neuron Disease Centre . Her work bridges clinical practice and fundamental research into amyotrophic lateral sclerosis (ALS). Education: BM BCh (University of Oxford, 2012) Training: Academic Foundation Programme, NIHR Academic Clinical Fellowship Her research focuses on activity-dependent mechanisms of motor neuron degeneration in ALS, particularly using optogenetics with induced pluripotent stem cells (iPSC) from ALS patients to study the C9ORF72 genetic subtype. Publications highlight expertise in neuroinflammation, axonal transport, and iPSC co-culture models. Key collaborations include work with Professor Kevin Talbot's group. Recent publications demonstrate her focus on genetic ALS mechanisms (C9ORF72 hexanucleotide repeats), microglial toxicity, and clinical diagnostics optimization. She contributes to advancing genetic testing methodologies in ALS clinics. Scientific Awards: Wellcome Trust Clinical Research Fellowship NIHR Academic Clinical Fellowship in Neurology Dr Farrimond combines clinical responsibilities as a Neurology Registrar with teaching neuroscience and clinical neurology to Oxford medical students. Her work exemplifies translational research merging bench and bedside insights.