جست‌وجوی استاد و پژوهشگر

Hudson Smithمشاهده پروفایل

استادیار

• Machine Learning
• Medical Imaging
• Quantum Physics
• +۵ مورد دیگر

Hudson Smith is an Assistant Professor in the Department of Mathematical and Statistical Sciences at Clemson University, College of Science. His research focuses on integrating domain knowledge with machine learning to address data-constrained problems in healthcare, forensics, and physics. He holds a PhD in theoretical atomic physics from Ohio State University, combining first-principles approaches with data-driven methods. Key areas of research include medical imaging analysis (e.g., ultrasound quality assessment), forensic decomposition modeling (geoFOR database collaboration), and AI detection of coordinated disinformation campaigns. His work bridges theoretical physics (quantum systems, cold atoms) with applied machine learning in healthcare and social media analysis. Publications highlight contributions to AI in trauma care, forensic science, and social media disinformation detection. Active collaborations span forensic science, biomedical informatics, and quantum physics. GitHub repositories showcase contributions to visualization tools (e.g., Schrödinger equation solvers, Voronoi-based image stylization).

• Process Control
• System Dynamics
• Process Design Optimization
• +۵ مورد دیگر

Nikolaos A. Diangelakis is an Assistant Professor at the Technical University of Crete (TUC), affiliated with the School of Chemical Engineering (ChEnvEng) and the Division II: Process Development, Analysis and Design. His research focuses on system dynamics, process control, and integrated process design optimization. He holds a PhD from Imperial College London (2017), an M.Sc. from the same institution (2012), and a Diploma in Chemical Engineering from the National Technical University of Athens (2011). He has conducted a Visiting Ph.D. research at Texas A&M University (2017). Diangelakis specializes in multi-parametric optimization and control strategies, with applications in chemical, environmental, and energy systems. He has contributed to software tools like PAROC and POP, advancing explicit model predictive control (MPC) and robust optimization frameworks. His work integrates process design, scheduling, and control to enhance operational efficiency in industries such as pharmaceuticals and energy systems. He has secured research funding through projects like 'PAROC' (National Science Foundation) and 'U Psi Psi' (EPSRC), and has been recognized with awards including the 2017 Excellence Award for Outstanding PhD Thesis in Computer-Aided Process Engineering (CAPE). His academic contributions span over 30 peer-reviewed publications, emphasizing topics like microgrid optimization, rotary tablet press control, and energy-efficient industrial processes. Diangelakis teaches Linear Algebra at TUC and actively engages in academic conferences, delivering invited lectures and presenting innovative research on MPC strategies and process operability. His research group collaborates internationally, advancing the frontiers of model-based systems engineering.

• Human Factors
• Human-Computer Interaction
• E-Health
• +۶ مورد دیگر

John Paulin Hansen is a Professor at the Technical University of Denmark (DTU), affiliated with the Department of Technology, Management and Economics under the Technology and Business Studies school. His research focuses on human factors, human-computer interaction, and assistive technologies, particularly in gaze interaction and rehabilitation robotics. He holds a Ph.D. from Aarhus University (1992) and has led research groups at institutions like Risø National Laboratory and the IT University of Copenhagen. His work emphasizes improving quality of life for individuals with motor disabilities through innovations like The Eye Tribe and GazeIT lab initiatives. Research Interests include: Eye-tracking technology and gaze interaction systems Exoskeletons and AR interfaces for stroke rehabilitation Human digital twins in healthcare Telepresence robotics accessibility Brain-computer interfaces (BCI) Key Achievements: Founded EU’s COGAIN network, co-created The Eye Tribe startup (acquired by Facebook/Oculus), and leads the GazeIT lab supported by the Bevica Foundation. His projects address sustainable development goals through inclusive technology solutions. Awards: Vanførefondens Forskerpris 2018 Multiple Best Paper Awards (2019–2022) Reviewers' Favourite Best Paper Award at DESIGN2022 Advising & Grants: Mentor to startups like The Eye Tribe and Orbital (acquired by GN Audio). Current projects include EU Horizon 2020 Rehyb initiative for AR exoskeleton interfaces and Human Digital Twin applications in rehabilitation. Labs/Teams: GazeIT lab pioneers assistive tech innovations, collaborating with LEGO and Serious Games Interactive. Active in developing inclusive design pedagogy and digital twin methodologies for healthcare.

Fu Huمشاهده پروفایل

استاد

• Trauma Care
• Medical Informatics
• Critical Care Monitoring
• +۵ مورد دیگر

Fu Hu, Ph.D., is a Professor in the Department of Anesthesiology at the University of Maryland School of Medicine. He holds secondary appointments in Epidemiology & Public Health and Surgery. His research focuses on trauma care, predictive analytics, telemedicine, and medical informatics, with an emphasis on leveraging continuous vital signs and machine learning to improve patient outcomes. Key areas include traumatic brain injury monitoring, blood transfusion prediction, and critical care systems design. Education: B.S. in Electrical Engineering (Shanghai University, China, 1984), M.S. and Ph.D. in Computer Science (University of Maryland Baltimore County, 1992 and 2013). Research interests span medical AI, surgical workflow optimization, and telemedicine platforms. His work integrates advanced computational methods with clinical data to address challenges in trauma and critical care. Recent efforts include developing algorithms for real-time patient monitoring and decision support systems. He has led/co-investigated multiple grants on topics like non-invasive monitoring, trauma patient outcomes, and telemedicine. His publications highlight innovations in predictive modeling, medical imaging analysis (e.g., retinal disease detection), and clinical informatics. Notable collaborations include studies on automated ICP monitoring and the ONPOINT project for trauma care.

• Digital Transformation
• Educational Technology
• Curriculum Analytics
• +۱ مورد دیگر

Venky Shankararaman is Professor of Information Systems (Education) and Vice Provost (Education) at Singapore Management University. A PhD graduate from University of Strathclyde (1992), he holds the SMU Fortitude Fellow in Computing Education position and serves as President of Asia-Pacific Association for International Education. Research expertise spans digital transformation, educational analytics, and enterprise architecture. Primary focus areas include AI governance frameworks, curriculum analytics, and microservices design patterns. Publications emphasize practical applications in government AI systems (ACQAR framework), educational technology (ChatGPT mentoring), and enterprise architecture (microservices decision frameworks). Recent work explores explainable AI for public sector and project-based learning models. Major Awards: Public Administration Medal (Silver) - Singapore Government (2023) Distinguished Education Award - SMU (2023) AIS Best Conference Paper Award (2020) Public Administration Medal (Bronze) - Singapore Government (2017) SAP Outstanding Academic Award (2014) Advises PhD students Kevin TAUKOOR Heman and Ng Kok Leong. Leads university-wide education initiatives including the Data Access and Use Committee and Teaching Bank project. Pioneered SMU's competency-based curriculum analytics tools and digital transformation frameworks for banking. Serves on ACM Education Advisory Committee and developed national skills frameworks for Singapore's IT workforce.

Trevor Cickovskiمشاهده پروفایل

استادیار

• Bioinformatics
• Microbiome Analysis
• GPU Computing
• +۶ مورد دیگر

Trevor Cickovski is an Assistant Professor at Florida International University's Knight Foundation School of Computing and Information Sciences, with a focus on bioinformatics and computational biology. Holding Graduate Faculty status, he specializes in microbiome analysis, GPU computing, network analysis, and Unix systems. His academic journey began with a Ph.D. in Computer Science and Engineering from the University of Notre Dame (2008). Current roles: Associate Director, Assistant Teaching Professor Research affiliations: Bioinformatics Research Group (BioRG), ACM, IEEE Dr. Cickovski's research spans microbiome analysis, software engineering, and GPU-accelerated computing. His work explores the microbiome's role in neuropsychiatric disorders (ADHD), genetic conditions (A1AD), respiratory diseases (COPD), and environmental phenomena (red tides) through multi-omics integration. His publications in Journal of Medical Microbiology , Bioinformatics , and IEEE/ACM TCBB reflect strengths in plugin-based software frameworks (PluMA), network analysis, and computational pipeline optimization. Awards include multiple teaching excellence honors and industry funding from NVIDIA. 2020 Graduate Faculty Status 2019 FIU CAT Fellow 2019 FIU Faculty Teaching Award 2017 Teaching Excellence Award 2014 Promotion to Associate Professor As lead developer of PluMA, he enables cross-language plugin development for bioinformatics workflows. Funded by NIJ and NSF, his projects apply machine learning to epigenetics and computational approaches to vaccine discovery.

Alex Savachkinمشاهده پروفایل

دانشیار

• Resilience Engineering
• Operations Research
• Public Health
• +۵ مورد دیگر

Alex Savachkin is an Associate Professor and Graduate Director in the Department of Industrial & Management Systems Engineering at the University of South Florida, Tampa. His academic career is complemented by industry experience as a technology feasibility analyst at MBS Consulting and industrial engineer at Integral Inc., both in Minsk, Belarus. He holds a Ph.D. in Industrial Engineering from Texas A&M University (2005), an M.S. in Management of Technology from the University of Colorado (1998), and a B.S. in Industrial Engineering/Applied Math from Belarusian State University (1996). Savachkin's research focuses on applying applied stochastic processes to design resilient cyber-physical-social systems. Key research areas include stochastic measures of system resilience, assessment of resilience in physical and social systems, and multi-objective optimization models for resilience enhancement. His work bridges theoretical frameworks and practical applications in infrastructure and healthcare systems. His academic contributions are highlighted by teaching awards: the IIE Annual Award for Excellence in the Teaching of Operations Research (2013) and USF Outstanding Undergraduate Teaching Award (2012) . In advising, he has guided PhD students such as Daniel Romero (2018), Sandro Paz (2014), and co-advised Dayna Martinez (2012) and Diana Prieto (2012). Current advisee Weimar Ardilla is pursuing a Ph.D. His research team collaborates on projects spanning pandemic preparedness and infrastructure resilience. His research trends emphasize balancing costs/benefits in resilience decisions (2025), critical reviews in system resilience (2025), and pandemic influenza outbreak modeling (2024–2010). He specializes in resilient distribution networks, heuristic algorithms for optimization, and cross-regional resource allocation strategies.

Varadraj Gurupurمشاهده پروفایل

دانشیار

• Health Informatics
• Decision Support Systems
• Data Semantics
• +۳ مورد دیگر

Varadraj Gurupur is an Associate Professor at the University of Central Florida (UCF) in the School of Global Health Management and Informatics. He holds a Ph.D. and has over 15 years of teaching experience across two countries. His research focuses on software engineering decision support systems for healthcare and education, with a particular emphasis on health informatics, decision support systems, and data semantics. He has received numerous awards, including the AHIMA Triumph Award for Innovation (2021) and the Joseph M. Biedenbach Outstanding Engineering Educator Award (2023). Dr. Gurupur has authored over 100 peer-reviewed publications, including journal articles, conference papers, and book chapters. He has secured research grants and holds three patents in health information management. His work addresses challenges in electronic health records (EHRs), telehealth, and data quality, with applications in diabetes care, dental imaging, and frailty assessment in aging populations. He is active in IEEE, having chaired the Workgroup on Data Quality for EHRs and served as Chair of the IEEE Orlando Section (2021–2023). Key contributions include developing AI-driven decision support systems, improving EHR data completeness through neural network models, and advancing telemedicine frameworks. His interdisciplinary research bridges clinical needs with technological solutions, emphasizing global health equity and patient-centric care.

Hua Dongمشاهده پروفایل

استاد

• Inclusive Design
• User-Centered Design
• Human-Computer Interaction
• +۶ مورد دیگر

Professor Hua Dong is a leading academic in inclusive design at Brunel University London , serving as Full Professor in Design, Director of Brunel Design Research Centre, and Inaugural Dean of Brunel Design School (2020-2024). She was elected Vice-Chair of the Design Research Society (DRS) in 2024, is a Fellow of DRS, and will chair QAA's Art and Design Subject Benchmarking Statement in 2025-26. Research Expertise: Dong pioneers inclusive design theory and application across industrial, engineering, architectural, and service design domains, with a focus on AI-powered products, mHealth for aging populations, and multisensory design. Her work bridges academia and industry through projects like the Design Bugs Out Challenge and collaborations with Ant Financial, Shanghai M&G Stationery, and UK-China initiatives. Scientific Contributions: She has secured major grants including an EPSRC grant and Newton Funds . Her publications span 2007-2024, covering AI-enhanced design ideation, service ontology for aging populations, and sustainable inclusion frameworks. She co-founded the Inclusive Design Research Centre in China and curated a special issue on inclusive design for Design magazine. Scientific Awards: Fellow of Design Research Society (2019) AHRC SEED Fellowship Member of Peer Review College of AHRC Teaching & Leadership: Dong holds a PGCert in Academic Practice and has shaped design education through co-design methodologies. She has supervised 14 PhD and 1 EngD student completions, organized the Cambridge Workshop for Universal Access since 2014, and served as External Examiner at Imperial College. Global Impact: As International Judge for SDGs Design Awards and advisor to UK charities (AgeUK), governments (Nanjing), and corporations (Reckitt Benkiser), she translates design research into tangible societal benefits. Her work has been exhibited at international venues including the Milan Triennale and Zurich Design Museum .

Maitreyee Deyمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Artificial Intelligence
• Low Carbon Technologies
• +۹ مورد دیگر

Dr. Maitreyee Dey serves as a Visiting Fellow in Mechanical Engineering and Design and works as a Post-doctoral research fellow at London South Bank University's Department of Electrical and Electronics Engineering. She concurrently holds the position of Data Mining Lead at Neuville Grid Data Management Limited, where she contributes to significant energy research projects. Her research expertise spans machine learning/artificial intelligence and low carbon technologies, with additional interests in pattern recognition, big data analysis, deep learning, image processing, energy optimization in smart buildings, renewable energy technology, and Computer-aided Diagnosis for smart health applications. Her work directly contributes to UN Sustainable Development Goals related to clean energy and sustainable communities. Analysis of her recent publications reveals a strong research trajectory focusing on two primary domains: power grid analysis using machine learning techniques and microwave-based medical imaging for breast cancer detection. Her work demonstrates sophisticated applications of neural networks and data mining methods to solve complex problems in both energy systems and medical diagnostics. Best Paper Award at the CUE conference, Elsevier (2020) Endorsement by the Royal Academy of Engineering Dr. Dey serves as an Editorial board member for MDPI journals and as an Adhoc reviewer for high-impact publications including IEEE transactions and Nature Scientific Data. She is actively involved in the Access to Innovation (A2i) and Low Carbon London (LCLDN) projects funded by the EU commission through its regional development Fund, working in collaboration between London South Bank University and Neuville Grid Data Management Limited. Her professional affiliations include active membership in IEEE, CIGRE NGN, and the Energy Institute, demonstrating her engagement with key professional organizations in her fields of expertise.

Hong Qinمشاهده پروفایل

استاد

• Computer Graphics
• Geometric Modeling
• Physics-Based Modeling
• +۵ مورد دیگر

Hong Qin is a Full Professor (with tenure) in the Department of Computer Science at Stony Brook University, where he is also a member of the Center for Visual Computing. He holds a B.S. and M.S. from Peking University, and a Ph.D. from the University of Toronto. His research focuses on computer graphics, geometric modeling, physics-based simulation, and scientific visualization. Education: B.S. (1986) and M.S. (1989) in Computer Science from Peking University; Ph.D. (1995) in Computer Science from the University of Toronto. Research interests include geometric modeling, computer-aided design, scientific visualization, medical imaging, and robotics. He has received notable awards like the NSF CAREER Award (1997), Alfred P. Sloan Fellowship (2001-2005), and multiple NSF grants. Qin has organized major conferences such as Computer Graphics International 2005 and chairs editorial boards for IEEE TVCG and The Visual Computer.

Tzu-Chieh Kurt Hongمشاهده پروفایل

استادیار

• Shape Grammars
• Visual Computing
• Generative Modeling
• +۴ مورد دیگر

Dr. Tzu-Chieh Kurt Hong is an Assistant Professor at the Department of Architecture within the School of Architecture and Design at the University of Kansas. He teaches design studios, algorithmic modeling, parametric design, and computer programming in design studies. He founded K9K Research & Design, focusing on innovative computational design methodologies. His research emphasizes shape grammars, visual computing, and generative modeling, particularly through the development of the Shape Machine—a computational tool integrating shape recognition and rewriting into CAD systems. Education: Ph.D. in Architecture (Design Computation), Georgia Institute of Technology (2021) M.S. in Architecture and Design, University of Michigan (2016) Master of Architecture, National Chiao Tung University (2008) M.S. and B.S. in Electronics Engineering, National Chiao Tung University (Taiwan) Research Interests: Shape embedding and rewriting in CAD systems Algorithmic design and generative systems Integration of traditional methods (e.g., Euclidean geometry) with computational tools Applications in architectural education and practice Awards: 2022 ARCC Dissertation Award for contributions to CAD systems through shape recognition research Professional Experience: Research Scientist at Georgia Tech's Shape Computation Lab (2016–2022) Contributions include the Shape Machine framework and the Smart 3D Atlanta visualization platform Labs/Teams: Leads the K9K Research & Design initiative, collaborating with academic and industry partners on computational design tools and generative workflows.

John Rasmussenمشاهده پروفایل

استاد

• Biomechanics
• Rehabilitation Robotics
• Musculoskeletal Simulation
• +۲ مورد دیگر

John Rasmussen is a Professor and Vice Head of the Department of Materials and Production at Aalborg University's Faculty of Engineering and Science. He founded the AnyBody Research Group and served as CEO of AnyBody Technology A/S. His research focuses on biomechanics, rehabilitation robotics, and musculoskeletal simulation, with applications in exoskeleton design and orthopedic interventions. Education: Ph.D. in Computer-Aided Design (Aalborg University, 1989) M.Sc. in Mechanical Engineering (Aalborg University, 1986) Research Interests: Biomechanics, CAD optimization, finite element analysis, and biomedical engineering. His work bridges computational modeling with clinical solutions for mobility disorders. Article Trends: Recent publications emphasize exoskeleton design, spinal biomechanics, and osteoarthritis interventions, utilizing experimental and simulation approaches across robotics and orthopedics. Awards: Wearable Robotics Innovation Prize (2018) Grand Challenge Competition Winner (2014) Steno Prisen (2012) Teacher of the Year (2011) Leadership: Manages the Center for Rehabilitation Robotics and oversees 37 research projects. Advises industry collaborations in assistive technology.

Shuang Liuمشاهده پروفایل

پژوهشگر

• Embedded Systems
• Computer Architecture
• Networks-on-Chip (NoC)
• +۳ مورد دیگر

Shuang Liu is a Researcher at the Institute of Computer Architecture and Computer Engineering, University of Stuttgart. Their work focuses on embedded systems, networks-on-chip (NoC), and chip design methodologies. They specialize in deadlock-free routing, fault-tolerant computing, and application-specific system synthesis using advanced techniques like integer linear programming. Research interests include optimizing NoC architectures for chiplet-based systems, co-design of floorplanning and routing topologies, and energy-efficient signal processing in medical electronics. Their recent work emphasizes formal verification methods and performance optimization in hardware-software co-design. Publications span topics such as deadlock prevention in NoC, ILP-based routing synthesis, and trade-offs in hearing aid ASIP design. Office hours are Monday 2–3 p.m. in Room 1.001, Pfaffenwaldring 5b, Stuttgart.

Chadi Assiمشاهده پروفایل

استاد

• Wireless Networks
• Information Security
• Cybersecurity
• +۶ مورد دیگر

Chadi Assi is a Professor and Tier II Concordia Research Chair at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on wireless networks, information security, and smart grid systems, with particular emphasis on reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), cybersecurity for electric vehicles (EVs), and machine learning-driven network optimization. He has pioneered work on mitigating cyber-physical attacks in power grids and IoT ecosystems, while advancing cooperative communication protocols like RSMA and NOMA. His technical contributions span theoretical frameworks for energy efficiency maximization in hybrid SDMA/NOMA schemes, low-complexity RIS element selection algorithms, and adversarial PINN models for grid dynamics. He also investigates vulnerabilities in EV charging infrastructure and O-RAN synchronization protocols, proposing robust detection mechanisms like PEACE and Grid Mirror. His interdisciplinary work bridges communications, power systems, and AI, addressing challenges in 5G/6G security and resilient IoT provisioning. Key Research Areas: RIS-enabled ISAC networks, EV cybersecurity, meta-learning in communications, IoT malware analysis Current Projects: Grid resilience against load-altering attacks, Movable antenna optimization, federated learning for AGC systems Recent publications (2024-2025) emphasize deep reinforcement learning frameworks for RIS-aided networks, cooperative RSMA performance enhancement, and defense mechanisms against dynamic trigger-based attacks. He has also developed novel datasets for advanced persistent threats and frameworks like ChargePrint for EV charging security analysis. His work is published in top venues including IEEE Transactions on Smart Grid, IEEE JSAC, and IEEE ICC, reflecting contributions to both theoretical advancements and practical system implementations.