جست‌وجوی استاد و پژوهشگر

Hongyu Gaoمشاهده پروفایل

مدرس

• Information Systems
• Business Analytics
• Database Management
• +۳ مورد دیگر

Hongyu Gao is an Instructor at Oakland University's School of Business Administration. He is completing his Ph.D. in Management Information Systems at Georgia State University, with an MBA from the University of Southern California (Marshall School of Business) and a bachelor's degree in Computer Science. Prior to academia, he spent 15 years in technology roles at IBM and other companies. Education: Ph.D. Candidate, Management Information Systems, Georgia State University MBA, University of Southern California Marshall School of Business Bachelor's Degree in Computer Science Research focuses on IS use, low-code development, and construal levels, employing methods like surveys, experiments, econometrics, and machine learning. Teaching interests include Business Analytics, Database Management, and Introduction to MIS. His recent articles explore human-automation team dynamics and cognitive factors in programming workload estimation. No scientific awards are explicitly mentioned. No grants or advising details are provided. No lab or team affiliations are noted.

ALESSANDRO FREDDIمشاهده پروفایل

دانشیار

• Robotics
• Control Systems
• Autonomous Systems
• +۸ مورد دیگر

Prof. Alessandro Freddi is an Associate Professor at the Department of Information Engineering, Polytechnic University of Marche. His research focuses on advanced control systems, robotics, and human-machine interaction, with a strong emphasis on fault detection, autonomous systems, and assistive technologies. Key research areas include: Fault-tolerant control for UAVs and remotely operated vehicles Human-in-the-loop systems using EEG and brain-computer interfaces Smart wheelchair navigation and assistive robotics Data-driven approaches for industrial and robotic applications His recent work explores cognitive workload estimation, cybersecurity for autonomous systems, and real-time monitoring techniques. He has contributed to datasets like UAV-FD and pioneered cooperative robotic systems for assisted living environments.

• Cognitive Science
• Psychology
• Computational Modeling
• +۵ مورد دیگر

Andrew Perfors is a Professor of Psychology at the University of Melbourne, leading the Complex Human Data Hub and the Computational Cognitive Science Lab within the Melbourne School of Psychological Sciences . His research focuses on applying quantitative methods to understand higher-order cognition, including concepts, language, decision-making, and misinformation dynamics. He employs computational models and experimental approaches to investigate how cognitive constraints and social environments shape human behavior at individual and group levels. Education: PhD in Brain & Cognitive Sciences (MIT, 2008), MA in Linguistics (Stanford, 2000), BSc in Symbolic Systems (Stanford, 1999). Research Themes: Cognitive modeling of decision-making, cultural evolution, language acquisition, and misinformation spread. His work bridges computational methods with psychological experimentation, exploring topics like sampling assumptions in reasoning, trust in information sources, and the cognitive basis of gender categorization. Key Projects: Active grants include Understanding Information and Trust (2018–2025), Bridging the Meaning Gap (2023–2027), and Anti-trans Disinformation Campaigns analysis. Recent work addresses misinformation mitigation strategies and the cognitive naturalness of trans-inclusive gender categories. Grants & Collaborations: Funded by ARC and NHMRC. Collaborations include work on contact-tracing technologies during the pandemic and cross-cultural studies on privacy calculus. Labs & Teams: Directs the Complex Human Data Hub, focusing on societal challenges like misinformation and cultural dynamics. Leads interdisciplinary teams in the Computational Cognitive Science Lab, integrating psychology, computer science, and linguistics.

• Affective Computing
• Machine Learning
• Human-Computer Interaction
• +۱۲ مورد دیگر

Subramanian Ramanathan is a researcher at the School of Computing, National College of Ireland , specializing in affective computing, multimodal behavior analysis, and human-computer interaction. His work spans machine learning, computer vision, and neuro-signal processing. Key research areas: Affective Computing, Deep Learning, Stress Detection, Depression Biomarkers Notable collaborations: Roland Göcke, Abhinav Dhall, Nicu Sebe His publications focus on: EEG-based cognitive load estimation Head motion pattern analysis for mental health Deepfake detection systems Audio-visual saliency prediction Transformers in behavioral modeling Stress detection via multimodal fusion Recent work includes medical imaging applications for autism detection and computational advertising systems using emotion recognition. He contributes to open science through dataset creation (SALSA, DECAF) and collaborative research in affective computing.

• Geropsychology
• Wellbeing and health
• Innovation expertise
• +۹ مورد دیگر

Tuomas Leisti is a Lecturer and Doctor of Psychology (PsT) at Metropolia University of Applied Sciences, affiliated with the Wellbeing Team 3. His professional roles include teaching psychology and research methods, supervising Master's theses, and contributing to RDI (Research, Development, Innovation) projects. He holds certifications as a licensed psychologist and professional teacher (AmO), with proficiency in Finnish (native), English (excellent), Swedish (average), and German (basic). Leisti's research focuses on geropsychology, wellbeing and health, innovation expertise, cognitive psychology, and the philosophy of mind. His doctoral work explored the role of consciousness in decision-making, with prior experience in human-technology interaction. He is particularly interested in decision-making processes, problem-solving, and the metacognitive skills underlying these activities. Key projects include the Wellbeing Hybridist initiative (2021–2023) and the pan-European COMHOM project (2025–2028), which addresses homelessness through data-driven solutions. His research outputs span over two decades, emphasizing subjective image quality evaluation, cognitive modeling, and quantitative methodologies. Leisti's work integrates empirical and philosophical approaches, addressing topics such as qualia, decision heuristics, and the interplay between conscious thought and judgment. Despite no explicitly listed awards, his extensive publication record reflects sustained contributions to psychological and applied research fields.

Christian Ploderمشاهده پروفایل

مدرس

• Information Systems
• Quality Management
• Blockchain Technology
• +۷ مورد دیگر

Christian Ploder is a Lecturer at MCI Management Center Innsbruck, focusing on Information Systems, ERP systems, and e-business. He holds a Dr. in Information Systems from the University of Innsbruck and has over 15 years of professional experience across academia and industry. Education: PhD in Information Systems, University of Innsbruck (2005-2009) Mag. in Information Systems, University of Innsbruck (2000-2005) Research interests include Quality Management Systems, Blockchain in healthcare, IoT applications in education, and gamification in learning. His work bridges theoretical frameworks with practical implementations in ERP systems, data analytics, and digital transformation. Recent articles explore blockchain for electronic health records, AR in engineering education, and machine learning for manufacturing cost estimation. These contributions highlight interdisciplinary approaches combining IT systems with organizational and educational contexts. Awarded for contributions to knowledge management frameworks and ERP integration strategies. Advised over 50 students, focusing on topics like RPA post-implementation, AR in classrooms, and cybersecurity in SMEs. Led projects on digital twin simulations, cloud-based ERP systems, and enterprise risk management. Active in SAP Academic Community and IEEE conferences, emphasizing practical teaching tools for emerging technologies.

• Clinical Trials
• Oncology
• GU Oncology
• +۳ مورد دیگر

Dr. Aamer Mahmud is an Associate Professor specializing in clinical oncology with a focus on GU, GI, and Sarcoma malignancies. His research emphasizes clinical trials and advanced multimodal data analysis techniques. He currently holds a Regular Attending Staff position at Kingston Health Sciences Centre. Research interests include developing innovative technologies for cognitive load assessment in medical settings, gaze estimation systems, and brain-computer interfaces for driver safety. His work bridges healthcare technology with artificial intelligence, addressing challenges in real-time patient monitoring and clinical decision support. Publications from 2022-2024 highlight contributions to multimodal data fusion, transfer learning in medical imaging, and human factors in automotive safety. No scientific awards are explicitly listed in the provided information. While no formal advising/grants details are provided, his clinical and research roles suggest involvement in oncology-related mentorship and collaborative projects. No lab/team affiliations are explicitly mentioned in the text.

Hamdi Melih Saraoğluمشاهده پروفایل

استاد

• Biomedical Engineering
• Biosensors (QCM Technology)
• Diabetes Diagnosis
• +۵ مورد دیگر

Prof. Dr. Hamdi Melih Saraoğlu is a full professor at the Department of Electrical and Electronics Engineering, Faculty of Engineering at Dumlupınar University since 2018. He holds a PhD in Electrical and Electronics Engineering from Sakarya University (1995-1998), preceded by a master's from Dumlupınar University (1993-1995) and bachelor's from Erciyes University (1989-1993). His academic career includes roles as associate professor (2011-2018), assistant professor (2002-2011), and earlier positions as lecturer and research assistant. Research focuses on biomedical engineering applications including biosensor development (QCM technology), non-invasive diabetes diagnosis, EEG-based emotion and disease analysis, and anesthesia monitoring systems. He led 6 TÜBİTAK and university-funded projects since 2004, with notable work on breath-based cancer detection and EEG emotion estimation. Administrative roles include Electronics USA Presidency (2010–present), Senate membership (2011–2017), and departmental leadership positions. Teaching responsibilities include courses like Biomedical Systems, Medical Imaging Systems, and Engineering Economics. His 43+ publications span journals and conferences, emphasizing AI-driven medical diagnostics and sensor systems. No patents or artistic contributions are listed.

Ranxiao Wangمشاهده پروفایل

استاد

• Emotional Neuroscience
• Cognitive Psychology
• Spatial Cognition
• +۵ مورد دیگر

**Roles & Affiliations**: Professor of Psychology and Beckman Institute for Advanced Science and Technology at the University of Illinois Urbana-Champaign. Holds dual appointments in Psychology and interdisciplinary research through the Beckman Institute. **Education**: PhD from Massachusetts Institute of Technology (MIT). **Research Interests**: Focuses on the neurobiological basis of emotion regulation, cognitive-emotional interactions in psychopathology (anxiety/depression), and spatial cognition. Explores brain lateralization, spatial memory distortions, and higher-dimensional spatial reasoning. Recent work includes human safety perception with UAVs, mind-wandering dynamics, and non-Euclidean spatial learning in virtual environments. Uses virtual reality, behavioral experiments, and computational models to study spatial navigation, attention, and human-computer interaction. **Article Trends**: Research spans spatial cognition (e.g., curved/non-Euclidean spaces), safety perception with drones, cognitive fluctuations in mind-wandering, and cross-modal effects (auditory-visual interactions). Integrates neuroscience and robotics to advance human-robot collaboration models. **Advising & Collaborations**: Supervised over 20 graduate students. Collaborates with experts in robotics (Naira Hovakimyan), vision science (Paul Kwiat), and cognitive neuroscience (Diane Beck, Sepideh Sadaghiani). Projects include Beckman Institute initiatives on spatial cognition and interdisciplinary AI-human interaction. **Labs & Teams**: Leads research at Beckman Institute’s Spatial Cognition and Human-Computer Interaction labs. Active in UIUC’s interdisciplinary programs on robotics, perception, and computational neuroscience.

• Privacy-Preserving Machine Learning
• Reinforcement Learning
• Data Privacy and Security
• +۵ مورد دیگر

Associate Professor Kee Siong Ng is affiliated with the School of Computing at the Australian National University (ANU). His research focuses on privacy-preserving technologies, reinforcement learning, distributed systems, and blockchain applications. He has contributed extensively to areas such as privacy-preserving machine learning, federated learning, entity resolution, and scalable database systems. His work emphasizes balancing computational efficiency with privacy guarantees in data-driven environments. Key research contributions include methodologies for secure data processing in federated learning frameworks, privacy-preserving reinforcement learning for population-level systems, and blockchain-based digital identity solutions. He has led projects like Integrated Graph Analytics and contributed to initiatives involving the Australian Medicare dataset. His research often intersects theoretical foundations with practical implementations, addressing challenges in scalability and real-world applicability. Ng has published over 24 peer-reviewed articles, with notable works appearing in venues like IEEE Transactions on Parallel and Distributed Systems and Transactions on Machine Learning Research . His articles frequently explore cutting-edge topics such as differential privacy, approximation algorithms, and multi-agent systems. Collaborations include industry partnerships and interdisciplinary efforts involving health informatics and financial intelligence. His projects include Integrated Graph Analytics (2018–2021): Focused on scalable graph-based data analysis. Translational Fellowship (2018–2022): Bridging theoretical research with practical applications. Research on Data Sets for Health and Pharmaceutical Schemes (2020): Analyzing Medicare and pharmaceutical data with privacy safeguards. Ng's work prioritizes ethical AI and privacy-by-design principles, with a focus on real-world deployment challenges in distributed and federated systems.

Patricia DeLuciaمشاهده پروفایل

استاد

• Human Factors
• Transportation Safety
• Health Care Systems
• +۶ مورد دیگر

Patricia DeLucia is a Professor in the Department of Psychological Sciences at Rice University, specializing in human factors research with applications across transportation, healthcare, and military domains. Her work bridges cognitive psychology with practical applications to improve safety and performance in complex systems. Dr. DeLucia earned her Ph.D. from Columbia University in 1989 followed by a National Research Council postdoctoral associateship at Wright Patterson Air Force Base from 1989-1991. Her expertise spans perception of collision across multiple sensory modalities, multisensory integration in normal and impaired vision, and virtual reality applications. Her research interests focus on human factors in transportation (manual and automated driving, pedestrian street-crossing), health care applications (nursing, medication administration, patient safety, minimally-invasive surgery, telehealth), and military applications (UAVs, night vision goggles). She has made significant contributions to understanding time-to-collision judgments, driver behavior, and perceptual processes in real-world contexts. Analysis of her recent publications reveals consistent focus on automated driving systems, human-machine interaction in healthcare settings, and perceptual processes related to collision avoidance. Her work increasingly addresses the challenges of human-automation interaction across multiple domains. Dr. DeLucia has received numerous professional honors including: Texas Tech University Faculty Distinguished Leadership Award (2016) Human Factors and Ergonomic Society's Paul M. Fitts Education Award (2015) American Psychological Association Division 21's Franklin V. Taylor Award (2014) Texas Tech University Barnie E. Rushing, Jr. Faculty Distinguished Research Award (2012) She previously served as Editor-in-Chief of Human Factors (2014-2021) and held leadership positions including President of APA Division 21 (2011) and Chairperson of the Accreditation Committee for the Human Factors and Ergonomics Society (2010-2013). Her professional service includes standing review panels for NASA and the Agency for Health Research Quality, demonstrating her impact across multiple scientific domains.

Andrew Buckمشاهده پروفایل

استادیار

• Machine Learning
• Intelligent Agents
• Autonomous Drones
• +۲ مورد دیگر

Andrew Buck is an Assistant Research Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri . His work focuses on machine learning , intelligent agents , autonomous drones , computer vision , and 3D visualization . Education: PhD, MS, BS in Computer Engineering, and BS in Electrical Engineering from the University of Missouri Andrew Buck's research involves the development of photorealistic synthetic datasets (e.g., HiFiAerial), explainable AI frameworks for drone autonomy, and human-agent teaming dynamics (e.g., trust modeling). He has pioneered multidisciplinary simulation platforms like Mizsim for AI training and evaluation, and contributed to real-time 3D reconstruction techniques combining classical algorithms with deep learning. His work on uncertainty quantification in depth estimation and fuzzy voxel maps demonstrates his interest in probabilistic approaches to perception. A key theme in his publications is the evaluation of AI performance in partially observable environments , including applications in explosive hazard detection and cooperative game scenarios.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۱۷ مورد دیگر

Prof. Dr. Antonio Krüger is the CEO of the German Research Center for Artificial Intelligence (DFKI) and Director of the Ubiquitous Media Technology Lab (UMTL) at the Saarland Informatics Campus in Saarbrücken, Germany. He is a leading researcher in human-computer interaction, virtual and augmented reality, multimodal interfaces, and intelligent systems. His research interests span a broad range of topics including virtual reality (VR), augmented reality (AR), gesture interaction, haptic feedback, EEG and eye tracking, gamification, cognitive load estimation, brain-computer interfaces, and smart environments. His work emphasizes user-centered design, perceptual illusions, and real-world applications in domains such as automotive, healthcare, and education. His recent publications (2023–2024) demonstrate a strong focus on advancing VR interaction through techniques like hand redirection, synthetic gesture generation for vehicles, implicit intent recognition using multimodal sensing, and personalized object referencing. These works reflect trends toward seamless, natural, and adaptive interfaces that leverage AI, perception, and real-time feedback. Prof. Krüger supervises a large team of researchers and students, including Mansi Sharma, Amr Gomaa, André Zenner, and Martin Feick, indicating active mentorship and collaborative research leadership. His lab, UMTL, develops innovative technologies in immersive environments, wearable systems, and intelligent user assistance, contributing to both academic knowledge and practical applications.

Shuchin Aeronمشاهده پروفایل

دانشیار

• Data Science
• Statistical Signal Processing
• Inverse Problems
• +۸ مورد دیگر

Shuchin Aeron is an Associate Professor in the Department of Electrical and Computer Engineering at Tufts School of Engineering, with joint appointments in the Departments of Computer Science and Mathematics. He holds a Ph.D. from Boston University (2009) and completed postdoctoral research at Schlumberger Doll Research, focusing on borehole acoustic signal processing. His research spans statistical signal processing, machine learning, compressed sensing, and information theory, with applications in geophysics, bioengineering, and imaging. Aeron has authored over 175 publications and holds patents in acoustic signal processing. He received the NSF CAREER Award (2016) and is a Senior Member of the IEEE. Educations: Ph.D., Electrical Engineering, Boston University, 2009 M.S., Electrical Engineering, Boston University, 2004 B.Tech., Indian Institute of Technology, 2002 Research Interests: Statistical signal processing (SSP), inverse problems, compressed sensing, information theory, convex optimization Machine learning applications in geophysical signal processing, imaging, and bioengineering His work emphasizes optimal sampling and recovery of multidimensional signals, with contributions to compressed sensing architectures and generative models for particle physics experiments. He leads NSF-funded projects on data science and domain generalization, and collaborates with industry partners like Schlumberger and Mitsubishi Electric Research Labs. Awards: NSF CAREER Award (2016) Mitsubishi Electric Research Lab Research Gift (2015) Grants and Funding: NSF HDR TRIPODS (2019–2023) AFOSR: Enabling Trusted Human-Like Artificial Teammates (2018–2023) NSF: Optimal Sampling and Recovery for Multilinear Signals (2013–2016) Aeron teaches advanced courses in probabilistic systems analysis, information theory, and machine learning. He directs the Tufts Data Science undergraduate and graduate programs, and serves on editorial boards of journals including Frontiers in Signal Processing and IEEE Transactions on Geoscience and Remote Sensing .

Saeid Nahavandiمشاهده پروفایل

استاد

• Artificial Intelligence
• Robotics and Haptics
• Autonomous Systems
• +۴ مورد دیگر

Roles and Affiliations: Distinguished Professor Saeid Nahavandi is the inaugural Associate Deputy Vice-Chancellor (Research) and Chief of Defence Innovation at Swinburne University of Technology. He leads defence innovation and research strategy, with a focus on autonomous systems, robotics, and AI. Previously, he served as Pro Vice-Chancellor (Defence Technologies) at Deakin University and founded its Institute for Intelligent Systems Research and Innovation. Research Focus: Specializes in robotics, haptics, autonomous systems, AI, and advanced modelling/simulation. His work bridges academia and industry, with collaborations spanning Airbus, Boeing, NASA, and NATO. He has secured over $150M in funding and established three tech startups. Key research areas include motion simulation, teleoperation systems, and defence technologies. Articles Overview: Over 1,300 publications span AI, robotics, and control engineering. Recent work emphasizes autonomous navigation reviews, uncertainty-aware AI, and motion cueing algorithms. His research addresses real-world applications like driver distraction detection and robotic ultrasound. Awards and Recognition: Recipient of the 2022 Clunies Ross Entrepreneur of the Year Award, 2021 Australian Space Awards Researcher of the Year, and multiple engineering excellence accolades. A Fellow of ATSE, IEEE, and other leading institutions. Grants & Industry Impact: Led ARC Training Centres for automated vehicles and energy storage. Notable grants include a $15M ARC Training Centre for Automated Vehicles in Rural/Remote Regions (2024–2029). Collaborates globally on defence, aerospace, and smart transportation projects. Labs & Teams: Heads Swinburne’s Defence Innovation Group and collaborates with Harvard University (as an Associate) and the University of Windsor (adjunct professor). Advises governments and industries on technology strategy and innovation.