جست‌وجوی استاد و پژوهشگر

Shengcheng Yuمشاهده پروفایل

پژوهشگر

• Software Testing
• GUI Testing
• Mobile App Testing
• +۵ مورد دیگر

Dr. Shengcheng Yu is a Postdoctoral Researcher at the TUM School of Computation, Information and Technology (CIT) of the Technical University of Munich (TUM) , affiliated with the Chair of Software Engineering & AI . He earned his bachelor's and Ph.D. from Nanjing University (NJU) in 2020 and 2024, respectively. Research Focus: His work bridges Software Testing with Artificial Intelligence , concentrating on GUI Testing , Mobile App Testing , Crowdsourced Testing , and GUI Automation . His methodologies integrate Image Recognition , Reinforcement Learning , and Large Language Models (LLMs) to enhance automated testing frameworks. Publications Trends: His recent studies (2023-2024) emphasize AI-driven testing tools , including vision-based GUI testing , LLM-based test script generation , and deep image-text fusion for crowdsourced test reports . Earlier work (2021) established foundations in cross-platform testing and screenshot understanding. Team Affiliation: Collaborates with Prof. Dr. Chunyang Chen and researchers such as Lukas Roschel , Wenchao Gu , and Yanqi Su .

• Bio-integrated Design
• Sustainable Bioprocess Engineering
• Industrial Biotechnology
• +۶ مورد دیگر

Brenda Parker serves as Associate Professor in the Department of Biochemical Engineering within University College London's Faculty of Engineering Sciences. She co-founded the Bio-Integrated Design Lab (Bio-ID) with Professor Marcos Cruz from the Bartlett School of Architecture, establishing an internationally recognized research platform exhibited at Centre Pompidou, London Design Festival, and Venice Biennale. Her academic journey began with an MEng in Biochemical Engineering from UCL, including specialization in microbial ecology at Caltech, followed by PhD research on non-natural amino acid synthesis via BBSRC CASE studentship with Dowpharma. Her research focuses on sustainable bioprocess design and bio-integrated architecture, addressing industrial biotechnology scalability through algal biotechnology, bioremediation systems, and circular biomaterials. The Bio-ID Lab's work spans microbiome-inspired green infrastructure, robotic fabrication of biohybrid materials, and sustainable sound absorption solutions – exemplified by the INDUS algal bioremediation project winning the Water Futures Design Challenge and Beazley Designs of the Year shortlist. Current teaching includes leadership of UCL's second-year Design and Professional Skills course and directorship of the radical interdisciplinary MSc in Bio-Integrated Design. Key Awards: Churchill Travelling Fellowship (2014) Public Engagement Award from Society for General Microbiology (2011) Royal Academy of Engineering Leadership Award Professor Parker actively mentors through her MSc program while leading research collaborations with Shell (Algal Biotechnology Consortium), Cambridge Water, and EU-funded projects including Energetic Algae and Innovation in Crops. Her Bio-ID Lab maintains strong industry partnerships through Phytofutures Ltd commercialization efforts. The lab's multidisciplinary approach integrates biochemical engineering with architectural design, creating novel platforms for urban ecosystem health and sustainable material innovation through living systems.

• Cybersecurity
• Game Theory
• Quantum Cryptography
• +۵ مورد دیگر

Stefan Rass is a Professor at the Institute of Networks and Security within the Faculty of Engineering & Natural Sciences at Johannes Kepler University Linz (JKU), where he leads the LIT Secure and Correct Systems Lab. As Principal Investigator for FFG-funded projects including reSilienz (digital supply chain resilience, 2023–2025) and ITPUK (AI signature verification, 2022–2024), he bridges theoretical game theory with practical cybersecurity solutions for critical infrastructures and robotics systems. His research spans game-theoretic security models (patrolling games, defense-in-depth strategies), quantum cryptography (QKD network architectures), and cyber deception frameworks like Honeyquest for measuring honeypot effectiveness. Recent work addresses robotics security benchmarking (RobotPerf), cryptographic instruction chaining for control flow protection, and risk assessment methodologies for interdependent infrastructures. His mathematical decision-making approach integrates bounded rationality and stochastic modeling to solve real-world security challenges. Professor Rass actively shapes the field through program committee roles (ARES 2023), peer reviews, and invited talks on security transparency. His current projects focus on cost-benefit-aware monitoring for cyber-physical systems and quantum key distribution standardization, reflecting Austria’s strategic priorities in digital resilience. The LIT Secure and Correct Systems Lab under his direction develops foundational theories while deploying tools for industrial applications, particularly in critical infrastructure protection and secure robotics workflows.

Junfeng Zhaoمشاهده پروفایل

استادیار

• Connected and Automated Vehicles
• CAV System Integration and Safety Assessment
• Motion Planning and Controls
• +۵ مورد دیگر

Dr. Junfeng Zhao is an Assistant Professor at Arizona State University's Polytechnic School within the Ira A. Fulton Schools of Engineering. He serves as the Principal Investigator of the Battery Electric & Intelligent Vehicle (BELIV) Lab and holds graduate faculty appointments in both the Robotics & Autonomous Systems (RAS) and Clean Energy Systems (CES) programs. Dr. Zhao's educational background includes: Ph.D. in Mechanical Engineering from The Ohio State University (2015), recipient of OSU Presidential Fellowship M.S. in Mechanical Engineering from University of British Columbia (2009) B.S. in Electrical Engineering from Tsinghua University (2007) Dr. Zhao's research focuses on connected and automated vehicles (CAV), with expertise spanning system integration, safety assessment, motion planning and controls, cooperative perception, AI/ML applications in automotive systems, and electrified propulsion control. His BELIV Lab develops advanced systems for battery electric and intelligent vehicles, targeting safer, cleaner, and more energy-efficient transportation solutions. With industry experience at General Motors R&D and Cummins Technical Center, his work bridges theoretical research with practical automotive applications. Analysis of Dr. Zhao's recent publications reveals a strong emphasis on cooperative perception frameworks, safety assessment methodologies for automated driving systems, integration of satellite positioning for vehicle localization, and novel testing approaches using digital twin and augmented reality technologies. His research consistently addresses critical challenges in autonomous vehicle deployment. Professional recognitions include: OSU Presidential Fellowship during doctoral studies 15 patents in automotive and vehicle systems Dr. Zhao actively mentors 9 current graduate students across PhD and Master's programs, with research areas spanning autonomous driving, battery management systems, and intelligent transportation. His former students have secured positions at major companies including Caterpillar Inc., BYD North America, and TSMC. The BELIV Lab has established itself as an Autoware Center of Excellence, received funding from industry partners like Cox, and has been featured in media coverage including The State Press and documentaries on self-driving technology. BELIV Lab maintains active industry collaborations and participates in outreach activities such as the 10th Annual Hands-on STEM Fair, demonstrating Dr. Zhao's commitment to inspiring future engineers and advancing autonomous vehicle technology through both academic research and practical implementation.

Judith Donathمشاهده پروفایل

پژوهشگر

• Social Media Design
• AI Ethics
• Online Identity
• +۳ مورد دیگر

Judith Donath is a prominent academic and researcher focusing on the intersection of technology, society, and design. She currently serves as a Faculty Fellow at Harvard University's Berkman Klein Center for Internet & Society, where she explores topics like trust, deception, and ethical AI. Previously, she was the founding director of MIT Media Lab's Sociable Media Group, leading projects on online identity, social interfaces, and virtual communities. Her work spans academia, art, and technology, emphasizing how design shapes social behavior. Her research interests include AI ethics, social media design, online identity, and the societal impact of emerging technologies. Notable works include The Social Machine: Designs for Living Online (2014) and her ongoing book project on technology, trust, and deception. She frequently publishes in venues like The Atlantic , CNN , and The Verge , addressing contemporary issues such as generative AI's threat to democracy and child safety in social media. Donath's contributions include innovative projects like Data Portraits and Visual Who , which visualize social interactions and identity. She has advised on digital ethics, participated in global conferences, and collaborated with institutions like Stanford University and the Oxford Internet Institute. Her interdisciplinary approach bridges computer science, sociology, and art to create solutions for evolving digital spaces. Key themes in her work include the ethical implications of AI, the design of trustworthy interfaces, and the societal consequences of digital deception. She advocates for transparency and human-centered design to foster healthier online communities.

Ben Ward-Cherrierمشاهده پروفایل

مدرس ارشد

• Robotics
• Computational Neuroscience
• Prosthetics
• +۲ مورد دیگر

Ben Ward-Cherrier is a Senior Lecturer in Robotics at the University of Bristol's School of Engineering Mathematics and Technology. His research focuses on biomimetic tactile sensing, neuromorphic systems for robotics, and haptic interfaces. He develops artificial tactile systems inspired by biological sensory mechanisms for applications in prosthetics, robotic manipulation, and human-robot interaction. Key research areas include neuromorphic tactile sensors that mimic biological afferents, real-time texture and edge classification algorithms, incipient slip detection for stable grasping, and vibrotactile feedback systems. Recent work integrates spiking neural networks with tactile hardware for efficient sensory processing. Publications demonstrate advancement in tactile sensing capabilities, including braille recognition in noisy environments, psychophysics-inspired benchmarking, multi-modal texture/velocity classification, and industrial applications like composite defect detection. Research bridges computational neuroscience with practical robotic systems.

• Robotics Perception
• Alternative Sensing
• Inertial Fusion
• +۶ مورد دیگر

Teresa Vidal-Calleja is an Associate Professor and Research Director at the Robotics Institute, University of Technology Sydney (UTS). She holds a Deputy Head of School (Research) role in the School of Mechanical and Mechatronic Engineering. Her research focuses on robotics perception, alternative sensing, inertial fusion, SLAM, and applications in manufacturing, agriculture, mining, and construction. Education: B.Sc. Mechanical Engineering (UNAM, 2000), M.Sc. Electrical Engineering (CINVESTAV-IPN, 2002), Ph.D. Automatic Control (Polytechnic University of Catalonia, 2007). Postdoctoral Experience: LAAS-CNRS (France), Australian Centre for Field Robotics (Sydney). Research Interests: Teresa’s work spans robotics perception, sensor fusion, autonomous navigation, and collaborative robotics. She leads projects on next-gen infrastructure robotics (ARC Discovery Grant) and is co-lead of the Australian Cobot Centre. Her innovations target hazardous environments, infrastructure maintenance, and human-robot collaboration. Funded Research: Includes grants for robotic sensors, satellite docking systems, and multi-robot collaboration. Recent projects involve Navantia, the NSW Space Research Network, and industry partnerships. Professional Roles: IEEE Senior Member, Treasurer of the Australian Robotics and Automation Association, and Associate Editor for IEEE Transactions on Robotics and other journals. She chairs conferences like the Australasian Conference on Robotics and Automation. Labs/Teams: UTS Robotics Institute, collaborating with global institutions like ETH Zürich and DLR. Her work integrates robotics with industries such as agriculture and construction, emphasizing sustainability and safety.

Stefan Conradمشاهده پروفایل

پژوهشگر

• Soft Robotics
• 3D Printing Technology
• Pneumatic Systems
• +۵ مورد دیگر

Dr. Stefan Conrad is a Postdoctoral researcher at the DELIVER project of the Carl Zeiss Foundation, focusing on data-driven engineering of sustainable living materials. Previously, he was a Hermann Staudinger Fellow (2019) and a demonstrator at the Cluster of Excellence livMatS (Freiburg Center for Interactive Materials and Bioinspired Technologies). He completed his PhD in 2023 under Prof. Thomas Bacon at the University of Freiburg, with a dissertation on 3D-printed actuators and material-embedded logic for pneumatic soft robotics. Education : PhD in Engineering (2023), University of Freiburg. Research Interests : Stefan’s work spans 3D printing technologies for soft robotics, pneumatic systems, and bioinspired material design. He develops multi-material 3D printers and electronics-free logic devices for autonomous decision-making in soft robots. His recent projects integrate artificial intelligence into lab automation, aiming to streamline repetitive testing procedures. Publications : His research trends highlight advancements in 3D-printed pneumatic logic, lab automation with AI, and rapid prototyping of bioinspired components. Key contributions include tool-changing printers and compliant machines without electronic controllers. Awards : Hermann Staudinger Fellow (2019). Advising & Grants : Supervised by Prof. Thomas Bacon. Funded by DFG (Germany’s Excellence Strategy) and the Carl Zeiss Foundation. His work aligns with the livMatS initiative for sustainable, living materials. Labs/Teams : Part of the livMatS Demonstrator Project and the DELIVER collaborative initiative, advancing soft robotics and sustainable engineering.

Aliyu Abubakarمشاهده پروفایل

مدرس

• Deep Learning
• Image Analysis
• Medical Imaging
• +۵ مورد دیگر

Dr. Aliyu Abubakar is a Lecturer in Computer Science at Teesside University's Department of Computing & Games. He holds a PhD in Computer Science from the University of Bradford (2023), an M.Sc. in Cyber Security (2015), and a B.Sc. in Computer Science from Gombe State University (2012). Prior to his current role, he was a Postdoctoral Research Associate at the University of Liverpool (2022–2024). His research focuses on deep learning applications in medical imaging, cybersecurity, and pattern recognition. He is a member of the Nigeria Computer Society (NCS) and the Cyber Security Experts Association of Nigeria (CSEAN). Education: B.Sc. Computer Science, Gombe State University (2008–2012) M.Sc. Cyber Security, University of Bradford (2014–2015) Ph.D. Computer Science, University of Bradford (2018–2022) Research Interests: Abubakar’s work spans medical image analysis (e.g., burns assessment, kidney transplantation viability, malaria detection), cybersecurity (deepfake detection, P2P network security), and electrical engineering (partial discharge analysis). His deep learning models address challenges in healthcare diagnostics and industrial safety. Recent studies include human deception detection via facial image comparison and automated liver viability assessment using pre-trained neural networks. Key Trends in Publications: His 2020–2024 articles emphasize cross-disciplinary applications of deep learning, particularly in healthcare and electrical systems. Collaborations span institutions like the University of Liverpool and NHS clinical partners, reflecting his commitment to translational research. Awards & Grants: While no specific awards are listed, his high citation counts (e.g., 32 citations for malaria detection work) highlight impactful contributions. Grants and funding details are not disclosed in the provided texts. Labs & Teams: Active collaborations with multidisciplinary teams in medical imaging and cybersecurity, as evidenced by co-authored papers with clinicians and electrical engineers.

Dawn MacIsaacمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Software Engineering
• Knowledge Engineering
• +۱ مورد دیگر

Dr. Dawn MacIsaac is an Associate Professor in the Department of Computer Science at the University of New Brunswick’s Faculty of Computer Science, where she has served for over 14 years. She holds a PhD and Master of Science in Engineering from the same institution. Her research focuses on Biomedical Engineering, Software Engineering, Knowledge Engineering, and Signal Processing, particularly in the context of myoelectric control systems and biomedical signal analysis. Dr. MacIsaac has authored 49 peer-reviewed publications and supervised 25 graduate students. Her work emphasizes improving the performance and robustness of myoelectric prosthetics through advanced machine learning techniques, signal processing algorithms, and adaptive control strategies. Notable contributions include developing the Myosim 2.0 EMG simulation tool and pioneering self-supervised learning approaches for pattern recognition in unclear-label environments. She currently serves on the Editorial Board of the Journal of Electromyography and Kinesiology and is a Professional Engineer (PEng) registered with the Association of Professional Engineers and Geologists of New Brunswick (APEGNB). Her research bridges engineering and healthcare, addressing challenges in signal quality assessment, fatigue monitoring, and human-machine interface design. Key themes in her publications include enhancing EMG signal analysis for medical applications, optimizing control systems for prosthetic devices, and advancing methodologies for automated biosignal evaluation. Her interdisciplinary work impacts rehabilitation technology, clinical diagnostics, and biomedical instrumentation.

Yazhou Tuمشاهده پروفایل

استادیار

• Cyber-Physical System Security
• Side Channel Analysis
• Sensing and Automation Security
• +۳ مورد دیگر

Yazhou Tu is an Assistant Professor in the Department of Computer Science and Software Engineering at Auburn University. He specializes in Cyber-Physical System Security, Side Channel Analysis, and Privacy in embedded systems. His work focuses on addressing vulnerabilities in sensors, actuators, and IoT devices to enhance security and privacy in critical systems. Education: Ph.D. Computer Science, University of Louisiana at Lafayette M.S. Software Engineering, Tsinghua University B.S. Software Engineering, Wuhan University Research Interests: Dr. Tu’s research explores cutting-edge topics such as adversarial control of embedded systems, acoustic and magnetic side-channel attacks, and privacy risks in robotic and biomedical systems. He develops novel defense mechanisms like ADC-Bank and Transduction Shield to counteract physical signal injection attacks. Key Contributions: His work spans sensor security, IoT exploitation, and healthcare technology, with notable studies on 3D printer IP theft, vehicle control via smart glasses, and keystroke tracking via audio. He also investigates physics-informed ML for porous media and glucose monitoring systems. Awards & Grants: No specific awards or grants listed in the provided data, but his prolific publication record highlights sustained research excellence. Labs & Collaborations: Engaged in Auburn’s Center for Artificial Intelligence and Cybersecurity Engineering and other interdisciplinary initiatives focused on secure embedded systems and cyber-physical infrastructure.

Bin Huمشاهده پروفایل

استادیار

• Resilient Cyber-Physical Systems (CPS)
• AI-Human Collaboration Safety & Security
• Big Data & Machine Learning-Based Control
• +۵ مورد دیگر

Dr. Bin Hu is an Assistant Professor in the Department of Engineering Technology at the University of Houston (2022–present) and previously held the same position at Old Dominion University (2019–2022). He earned a Ph.D. in Electrical Engineering from the University of Notre Dame (2016), an M.S. in Control Science from Zhejiang University (2010), and a B.S. in Electrical Engineering from Hefei University of Technology (2007). His research focuses on resilient Cyber-Physical Systems (CPS), AI-human collaboration safety, machine learning-driven control, and vehicular networks. Key projects include NASA-funded work on adaptive human-autonomy responsibility allocation (2023–2026) and NSF-supported AI-human collaboration in autonomous vehicles (2020–2023). He has secured over $1.2 million in grants, including a $700k NASA grant (pending) and an ONR Rapid Solutions grant ($42k). Dr. Hu’s work bridges control theory, machine learning, and human factors. Recent contributions include safer leader-follower robotic systems, fault-tolerant UAV control, and studies on driver trust in AI-driven vehicles. His research has been recognized through awards like the 2024–2025 APeX Excellence Speaker Series. Teaching experience includes courses on C++ programming and electrical engineering fundamentals at both the University of Houston and Old Dominion University. He advises multiple undergraduate and graduate students in projects ranging from LiDAR systems to cyber-physical security. Key Labs/Teams : NAIL Lab (Networked Autonomous Intelligence & Learning), part of the University of Houston’s Cybersecurity and Robotics initiatives. Grants : NASA TTT Grant ($700k), NSF CHS Grant ($500k), ONR RSLP Project ($42k).

Vinicius Prado da Fonsecaمشاهده پروفایل

استادیار

• Robotics
• Tactile Sensing
• Robotic Manipulation
• +۴ مورد دیگر

Vinicius Prado da Fonseca is an Assistant Professor in the Department of Computer Science at Memorial University of Newfoundland. His research focuses on advanced robotics, tactile sensing technologies, and human-robot interaction. His work integrates machine learning and artificial intelligence to improve robotic manipulation, prosthetic control, and haptic interfaces. Education background includes: Ph.D. in Electrical and Computer Engineering from University of Ottawa (2020) M.Sc. in Systems and Computing from Military Institute of Engineering, Brazil (2013) B.Sc. in Computer Science from Federal University of Tocantins, Brazil (2010) Research interests emphasize tactile perception systems, compliant robotic grippers, and bio-inspired sensor modules. Notable contributions include the BioIn-Tacto tactile sensing framework and studies on myoelectric control for upper-limb prosthetics. His work bridges theoretical machine learning with practical robotics applications in manufacturing, healthcare, and assistive technologies. Publications span over 30 peer-reviewed articles focusing on tactile datasets, sensor design, and robotic control algorithms. Recent trends show increasing emphasis on multimodal data fusion, active learning for sensor optimization, and human-centric robotics applications. Currently no listed scientific awards or grants, but maintains active collaborations in prosthetic development and industrial automation projects.

Jana-Rebecca Rehseمشاهده پروفایل

استادیار

• Business Process Management
• Process Mining
• User Behavior Mining
• +۵ مورد دیگر

Prof. Dr. Jana-Rebecca Rehse serves as Assistant Professor for Management Analytics at the University of Mannheim Business School, where she leads the Chair of Management Analytics within the Information Systems department. Her academic work bridges theoretical research with practical business applications, focusing on data-driven approaches to business process optimization. Her primary research interests encompass User Behavior Mining , Process Mining , and AI applications in business process management . Rehse investigates how organizations can leverage process mining techniques to extract meaningful insights from event logs, with particular attention to conformance checking, process resilience assessment, and the practical implementation challenges businesses face when adopting these technologies. Her work frequently addresses the intersection of human behavior and process execution, examining how user interactions with IT systems can be analyzed to improve process design and user experience. Analysis of her recent publications reveals a clear research trajectory toward increasingly sophisticated integration of artificial intelligence with traditional process mining techniques. Starting with foundational work on reference model mining and process discovery methodology, her research has evolved to address cutting-edge applications of generative AI, explainable AI, and predictive analytics in business process contexts. The majority of her work appears in top-tier information systems and business process management journals including Information Systems, Process Science, and ACM Transactions publications, demonstrating her significant contributions to the field. Professor Rehse actively collaborates with industry partners including Siemens and MEHRWERK, offering thesis opportunities and research projects that address real-world business challenges. Her current call for applications includes work-study programs at Siemens and master thesis topics focused on conformance checking in cooperation with MEHRWERK. She has recently introduced innovative thesis topics exploring the use of Generative AI for Emotion Identification, reflecting her forward-looking research agenda that anticipates emerging technological trends and their business implications.

Mohammad Karimمشاهده پروفایل

استاد

• Optical Computing
• Information Processing
• Pattern/Target Recognition
• +۵ مورد دیگر

Mohammad Karim, PhD, is a Professor in the Department of Electrical & Computer Engineering at the University of Massachusetts Dartmouth (UMass Dartmouth), affiliated with the College of Engineering. He previously held leadership roles including Provost, Executive Vice Chancellor for Academic Affairs, and Chief Operating Officer at UMass Dartmouth. His career includes serving as Vice President of Research at Old Dominion University (2004–2013), Dean of Engineering at City College of New York (2000–2004), and Head of Electrical and Computer Engineering at the University of Tennessee (1998–2000). He is an elected fellow of multiple prestigious organizations, including IEEE, OSA, and SPIE. Dr. Karim holds a BS Honors in Physics from the University of Dhaka (1976) and MS in Physics (1978) and MS/PhD in Electrical Engineering (1979/1981) from the University of Alabama. His research focuses on optical computing, pattern recognition, electro-optical systems, and sensors, with funding from agencies like the Office of Naval Research and NASA. He has authored 19 books, over 365 papers, and 13 book chapters, and served as guest editor for 36 journal special issues. His awards include Fellowships from IEEE, OSA, and the Bangladesh Academy of Sciences. He mentors students in MS/PhD programs and advises on research proposals. His work spans academic leadership, technical innovation, and interdisciplinary collaboration in engineering and optics.