جست‌وجوی استاد و پژوهشگر

Tobias Delbrückمشاهده پروفایل

استاد مدعو

• Neuromorphic Engineering
• Bio-Inspired Sensory Processing
• Silicon Retina Sensors
• +۳ مورد دیگر

Prof. em. Dr. Tobias Delbrück is a retired Adjunct Professor at the Department of Information Technology and Electrical Engineering, ETH Zürich. He holds a BSc in Physics and Applied Mathematics from UC San Diego (1983) and a PhD in Computation and Neural Systems from Caltech (1993). His research focuses on neuromorphic engineering, bio-inspired sensory systems, and event-based silicon sensors for vision and auditory applications. He has been affiliated with the Institute of Neuroinformatics (INI), a joint institute of ETH Zurich and the University of Zurich, since 2009. Notable achievements include being named an IEEE Fellow (2014) and receiving the Jan van Vesem Outstanding European Paper Award (2006). He holds 7 patents and co-founded inilabs GmbH. Prior to joining INI, he consulted for Silicon Valley firms including Synaptics and Foveon. His work emphasizes interdisciplinary applications of neuromorphic systems, with contributions to silicon retina design and event-driven sensor algorithms.

Patricia A. Vargasمشاهده پروفایل

دانشیار

• Robotics
• Evolutionary Robotics
• Swarm Robotics
• +۷ مورد دیگر

Patricia A. Vargas is an Associate Professor/Reader in Computer Science and Robotics at the School of Mathematical & Computer Sciences, Heriot-Watt University, UK. She is the Founder Director of the Robotics Laboratory and Director of Ethics. Her research focuses on interdisciplinary robotics, including Evolutionary Robotics, Swarm Robotics, Biologically-Inspired Algorithms, Computational Neuroscience, and Neurorobotics. She holds IEEE Senior Member and Fellow of the Higher Education Academy titles. Education: PhD in Robotics, postdoc at the Centre for Computational Neuroscience and Robotics (University of Sussex, UK). She has contributed to over 66 research outputs since 2009, with recent work emphasizing neurorobotics, SLAM systems, and precision robotics. Her research aligns with UN Sustainable Development Goals, particularly in healthcare and industrial innovation. Research interests span from bio-inspired algorithms to human-robot interaction, with notable contributions in Parkinson’s disease modeling and swarm robotics. She co-founded the Edinburgh Centre for Robotics and is an executive member of the IEEE Ro-Man Standing Steering Committee. Awards include the 2017 Spirit of Heriot-Watt Award (Outward Looking). Her work bridges robotics with neuroscience, aiming to advance assistive technologies and ethical robotic systems.

Leonardo Giannantoniمشاهده پروفایل

پژوهشگر

• Computer architectures
• Computer aided design
• Computer graphics
• +۱۰ مورد دیگر

Leonardo Giannantoni is a PhD Student in Control and Computer Engineering at the Polytechnic University of Turin (2021-2024) and a current Research Engineer at the same institution. His work focuses on bio-inspired and AI-driven algorithms for modeling, simulating, and optimizing complex systems, with applications in synthetic biology , structural biology , and healthcare technology . Education PhD in Control and Computer Engineering (2024, Polytechnic University of Turin) MSc in Computer Engineering (2016, Polytechnic University of Turin) BSc in Computer Engineering (2014, Polytechnic University of Turin) Giannantoni's research spans multiple domains, including reinforcement learning for genetic networks , co-simulation in biofabrication , and virtual reality rehabilitation systems for Parkinson's disease. His work integrates machine learning with biological modeling , leveraging parallel computing and software engineering principles. Recent publications highlight his expertise in AI-driven structural biology , synthetic oscillatory networks , and privacy tools like tracker blockers. His Biology System Description Language (BiSDL) provides a framework for multicellular synthetic biological systems design. Scientific Contributions Member of the Focus Group of Researchers (2023-) Giannantoni has served as a Teaching Assistant for courses on Systems Programming and Algorithms , and contributed to open-source projects like nwn-petrisim (Petri Nets simulator) and microgp4 (evolutionary computing toolkit). His work bridges academic research and practical software development for complex systems.

Qinghua Zhouمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۱۱ مورد دیگر

Qinghua Zhou is a Researcher in the Department of Mathematics at King's College London , within the Faculty of Natural, Mathematical & Engineering Sciences . His work focuses on robust, stable, and trustworthy AI systems through theoretical and computational analysis of computer vision and large language models. Education: BSc in Applied Mathematics and Physics from the University of Sydney PhD in AI from the University of Leicester Research interests include: Adversarial and stealth attacks on AI models Model watermarking and locking without retraining High-dimensional low-sample-size data analysis Neuromorphic and reservoir computing Weight manipulation with theoretical guarantees His recent publications highlight trends in: 2024–2025 : AI safety via deterministic weight edits, vulnerabilities of LLMs, and theoretical frameworks for adversarial robustness. 2023 : Ensemble methods for medical data, intrinsic dimensionality, and neuromorphic feature space optimization. Collaborations include researchers such as Dr. Oliver Sutton and Prof. Ivan Tyukin. Projects involve developing high-performance software and interactive demos for AI verification.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۶ مورد دیگر

Shwai He is a PhD student and Affiliate Assistant Professor at the University of Maryland, advised by Ang Li. Their research focuses on advancing AI systems through innovative approaches in large language models (LLMs), fairness in machine learning, and efficient neural network architectures. Key areas include multi-agent systems, causal modeling for bias mitigation, and optimization techniques for mixture-of-experts models. Research interests span artificial intelligence, machine learning, and natural language processing with emphasis on practical applications like healthcare diagnostics and social pairing systems. Notable work includes developing GNWT-based multi-agent digital twins for social platforms and improving LLM transparency through token analysis. Publications highlight contributions to counterfactual fairness, dynamic-depth transformers, and parameter-efficient methods. Current efforts explore computational efficiency in vision-language models and bio-inspired antibody prediction systems. No scientific awards have been mentioned. Advising and grants: Currently a PhD student under Ang Li's supervision. Research involves collaborations across computer science and bioinformatics domains.

• Complex Adaptive Systems
• Collective Behavior
• Organismal Biology
• +۹ مورد دیگر

Ted Pavlic is an Associate Professor at Arizona State University (ASU), jointly appointed in the School of Computing and Augmented Intelligence and the School of Life Sciences. His interdisciplinary research bridges engineering and biology, focusing on adaptive decision-making in natural and artificial systems. He leads the BEET lab, which studies collective behavior in social insects and designs bio-inspired algorithms for robotics and AI. Education: Ph.D. in Electrical and Computer Engineering (The Ohio State University, 2010), postdoctoral training in life sciences and computer science (ASU and OSU). Former industry roles include software engineering and analog electronics. Research interests include complex adaptive systems, social insect behavior, optimal foraging theory, AI, and biomimicry. He has mentored over 20 students and postdocs, leading to impactful work in swarm robotics, collective intelligence, and sustainability. Key awards: SWARM 2021 Best Paper Award, invited TEDx speaker. Active in professional organizations like the Animal Behavior Society and the Entomological Society of America. Grants include NSF-funded projects on sleep-dependent learning in AI and biomimetic control systems. Collaborates across ASU’s complexity initiatives, including the Biomimicry Center and the Center for Social Dynamics and Complexity. Lab affiliations: BEET Lab, ASU-SFI Center for Biosocial Complex Systems. Engages in public outreach through YouTube, Twitter, and Mastodon.

Tobias Fischerمشاهده پروفایل

مدرس ارشد

• Robotics
• Computer Vision
• Computational Cognition
• +۴ مورد دیگر

Dr. Tobias Fischer is a Senior Lecturer at Queensland University of Technology (QUT) in the School of Electrical Engineering & Robotics, Faculty of Engineering. He is an ARC DECRA Fellow and leads research in robotics, computer vision, and computational cognition. His work focuses on enabling robots to interact with humans through perception systems inspired by animal visual systems. He holds a PhD from Imperial College London and has held postdoctoral roles at Imperial College's Personal Robotics Lab. Education: PhD (Imperial College London, 2019), MSc (University of Edinburgh, 2014), BSc (Ilmenau University of Technology, Germany, 2013). Scholarships include the German National Academic Foundation and DECRA Fellowship. Research interests span bio-inspired neural networks, event-based vision, spiking neural networks, and neuromorphic computing. He has led projects funded by Intel, Amazon, Samsung, EU, and Australian Research Council, including $462,000 DECRA grant for adaptive robot positioning. Key awards include the 2023 IEEE Outstanding Paper Award and Queen Mary UK Best PhD in Robotics. Teaching includes units like EGB339 Introduction to Robotics and EGB439 Advanced Robotics. Supervision involves PhD students in place recognition and underwater imagery. His lab, QUT Centre for Robotics, focuses on long-term localization and bio-inspired autonomy.

Adam Hinesمشاهده پروفایل

پژوهشگر ارشد

• Neuroscience
• Robotics
• Artificial Intelligence
• +۳ مورد دیگر

Dr Adam Hines is a Research Fellow at the QUT Centre for Robotics, affiliated with Queensland University of Technology. He holds a PhD in neuroscience from the Queensland Brain Institute (2023), focusing on synaptic physiology and the effects of general anaesthesia on neuronal communication. His current research bio-inspires visual place recognition methodologies for robotic navigation, leveraging neuroscience principles. Dr Hines collaborates with Dr. Tobias Fischer’s group to bridge biological insights with robotic systems. His work emphasizes interdisciplinary approaches combining neuroscientific understanding with engineering challenges in autonomous navigation. No recent articles or grants are explicitly listed in the provided information.

Therese Josephمشاهده پروفایل

پژوهشگر

• Robotics
• Neuromorphic Engineering
• Biological Navigation Systems
• +۵ مورد دیگر

Therese Joseph is a Researcher at the Queensland University of Technology (QUT) Centre for Robotics. Her research focuses on advancing robotics navigation by integrating biological inspiration from natural positioning systems to reduce reliance on GPS and enhance sovereign capabilities in localization and mapping. She is involved in the 'Re-Evolving Nature’s Best Positioning Systems for People and Their Machines' project, exploring neuromorphic computing and bio-inspired algorithms for autonomous systems. Her work emphasizes cross-disciplinary approaches, combining robotics engineering with materials science (e.g., granular jamming grippers) and neuroscience-inspired trajectory tracking. She contributes to open-source datasets and hardware innovations in soft robotics, such as the 'jamming donut' gripper design. Therese collaborates within QUT’s Centre for Robotics, a hub for advanced robotics research and industry partnerships. Though no awards are directly attributed to her in the provided text, her projects align with grants and recognitions won by her colleagues, indicating a dynamic research environment.

Stephen Hauslerمشاهده پروفایل

پژوهشگر ارشد

• Robotics
• Neuroscience
• Autonomous Systems
• +۳ مورد دیگر

Dr. Stephen Hausler is a Research Fellow at the QUT Centre for Robotics, focusing on bio-inspired algorithms for autonomous navigation. He holds a PhD from QUT (completed in 2021) and a Bachelor of Engineering (Electrical Engineering) with First Class Honours (2013). His research integrates neuroscience principles to develop robust navigation systems for robots in challenging environments. Education: Bachelor of Engineering (Electrical Engineering), QUT, 2013 (First Class Honours) PhD in Robotics, QUT, 2021 Research Interests: Stephen’s work bridges robotics and neuroscience, emphasizing bio-inspired solutions for autonomous systems. Key areas include multi-process fusion, visual place recognition, and neuro-inspired algorithms to enhance robotic navigation reliability. Key Projects: ARC Future Fellowship: Superhuman Place Recognition HD Maps for Automated Driving AUSMURI: Neuro-Autonomy (Neuroscience-Inspired Perception for Autonomous Robots) NVIDIA Applied Research Accelerator Program Collaborations: He contributed to a collaborative project with QUT, iMOVE Australia, RACQ, and TMR, focusing on industry-relevant autonomous systems. His work aligns with NVIDIA’s applied research initiatives. Awards: Grand Finalist, 2020 QUT Three Minute Thesis Competition

• Robotics
• Computer Vision
• Sensor Fusion
• +۳ مورد دیگر

Adam Jacobson is a former Research Fellow at the Queensland University of Technology (QUT) Centre for Robotics, now working at Caterpillar as an Automation Engineering Specialist. He holds a PhD (QUT) and Bachelor of Engineering (Electrical) from QUT. Research Focus: Bio-inspired algorithms for robotic SLAM, sensor fusion, and underground mining automation. Key Projects: 'Infinitely Scalable Learning and Recognition Network' (funded by Asian Office of Aerospace Research and Development) and 'Automation Enabling Positioning for Underground Mining' (collaboration with Caterpillar and Mining3). His work emphasizes scalable visual place recognition, low-cost sensor integration, and overcoming challenges in dynamic environments like underground mines. Awards include an ARC Future Fellowship for 'Superhuman place recognition' research. Awards: ARC Future Fellowship, 201X (specific year unlisted). Collaborations: Harvard University, University of Notre Dame, Caterpillar, and Mining3. His research has advanced autonomous vehicle navigation, particularly in harsh environments, through innovations in multi-scale visual recognition and sensor calibration.

Shuodao Wangمشاهده پروفایل

دانشیار

• Dynamic mechanical behaviors of soft biological tissues
• 3D stereoimaging for full-field displacement measurements
• Mechanical behaviors of soft and thin web materials
• +۵ مورد دیگر

Shuodao Wang is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Oklahoma State University. His research focuses on dynamic mechanical behaviors of soft biological tissues, 3D stereoimaging for displacement measurements, and mechanics of nanomeshed materials. He holds a Ph.D. from Northwestern University (2012) and a B.S. from Tsinghua University (2007). Key research areas include: Biomechanics of soft tissues and hydrogel materials Transparent/stretchable electronic device design Inverse finite element modeling for material characterization Adaptive optoelectronic systems inspired by nature Notable awards include the NSF CAREER Award (2019) and ASME Haythornthwaite Research Grant (2015). He teaches advanced courses in elasticity, composite mechanics, and structural stability. Recent work explores electrochemically triggered transient electronics and neural probe mechanics. Publications span over 20 peer-reviewed articles from 2008-2024, with emphasis on nano/microscale mechanics and biomedical applications. His group develops novel materials for soft robotics, wearable sensors, and medical devices through interdisciplinary approaches combining experimental mechanics, computational modeling, and machine learning.

Martin-Pierre Schmidtمشاهده پروفایل

مدرس

• Topological Optimization
• Multi-physics Optimization
• Approximation Theory
• +۳ مورد دیگر

Martin-Pierre Schmidt is a Lecturer at the National Institute of Applied Sciences (INSA) Rouen, affiliated with the Department of Mathematical Engineering. His research focuses on topological/multi-physics optimization, approximation theory, and applications in computer-aided geometric design (CAGD). He completed his PhD in March 2020 under the supervision of Christian Gout, with co-supervisors David Bonner and Auxkin Ortuzar from Dassault Systèmes, funded by Dassault Systèmes. His work integrates machine learning and data science into imaging and design processes. He teaches in the GM5 program at INSA Rouen, emphasizing machine learning and data approximation techniques. His research team is part of the Numerical Analysis, Imaging and Approximation group. Notable contributions include interactive topology optimization tools, biomimetic microstructure design, and robust 3D shape detection algorithms. His thesis defense in 2020 involved a jury of international experts in mechanical engineering and computational design. Key collaborations include Dassault Systèmes, with applications in CAD model optimization and manufacturing process design. His work bridges theoretical optimization methods with practical industrial applications in additive manufacturing and structural engineering.

• Control Engineering
• Robotics
• Mechatronics
• +۳ مورد دیگر

Stephen Mascaro is an Associate Professor (Lecturer) in the Department of Mechanical Engineering at the University of Utah, where he has served since 2005. He currently holds the role of Director of Robotics Studies, effective January 2024. His academic journey includes degrees from Clarkson University (BS in Mechanical Engineering and BA in Physics, 1995), and advanced degrees from MIT (MS 1997, PhD 2002 in Mechanical Engineering). His research focuses on control engineering, mechatronics, robotics, and sensor systems. Notable contributions include fingernail imaging for tactile force sensing, robotic tendon modeling, and biomimetic actuators. He has secured grants such as the NRI-Small grant for grasp force research. His work bridges robotics, biomedical engineering, and haptics, with applications in surgical robotics, human-robot interaction, and sensor development. Mascaro teaches courses in Mechatronics and System Dynamics, emphasizing hands-on learning. He actively mentors FIRST Robotics teams and engages in community outreach, including mentoring high school robotics competitions. His awards include the 2024 Top 15% Instructor Award from the University of Utah. His lab develops innovative sensors and robotic systems, integrating principles from biomechanics and materials science. Current projects include real-time tactile sensing via deep learning and robotic tendon repair simulation. His work is published in IEEE Transactions, Journal of Dynamic Systems, and other leading journals, with over 40 peer-reviewed articles since 1998.

Zahra Bagheriمشاهده پروفایل

پژوهشگر ارشد

• Bio-inspired Robotics
• Neuroengineering
• Computer Vision
• +۳ مورد دیگر

Zahra Bagheri is an Adjunct Research Fellow at the School of Biological Sciences, The University of Western Australia. She holds a PhD in interdisciplinary bio-inspired robotics and completed postdoctoral studies at UWA's neuroecology laboratory under A/Prof. Jan Hemmi. Her research focuses on integrating engineering solutions with biological systems, particularly in bio-inspired robotics, neuroengineering, and visual function analysis. Education: BSc and MSc in Engineering, followed by a PhD in interdisciplinary robotics and a postdoctoral specialization in neuroecology. She combines behavioral studies, neural data, and computational modeling to explore how small-brained animals solve environmental challenges. Key collaborations include work with the UWA Oceans Institute and international researchers. Research interests span bio-inspired robotics, computational modeling of animal vision, and neuroecological adaptations. Her work bridges engineering and biology to develop practical solutions for autonomous systems and sensory systems. Recent studies include deep-sea amphipod vision, fiddler crab sensory processing, and virtual reality systems for ecological experiments. Grants include a Konishi Neuroethology Research Award (2020–2022) for studying decision-making in animals, and a project on deep-sea vision (2022–2023). Media coverage highlights applications of dragonfly vision for driverless cars and bionic eye technology. Labs/Teams: Affiliated with the neuroecology laboratory at UWA and collaborates with interdisciplinary teams in marine biology and robotics.