جست‌وجوی استاد و پژوهشگر

Mauro Manassiمشاهده پروفایل

مدرس

• Visual Neuroscience
• Perception
• Visual Organization
• +۵ مورد دیگر

Dr. Mauro Manassi is a Lecturer in Psychology at the University of Aberdeen's School of Psychology, where he has been appointed since August 2019. He leads the Manassi Laboratory, which focuses on visual perception research, and co-hosted the 46th European Conference on Visual Perception in Aberdeen in August 2024. His educational background includes a PhD in Neuroscience from École Polytechnique Fédérale de Lausanne (2014), an MSc in Clinical Psychology from the University of Padua (2009), and a BSc in Psychology of Personality and Interpersonal Relationships from the University of Padua (2006). Prior to his academic career, he completed an 18-month postdoc at UC Berkeley under Prof. David Whitney's laboratory, funded by the Swiss National Science Foundation. Manassi's research centers on how the visual system organizes cluttered environments into coherent perceptions and stabilizes our visual interpretations of the world. His laboratory investigates two key principles: Organization (studying visual crowding and ensemble perception) and Stabilization (examining serial dependence in visual perception). His work has significant implications for understanding visual perception in complex environments, including applications in medical image perception for radiology and dermatology. His publication record shows a strong focus on serial dependence mechanisms, visual crowding phenomena, and medical image perception. The research demonstrates how our brains create stable visual experiences despite discontinuous retinal input, with findings showing that our perception integrates visual information over approximately 15 seconds. His recent work extends these principles to clinical contexts, revealing how perceptual biases affect medical diagnosis. His scientific recognition includes the British Psychology Society Cognitive Psychology Section Award for Best Research Article of the Year (2022) and awards for hosting the European Conference on Visual Perception in 2024. Manassi actively supervises PhD students and research assistants while serving in multiple administrative roles at Aberdeen, including Head of S.C.R.E.A.M. committee, Data Protection Champion, and member of the Ethics Committee. His research has attracted substantial media attention, with over 259,000 views on his YouTube visual illusion and viral coverage of his work on The Conversation.

Li Liمشاهده پروفایل

استاد

• Visual perception
• Visuomotor control
• Eye-hand coordination
• +۴ مورد دیگر

Li Li is a Professor of Neural Science and Psychology at NYU Shanghai and a Global Network Professor at NYU. Her research focuses on visual perception, visuomotor control, eye-hand coordination, and virtual reality applications. Dr. Li earned her educational degrees from prestigious institutions: 1999 Ph.D. in Cognitive Science from Brown University 1995 M.A. in Cognitive Psychology from Stony Brook University 1992 B.S. in Psychology from Peking University Dr. Li's research program investigates fundamental processes of visual perception and motor control. Her lab employs interdisciplinary approaches that integrate psychophysics, neuroscience, computer science, and engineering to examine how humans perceive visual information, control self-motion, and integrate perception with motor actions. A significant portion of her work explores how visual information guides navigation and goal-directed movements, with applications to understanding visuomotor control in both healthy individuals and those with neuromotor disorders. Her research demonstrates consistent innovation in experimental paradigms for studying heading perception, optic flow processing, and the integration of motion and form cues for self-motion perception. Dr. Li's publication record shows a clear trajectory of research advancing our understanding of visual-motor integration across multiple contexts including natural navigation, virtual environments, and sports performance. Her work bridges basic science with practical applications in rehabilitation, human-computer interaction, and virtual reality technologies. Dr. Li actively collaborates with researchers across multiple disciplines as evidenced by her co-authorship patterns. Her laboratory at NYU Shanghai provides a dynamic environment for investigating the neural and cognitive mechanisms underlying visual perception and motor control, with recent work extending into 2025.

Mohit Lawمشاهده پروفایل

دانشیار

• Machining dynamics
• Machine tool design and analysis
• Dynamic substructuring
• +۶ مورد دیگر

Mohit Law is an Associate Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Kanpur. His research focuses on machining dynamics, machine tool design and analysis, vibration control, and manufacturing systems. With expertise spanning both theoretical modeling and practical applications, Dr. Law has established himself as a notable researcher in precision manufacturing technologies. PhD (2013), University of British Columbia, Canada. Thesis: "Position-dependent dynamics and stability of machine tools." MSc, Michigan Technological University, USA BE, Pune University, India Dr. Law's research spans multiple areas in manufacturing and mechanical engineering, with a strong focus on machining dynamics and machine tool performance. His work addresses critical challenges in precision manufacturing, vibration control, and advanced machining strategies. He has made significant contributions to understanding position-dependent dynamics in machine tools and developing innovative solutions for vibration damping and isolation. His research integrates analytical methods with experimental validation to improve machine tool performance and manufacturing efficiency. Dr. Law's publication record demonstrates a consistent focus on machine tool dynamics, particularly position-dependent behavior. His work bridges theoretical modeling with practical applications in manufacturing, with emphasis on substructuring techniques, vibration isolation, and stability analysis. He has developed novel approaches that have advanced the field of precision manufacturing, particularly in high-performance machining strategies. International Partial Tuition Scholarship, The University of British Columbia, 2009-2013 Graduate Scholar, Sustainable Futures Institute, Michigan Technological University, 2007-2008 Dr. Law has extensive industry experience as a Machine Tool Design Engineer at TAL Manufacturing Solutions (TATA) and Bharat Fritz Werner Ltd. He also served as a Research Associate at the Fraunhofer Institute for Machine Tools and Forming Technology in Germany. He maintains active professional affiliations as a CIRP Research Affiliate and SME Member. His research has practical applications in industrial manufacturing settings, particularly in improving machine tool performance and reliability. Dr. Law is associated with the Manufacturing Science and Solid Mechanics and Design research groups at IIT Kanpur. His work involves developing advanced modeling techniques and experimental methods to improve machine tool dynamics and manufacturing processes. He collaborates with international research institutions and maintains strong industry connections to ensure his research addresses real-world manufacturing challenges.

• Theoretical Kinematics
• Screw Theory
• Lie Algebra
• +۷ مورد دیگر

DAI Jiansheng is a Chair Professor at Southern University of Science and Technology (SUSTech) and Director of the Robotics Research Institute. He is a Fellow of the Royal Academy of Engineering (FREng), Fellow of the Academia Europaea, and holds multiple fellowships including IEEE, ASME, RSA, and IMechE. As Editor-in-Chief of the international journal Robotica, he has established himself as a leading authority in mechanisms and robotics research. His educational background includes a PhD from the University of Salford (1989-1993), a Master's degree from Shanghai Jiao Tong University (1982-1984), and a Bachelor's degree from the same institution (1978-1982). His academic journey has taken him from postdoctoral work at Salford University to research positions at Unilever Liverpool Research Centre before becoming a faculty member at the University of Sunderland and ultimately King's College London, where he served as Reader and then Chair Professor from 2007 until his current position at SUSTech. Professor Dai's research spans theoretical kinematics, screw theory, Lie algebra, and their applications to metamorphic and reconfigurable mechanisms. His pioneering work bridges the gap between versatile but expensive robots and efficient but non-flexible machines. His research interests include origami-inspired robotics, rehabilitation robotics for ankle treatment, soft robotics, and industrial applications in packaging and manufacturing. His theoretical framework has enabled significant advances in reconfigurable parallel mechanisms and metamorphic robotics. His extensive publication record shows a clear progression from fundamental theoretical work on screw algebra and Lie groups to practical applications in rehabilitation, manufacturing, and soft robotics. Recent publications demonstrate increasing focus on soft robotics, variable stiffness actuators, and continuum robots with Shape Memory Alloy applications, while maintaining strong theoretical foundations in screw theory and kinematic analysis of metamorphic mechanisms. ASME Mechanisms and Robotics Award (2015) ASME Machine Design Award (2020) IFToMM Excellence Award (2023) Tianjin Municipal Natural Science First Prize (2021) Crossley Award (2018) AT Yang Award in Theoretical Kinematics (2019) Professor Dai has supervised over 50 PhD students who now hold faculty positions at world-leading universities including University College London, Queen Mary University London, Purdue University, and Wollongong University. His research has been supported by numerous grants enabling the establishment of advanced robotics laboratories and international collaborations. He founded the IEEE Triennial International Conference on Reconfigurable Mechanisms and Robots (ReMAR), creating a major platform for international scholarly exchange in this specialized field. His research group maintains strong industry partnerships with companies including Cambridge Consultants, Goldman Sachs, and Amazon. The Robotics Research Institute he directs at SUSTech serves as a hub for interdisciplinary research, bringing together experts in mechanical engineering, computer science, biomedical engineering, and materials science. The institute focuses on both fundamental theoretical advances in mechanism design and practical applications in healthcare, manufacturing, and service robotics, with particular emphasis on metamorphic and reconfigurable systems that can adapt to multiple tasks.

Alexander Goettkerمشاهده پروفایل

پژوهشگر

• Oculomotor Control
• Eye Movement Research
• Perceptual Judgment
• +۷ مورد دیگر

Alexander Goettker is a postdoctoral researcher at Justus Liebig University Giessen, focusing on oculomotor control, perceptual judgment, and sensorimotor integration. His work bridges basic research on eye movements with applied studies in VR/AR display optimization. Current role: Postdoctoral Researcher at Justus Liebig University Giessen Key collaborations: Professor Karl Gegenfurtner's lab Research interests include predictive eye movements in naturalistic scenes, serial dependence effects in motor tasks, and the influence of contextual cues on oculomotor behavior. He explores how retinal signals and internal models interact to enable stable perception during eye movements. Recent trends in publications emphasize individual differences in sensorimotor processing, the role of naturalistic stimuli in vision science, and the trade-offs between perceptual and oculomotor artifacts in head-mounted displays. His work also investigates eye-hand coordination and the impact of display duty cycles on visual tracking accuracy. Labs and teams include collaborations with Professor Karl Gegenfurtner's lab, leveraging interdisciplinary approaches to study eye movements in ecological contexts and their implications for VR/AR technology.

Ioannis Kyriakouمشاهده پروفایل

استاد

• Actuarial Science
• Quantitative Finance
• Financial Mathematics
• +۱۳ مورد دیگر

Professor Ioannis Kyriakou is a leading academic in actuarial finance and quantitative methods at Bayes Business School, City St George's, University of London, where he serves as Professor of Actuarial Finance and Director of the MSc in Actuarial Science and MSc in Actuarial Management. He holds a visiting professorship at the University of Eastern Piedmont and has previously served as affiliate faculty at the Cyprus International Institute of Management. His research spans actuarial science, derivatives pricing, risk management, computational finance, and machine learning applications in finance and insurance. His research interests focus on quantitative finance , stochastic modeling , numerical methods , and machine learning , particularly in the context of derivative pricing , pension product design , energy and commodity markets , and investor sentiment . He has developed advanced computational techniques such as moment-based approximations and transform methods for financial modeling. His work integrates simulation, optimization, and data-driven approaches to solve complex financial and actuarial problems. The recent publications reflect a strong trend toward interdisciplinary research, combining machine learning with financial economics , energy efficiency forecasting , mutual fund performance , and climate risk . His work frequently appears in top journals like Operations Research , Journal of Financial and Quantitative Analysis , and European Journal of Operational Research , showcasing expertise in both theoretical and applied finance. European Journal of Operational Research (2020) Editors' Award for Excellence in Reviewing Cass Business School (2014) Prize for Excellence in Teaching and Learning Dimitris N. Chorafas Foundation (2009) Prize for outstanding PhD research work EPSRC Doctoral Training Award (2008) He supervises several PhD students in areas such as derivatives pricing, machine learning in actuarial science, and pension optimization. He has received research support through editorial leadership, consultancy (e.g., with Lloyd’s Treasury), and academic collaboration. He is actively involved in organizing conferences and workshops, including the Finance and Business Analytics Conference. He is affiliated with research groups focusing on financial modeling , actuarial computation , and machine learning in insurance , contributing to both academic and industry-facing initiatives. His co-authored book Machine Learning in Insurance (MDPI, 2020) highlights his leadership in bridging data science with actuarial applications.

• Cognitive Neuroscience
• Psychology of Language
• Neuroimaging
• +۴ مورد دیگر

Dr. Xiaolin Zhou serves as the Director of the Center for Brain and Cognitive Sciences and Chair of the Department of Psychology at Peking University in Beijing, China, holding dual leadership roles that underscore his prominence in cognitive neuroscience and academic administration. His educational trajectory includes: Bachelor's degree from East China Normal University Ph.D. in Psychology of Language from the University of Cambridge (awarded 1992) Zhou's research spans cognitive neuroscience with emphases on language processing, emotion regulation, attentional mechanisms, and social cognition. His methodological approach integrates neuroimaging (fMRI, ERP) and behavioral paradigms to investigate neural substrates of cognition, particularly examining clinical populations with chronic pain, Parkinson's disease, and aggression disorders. His work bridges theoretical cognitive models with clinical applications. Analysis of recent publications reveals a cohesive interdisciplinary framework where language processing intersects with social decision-making and clinical neuroscience. His team consistently employs multimodal neuroimaging to dissect how reward systems modulate emotional responses and how cortical networks adapt in pathological conditions, establishing China as a significant contributor to global cognitive neuroscience. Editorial leadership includes Specialty Chief Editor for Psychology of Language at Frontiers in Psychology and Associate Editor for Cognitive Neuroscience at Frontiers in Human Neuroscience, reflecting his influence in shaping scholarly discourse. As Director of the Center for Brain and Cognitive Sciences, Zhou oversees a multidisciplinary research ecosystem integrating psychology, neuroscience, and clinical applications, fostering collaborations that advance China's cognitive neuroscience infrastructure through cutting-edge brain imaging and behavioral research facilities.

• Corporate Social Responsibility
• Syndicated Loans
• Portfolio Management
• +۳ مورد دیگر

Dr. Robert Schwebach serves as an Associate Professor of Finance within the Department of Finance and Real Estate at Colorado State University's College of Business, where he has held a faculty position since 1996. His academic career includes prior appointments at the University of Wyoming and industry experience as an actuarial consultant with Towers Perrin and Hewitt Associates. His educational background includes: Ph.D. in Finance, University of Nebraska–Lincoln (1992) M.A., University of South Dakota B.S., University of South Dakota Dr. Schwebach's research centers on corporate social responsibility , portfolio risk dynamics influenced by investment time horizons, supply chain effects of private equity acquisitions , and strategic flexibility in revolving credit facilities . His scholarly work, published in journals like the Journal of Risk and Insurance and Strategic Management Journal , bridges theoretical finance with practical market applications through rigorous event study methodologies. Analysis of his publication record reveals sustained focus on syndicated loan markets during financial crises, corporate social responsibility disclosures, and international investment strategies. His research consistently examines market reactions to financial announcements across banking, corporate finance, and fixed income domains with particular attention to crisis-period dynamics. No scientific awards or fellowships were documented in the available materials. In teaching, Dr. Schwebach instructs corporate finance and investments across undergraduate, MBA, Executive MBA, and Financial Risk Management master's programs. He has developed online courses through Continuing Education and taught internationally at Foreign Trade University in Hanoi. While his teaching portfolio is extensive, the documentation does not specify formal student advising relationships or research grant funding.

• Compilers
• Computer Architecture
• High-Level Synthesis
• +۵ مورد دیگر

Scott Mahlke is a Professor and Associate Chair in the Department of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. He is affiliated with both the Advanced Computer Architecture Laboratory and the Software Systems Laboratory. Dr. Mahlke joined the University of Michigan in 2001 after completing his Ph.D. at the University of Illinois and working at HP Laboratories. Ph.D., University of Illinois Former Researcher, HP Laboratories Dr. Mahlke's research spans compilers, computer architecture, and high-level synthesis, with particular focus on overcoming challenges in performance, power consumption, and reliability for next-generation computer systems. His work integrates hardware and software co-design approaches to address fundamental limitations in modern computing platforms. His research has evolved from traditional compiler and architecture topics toward increasingly incorporating machine learning acceleration, autonomous systems, and reliability engineering. Analysis of his recent publications (2021-2025) reveals a strong trend toward hardware-software co-design for emerging workloads, particularly in autonomous systems, neural network acceleration, and reliability-aware computing. His work demonstrates consistent innovation in bridging compiler technology with architectural innovations to solve real-world performance and efficiency challenges. Dr. Mahlke has received significant recognition for his contributions to the field: National Science Foundation CAREER Award (2003) for "Compiler-Directed Synthesis of Application Specific Processors" Morris Wellman Faculty Development Assistant Professor appointment (2004) ISCA Most Influential Paper Award (2006) for the 1991 paper "IMPACT: An Architectural Framework for Multiple Instruction Issue Processors" Young Alumni Award from the University of Illinois ECE Department (2007) As an educator, Dr. Mahlke has taught core computer systems courses including EECS 370 (Introduction to Computer Organization), EECS 483 (Compiler Construction), and EECS 583 (Advanced Compilers) since joining Michigan. His teaching philosophy follows Yale Patt's 10 commandments for teaching, emphasizing understanding over memorization, genuine respect for students, and taking responsibility for course content. He has received mixed but generally positive student evaluations, with students noting both his deep subject matter expertise and areas for improvement in lecture delivery. Dr. Mahlke maintains active research leadership through his affiliations with the Advanced Computer Architecture Laboratory and Software Systems Laboratory, where his team continues to explore innovative approaches to compiler and architecture challenges in modern computing systems.

Richard A. Davisمشاهده پروفایل

استاد

• Applied Probability
• Time Series Analysis
• Stochastic Processes
• +۴ مورد دیگر

Richard A. Davis is a Professor of Statistics at Columbia University and a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS). He holds the Howard Levene Professorship in Statistics. His research focuses on applied probability, time series analysis, stochastic processes, and extreme value theory. Davis has contributed to nonlinear time series models, spatial modeling, and financial econometrics. He has held academic positions at Colorado State University and MIT, and has been recognized with awards including the Koopmans Prize, IBM Faculty Award, and fellowships from the Institute of Mathematical Statistics and American Statistical Association. His education includes a B.A. and Ph.D. in Mathematics from the University of California, San Diego. He co-authored influential textbooks like Time Series: Theory and Methods and has advised numerous papers on topics ranging from count time series to spatial extremes. Current research explores machine learning applications in time series and environmental risk modeling through collaborations like the STARMAP program.

Chad Dubéمشاهده پروفایل

دانشیار

• Cognitive Psychology
• Recognition Memory
• Signal Detection Theory
• +۷ مورد دیگر

Chad Dubé is an Associate Professor in the Department of Psychology at the University of South Florida, where he has been a faculty member since 2013, advancing from Assistant to Associate Professor in 2019. His research is centered on cognitive psychology, particularly in memory, perception, and decision-making. He completed his Ph.D. and M.S. in Cognitive Psychology at the University of Massachusetts, Amherst, under Caren Rotello, and earned his B.S. in Psychology from Eastern Michigan University. Ph.D., Cognitive Psychology, University of Massachusetts, Amherst (2011) M.S., Cognitive Psychology, University of Massachusetts, Amherst (2009) B.S., Psychology, Eastern Michigan University (2006) His research interests include recognition memory, signal detection theory, ROC analysis, visual short-term memory, alpha oscillations in attention and memory, and deductive reasoning. He employs quantitative and computational modeling approaches to investigate cognitive mechanisms underlying memory and perception. The recent publications reflect a strong focus on theoretical and empirical investigations in memory and perception, particularly using signal detection and computational modeling frameworks. Key themes include central tendency effects, serial dependency, ensemble coding, and the statistical structure of memory representations. His work bridges experimental psychology with formal modeling and information theory. Although no formal awards are listed in the provided text, his publication record in high-impact journals such as Quarterly Journal of Experimental Psychology and Journal of Memory and Language indicates scholarly recognition. Chad Dubé advises graduate and undergraduate students, as indicated by annotations (GA, UA) on his publications. He has collaborated with students such as K. Tong, J. Zepp, and M. Lowry. There is no mention of specific grants or funding sources in the provided text. He previously held a postdoctoral fellowship at Brandeis University’s Volen Center and an adjunct position at Babson College. He is affiliated with the Department of Psychology, which is part of the College of Arts and Sciences at the University of South Florida. His work contributes to the Cognitive and Neural Systems (CNS) specialty area within the department.

Denis L. Rousseauمشاهده پروفایل

استاد

• Biochemistry
• Structural Biology
• Biophysics
• +۵ مورد دیگر

Denis L. Rousseau is Professor of Biochemistry at Albert Einstein College of Medicine, where his research focuses on cytochrome c oxidase structure, function, and dynamics. This 400 kDa membrane-bound enzyme serves as the terminal component of the mitochondrial electron transfer chain, responsible for over 90% of biological oxygen consumption. His research interests include: Structural mechanisms of membrane-bound enzymes Time-resolved resonance Raman spectroscopy Serial Femtosecond X-ray Crystallography (SFX) Cryo-electron microscopy of catalytic intermediates Proton translocation coupling mechanisms Dr. Rousseau's laboratory employs an integrated approach combining rapid-mixing techniques, laser spectroscopy, and advanced structural methods at national facilities including SLAC's Linac Coherent Light Source and the New York Structural Biology Center. His team embeds cytochrome c oxidase in nanodiscs for cryo-EM studies and captures transient catalytic states using femtosecond X-ray pulses. Recent publications (2015-2023) reveal structural insights into oxidized states, CO-bound configurations, oxygen intermediates, and temperature-dependent transitions in cytochrome c oxidase. This work establishes molecular foundations for understanding bioenergetic processes critical to cellular respiration. His laboratory maintains active collaborations with structural biology facilities nationwide to advance research on one of biochemistry's most fundamental enzymatic processes.

David Black-Schafferمشاهده پروفایل

استاد

• Computer Architecture
• Memory Systems
• Parallel Programming
• +۴ مورد دیگر

David Black-Schaffer is a Professor at Uppsala University's Department of Information Technology, specializing in computer systems research. As of 2023, he serves as Dean of Research for the Faculty of Science and Technology. His work bridges software and hardware innovations to enhance data movement efficiency in computer systems, with applications commercialized through a startup and integrated into industry standards like OpenCL. Black-Schaffer earned his PhD in Electrical Engineering from Stanford University in 2008, focusing on many-core processor programming. His career spans roles at Apple Inc. (contributing to OpenCL standards), postdoctoral research at Uppsala University, and academic progression from assistant to full professor (2010–2017). He has held leadership roles including Head of the Division of Computer Systems (2022) and department representative on the faculty Advisory Committee for Research (2021). His research spans computer architecture, memory systems, parallel programming, and simulation techniques. Recent publications (2024–2020) explore garbage collection, cache optimization, memory contention, NUMA systems, and instruction scheduling. Key trends include software-hardware co-design for power efficiency, reuse-aware data placement, and machine learning for performance modeling. Knut & Alice Wallenberg Foundation: Wallenberg Academy Fellowship Prolongation (2020–2025), Wallenberg Academy Fellow (2016–2021) Swedish Research Council (VR): Project Grant (2019–2024), Young Researcher Grant (2015–2018), Framework Grant (2012–2017) European Research Council: ERC Starting Grant (2017–2022) Teaching Awards: Uppsala Engineering and Science Student Union Pedagogical Prize (2012), Uppsala University Pedagogical Prize (2016), Uppsala Technical Physics Students' Teaching Award (2019) Other Grants: ScalableLearning flipped classroom project (2012–2020), Arm Ltd. collaborations on memory system designs He pioneered flipped-classroom teaching through the ScalableLearning project, impacting over 80,000 students. His research is conducted in collaboration with institutions like Arm Ltd., with past contributions to Apple's OpenCL implementation and UPMARC research center.

• Saddlepoint-Based Bootstrap
• Time Series Modeling
• Longitudinal Modeling
• +۳ مورد دیگر

Dr. A. Alexandre Trindade is a Professor in the Department of Mathematics & Statistics at Texas Tech University. His research focuses on developing novel statistical methodologies for complex data structures, with applications spanning finance, physics, and environmental science. He teaches graduate courses in Time Series Analysis and Nonparametric Statistics, and serves as advisor for the undergraduate Actuarial Science Minor program. His primary research areas include: Saddlepoint-Based Bootstrap (SPBB) : Methods for approximate inference in complex models with intractable distributions Time Series & Volatility Modeling : Multivariate autoregressive models, GARCH variants, and asymmetric distributions Spatial & Longitudinal Analysis : State-space models for missing data and spatial regression techniques Tail Risk Quantification : Nonparametric estimation of systemic risk measures like CoVaR Nonparametric Inference : Density estimation and signal detection for high-energy physics His publications demonstrate consistent innovation in statistical theory, particularly in developing resampling-based inference and extending time series methodologies. Collaborative projects include interdisciplinary work with petroleum engineering, nuclear science, and finance. Dr. Trindade maintains active research partnerships with national laboratories and industry, including reliability studies for Boeing and medical device research. He has developed specialized software for multivariate time series analysis and maintains public repositories for statistical computing resources.

• Computer Architecture
• VLSI Design
• Hardware Security
• +۳ مورد دیگر

Dr Tomasz Kazmierski is an Associate Professor in the Department of Electronics and Electrical Engineering at the University of Southampton. His research focuses on hardware security, VLSI design, and energy-efficient computing. He leads projects such as the EPSRC-funded 'Next Generation Energy-Harvesting Electronics' and 'Event-based parallel computing (POETS)'. Current Projects: Event-based parallel computing (EPSRC) Next Generation Energy-Harvesting Electronics (EPSRC) Supervision: PhD students Peiyao Sun, Xuan Ji, and Haosen Yu Research Interests: Hardware Security & Trojan Resilience Approximate Computing Ultra-Low Power Circuits Neural Network Accelerators Recent work emphasizes secure design of neural network hardware, optimization of VLSI interconnects, and aging-aware circuit techniques. His publications span conferences like IEEE ISCAS and IEEE AsianHOST, addressing topics from fault-tolerant signal processing to energy-harvesting systems.