جست‌وجوی استاد و پژوهشگر

• Ergonomics
• Human-Machine Systems
• Industrial Engineering
• +۴ مورد دیگر

Alexander Mertens serves as Associate Professor and Department Head of the Institute of Industrial Engineering within RWTH Aachen University's Faculty of Mechanical Engineering, concurrently leading the Ergonomics and Human-Machine Systems group. His dual doctorates (Dr.-Ing. and Dr. rer. medic.) underpin his interdisciplinary approach bridging engineering and medical sciences. His research centers on human-centered technology integration , with core interests in Ergonomics , Human-Machine Systems , and Virtual Reality applications . He investigates physiological workload monitoring, human-robot collaboration, and inclusive workplace design—particularly through AR/VR systems and sensor-based interventions for manufacturing and healthcare contexts. His work emphasizes translating biomechanical and psychosocial insights into practical solutions for worker safety and performance. Analysis of his 2024-2025 publications reveals three dominant trends: human-robot collaboration in manufacturing (evident in VR-based robot assistance studies), physiological workload assessment (using pupillometry and multimodal signals), and workplace health innovation (addressing interruptions, musculoskeletal disorders, and aging populations). These threads consistently prioritize human factors in digital transformation across automotive, healthcare, and industrial domains. Prof. Mertens directs the Ergonomics and Human-Machine Systems laboratory, driving initiatives like AixistenzRobotik (Aachen Competence Center for Interactive Robotics in Health/Care) and workHEALTH (holistic prevention of work-related musculoskeletal disorders). His team develops adaptive interfaces for inclusive factories and evaluates digital escape signage through age-differentiated studies, maintaining strong industry partnerships for real-world implementation.

• Cyber-physical systems
• Green and sustainable computing
• Mobile and pervasive computing
• +۷ مورد دیگر

Sandeep Gupta is a Professor and Director of the School of Computing and Augmented Intelligence at Arizona State University's Ira A. Fulton Schools of Engineering. He also serves as a Senior Global Futures Scientist. His work bridges computer science, engineering, and healthcare applications with a focus on creating reliable cyber-physical systems that interact safely with humans. Education: Ph.D. from The Ohio State University (1995) Research Interests: Professor Gupta's research spans cyber-physical systems, green and sustainable computing, mobile and pervasive computing, and parallel and distributed computing. His work increasingly focuses on human-in-the-loop systems where AI and humans collaborate safely, particularly in healthcare contexts. Recent research integrates large language models with cyber-physical systems to enhance safety and operational effectiveness in critical applications like medical monitoring and industrial automation. Research Trends: Analysis of Professor Gupta's recent publications reveals a strong focus on operational safety in human-AI collaborative systems, particularly in healthcare applications. His work combines physics-guided models with machine learning to detect "unknown-unknowns" in safety-critical systems, develops LLM-based approaches for medical image classification, and creates frameworks for ethical human-AI collaboration. The research increasingly addresses real-world challenges in diabetes management, epilepsy diagnosis, and industrial automation. Professional Service: IEEE Communication Letters Editorial Board, Area Editor (2008-Present) IEEE Journal on Special Areas in Communications - Issue on Body Area Network, Co-editor (2006-Present) Elsevier COMNET - Computer Network Journal, Reviewer (2008-Present) Technical Advisory Committee Chair for Networks (2005-Present) Advising and Grants: Professor Gupta has secured numerous research grants from NSF, NIH, Intel, Raytheon, and other organizations, totaling millions of dollars. His research portfolio includes projects on smart stadiums, mobile ECG sensing, power-aware scheduling, medical device verification, and sustainable data center management. He actively advises PhD and Master's students through thesis courses and research supervision, focusing on cyber-physical systems and healthcare applications. Labs and Research Groups: Professor Gupta leads research in cyber-physical systems with applications in healthcare, sustainable computing, and mobile networks. His work involves interdisciplinary collaboration across engineering, computer science, and medical domains, particularly through ASU's Global Futures initiatives.

Jay Barneyمشاهده پروفایل

استاد

• Strategic Management
• Entrepreneurship
• Resource-based Theory
• +۳ مورد دیگر

Jay Barney is the Presidential Professor of Strategic Management and Pierre Lassonde Chair of Social Entrepreneurship in the Department of Entrepreneurship & Strategy at the University of Utah's David Eccles School of Business. Previously holding the Chase Chair for Excellence in Corporate Strategy at Ohio State University, he is a foundational scholar in strategic management renowned for developing the resource-based view of the firm. Education: Doctor of Philosophy, Yale University Master of Arts, Yale University Bachelor of Science, Brigham Young University Barney's research revolutionized strategic management through his seminal work on how costly-to-copy firm resources create sustained competitive advantage, establishing the VRIN (Valuable, Rare, Inimitable, Non-substitutable) framework. His scholarship bridges strategic management and entrepreneurship, examining opportunity formation processes, social entrepreneurship for poverty alleviation, and the philosophical foundations of entrepreneurial research. Current work increasingly focuses on integrating social impact with strategic advantage, particularly through industrialization solutions to poverty and stakeholder engagement under uncertainty. Analysis of his 2012-2016 publications reveals three dominant research streams: (1) theoretical extensions of resource-based theory into human capital, IT capabilities, and multinational contexts; (2) philosophical and methodological foundations of entrepreneurship research; and (3) social entrepreneurship applications addressing poverty and public interest. These works consistently appear in top-tier journals including Strategic Management Journal and Academy of Management Review, demonstrating rigorous theoretical development coupled with practical implications for organizational strategy. Scientific Awards: SMS Fellow Fellow of the Academy of Management Honorary Doctorate from University of Lund Honorary Doctorate from Copenhagen Business School Honorary Doctorate from Universidad Pontificia Comillas As a dedicated educator, Barney teaches doctoral seminars and strategy courses while mentoring PhD students in strategic management and entrepreneurship. His professional impact extends through executive training programs across North America and Europe, and strategic consulting engagements focused on organizational transformation. He has significantly shaped the field through editorial leadership as associate editor of Journal of Management, senior editor of Organization Science, and co-editor of Strategic Entrepreneurship Journal, while serving in officer roles for both the Strategic Management Society and Academy of Management's Business Policy and Strategy Division. Barney's research activities are closely integrated with the Lassonde Entrepreneur Institute at the University of Utah, where his social entrepreneurship chair supports initiatives connecting strategic management principles with poverty alleviation efforts and opportunity creation in resource-constrained environments.

Cosimo Lacavaمشاهده پروفایل

استادیار

• Silicon Photonics
• Integrated Optics
• Nonlinear Optics
• +۳ مورد دیگر

Cosimo Lacava is an Assistant Professor at the University of Pavia, Department of Industrial and Information Engineering. He works in the Integrated Photonics Laboratory (Floor F) and specializes in silicon photonics, integrated optics, and nonlinear optics for optical communications applications. His research focuses on developing advanced photonic integrated circuits for next-generation optical networks and signal processing systems. Dr. Lacava's primary research interests include: Silicon and silicon nitride photonic devices (design, fabrication and testing) Integrated electro-optic devices for telecommunications applications Design of highly spectral-efficient optical networks enabled by advanced modulation formats Digital signal processing (DSP) for telecommunication and data communication applications Nonlinear optics for all optical signal processing His recent publication record demonstrates significant contributions to integrated photonics, particularly in wavelength conversion technologies, nonlinear signal processing, and silicon nitride platforms. The research shows a clear progression from fundamental studies of nonlinear optical properties to practical implementations of photonic integrated circuits for optical communications systems. His work bridges theoretical understanding with practical device development for real-world applications. Dr. Lacava received his education at the University of Pavia, graduating with honors in Electronic Engineering in 2011 and completing his PhD in Optoelectronics and Electronic Engineering in 2014. Prior to his current position, he worked as a Senior Research Fellow at the Optoelectronics Research Centre, University of Southampton, and as a Postdoctoral researcher at the Quantum Electronics Laboratory at the University of Pavia working on the 'Fabulous' European Project. As an educator, he teaches Physics 1 for civil and environmental engineering students. His laboratory work in the Integrated Photonics Laboratory focuses on developing and testing photonic integrated circuits with applications spanning optical communications, signal processing, and emerging quantum information systems.

Ahmad Lotfiمشاهده پروفایل

استاد

• Computational Intelligence
• Ambient Intelligence
• Robotics
• +۷ مورد دیگر

Ahmad Lotfi is a Professor of Computational Intelligence and Head of Department of Computer Science at Nottingham Trent University , with a Visiting Professor role at Tokyo Metropolitan University . He leads the Computational Intelligence and Applications (CIA) research group and has supervised over 30 PhD students to completion. PhD in Learning Fuzzy Systems (University of Queensland, 1995) MTech in Control Systems (Indian Institute of Technology, India) BSc in Control Systems (Isfahan University of Technology, Iran) His research spans computational intelligence , ambient intelligence , robotics , and machine learning , with applications in dementia monitoring , smart environments , and healthcare technology . Recent work focuses on using thermal sensor arrays for privacy-preserving human activity analysis. He has secured funding from Innovate UK , EPSRC , The Royal Society , and Horizon 2020 , with projects like iCarer (assistive living), SmartBerry (agricultural AI), and BigSpark (financial data augmentation). His 15 most recent articles demonstrate expertise in Wi-Fi-based activity recognition , EEG fall detection , and thermal sensor fusion . Senior Member IEEE Member of British Computer Society (MBCS) Editorial roles in Soft Computing and Journal of Ambient Intelligence and Smart Environments He has served as Program Chair for conferences like PETRA and ICCRT , and as Keynote Speaker at PETRA 2023 . His 28+ years of academic leadership include organizing UKCI and UKRAS conferences.

• Digital Humanities
• Human-Centered Computing
• Data Visualization
• +۵ مورد دیگر

Dr. Almila Akdag is an Assistant Professor in Human-Centered Computing at Utrecht University's Faculty of Science, Department of Information and Computing Sciences. As a Digital Humanities scholar with expertise spanning new media analysis, bibliometrics, and information visualization, she combines qualitative and quantitative methods to study humanities and social data. Research Focus Her interdisciplinary research bridges: Digital Humanities : Computational analysis of cultural artifacts including paintings, poetry, and oral histories Human-Centered AI : Developing empathetic and accessible AI systems Trauma Informatics : Analyzing breathing patterns in oral histories of trauma survivors Cultural Analytics : Studying art communities and online creative platforms Following the 2023 Turkey/Syria earthquake, she is creating an oral history archive to document collective memory of the disaster, with particular focus on Turkish, Kurdish and Syrian diaspora experiences. Awards and Recognition NWO VENI laureate for 'deviantArt: Mapping the Alternative Art World' project Co-initiator of Mellon Grant: 'Tools for Analysis and Visualization of Large Image/Video Collections for Humanities' Leadership and Service Workgroup leader of 'Visual Media and Interactivity' for DARIAH-EU Founding member of International Society for Knowledge Organization (ISKO LC Low Countries Chapter)

Grzegorz Chrupałaمشاهده پروفایل

دانشیار

• Computational Linguistics
• Artificial Intelligence
• Cognitive Science
• +۳ مورد دیگر

Grzegorz Chrupała is an Associate Professor at the Department of Cognitive Science and Artificial Intelligence , Tilburg University, where he leads research in computational approaches to multimodal communication. Previously, he was a postdoctoral researcher at Saarland University's Spoken Language Systems group and earned his PhD from Dublin City University's School of Computing. His research bridges biological and artificial computation , focusing on enabling machines to learn language from multimodal data (speech, gestures, visual-auditory stimuli) as children do naturally. This involves developing and interpreting deep learning architectures, analyzing emergent representations, and advancing speech technology for under-resourced languages. Key themes include Visually grounded speech modeling Feature attribution and model interpretability Human-inspired learning paradigms BlackboxNLP workshop leadership His recent publications examine speech model reliability , lexical tone encoding , and contextual dependencies in NLP systems. He mentors a team of PhD candidates and alumni working on topics like user-centric interpretability, bioacoustics, and disentangled speech representations. He also serves on the board of the Dutch Open Speech Technology Foundation, chairs Interspeech 2025 tutorials, and contributes as an Action Editor for TACL.

Zhang Yangمشاهده پروفایل

دانشیار

• Artificial Intelligence in Biomedical Imaging
• Deep Learning for Omics Data Analysis
• Pathogen Detection and Diagnostics
• +۷ مورد دیگر

Zhang Yang is an Associate Professor at the School of Medical Engineering, Harbin Institute of Technology (Shenzhen), with a joint appointment as Visiting Professor at the University of Tokyo starting in July 2024. He holds a PhD from the University of Cambridge's Department of Pathology and an M.Phil. from the University of Hong Kong's HKU-Pasteur Research Center. Previously, he served as an Assistant Professor at Harbin Institute of Technology (Shenzhen) from September 2015 to December 2020. His research integrates computational and experimental approaches to address challenges in pathogen and cancer research. On the computational side, his work focuses on developing AI-powered microscopic imaging systems, applying deep learning to analyze multi-omics data (including proteins, DNA, miRNAs, LncRNAs, and mRNAs), and utilizing deep learning in cheminformatics for drug discovery. On the experimental side, his laboratory combines imaging, high-throughput sequencing, mass spectrometry, and chemical biology to understand disease mechanisms at the molecular level. His publication record demonstrates significant impact, with over 50 SCI-indexed papers in high-impact journals including Nature Communications, Briefings in Bioinformatics, Bioinformatics, Analytical Chemistry, and Trends in Biotechnology. His work has been cited by prestigious journals such as Nature Reviews Methods Primers and Nature Communications, with three ESI highly cited papers. His research spans multiple interdisciplinary fields, combining artificial intelligence with biomedical applications to advance diagnostic and therapeutic approaches. World's Top 2% Scientists 2021 Fellow of the Royal Society of Biology Three ESI Highly Cited Papers Five authorized national invention patents As an academic leader, he serves as Associate Editor for BMC Biology and Frontiers in Microbiology, Academic Editor for PLOS Genetics, Editorial Board Member for Communications Biology, and Guest Editor for a Special Issue on AI in analytical chemistry in Trends in Analytical Chemistry. His laboratory actively collaborates with international institutions, with graduates pursuing further studies at Hong Kong Chinese University, Hong Kong University of Science and Technology, Hong Kong Polytechnic University, Macau University, and the University of New South Wales. He teaches Introduction to Modern Biology for undergraduates and Bioanalytical Chemistry for graduate students.

Ajay K. Kohliمشاهده پروفایل

استاد

• Customer Centricity
• Sales Management
• B2B Marketing
• +۴ مورد دیگر

Ajay K. Kohli is the Gary T. and Elizabeth R. Jones Chair and Regents' Professor in Marketing at the Scheller College of Business, Georgia Institute of Technology. His research focuses on customer centricity, sales management, B2B marketing, brand management, and market orientation. He has served as Editor-in-Chief of the Journal of Marketing and currently holds editorial roles at the Journal of Marketing and International Journal of Research in Marketing . Current Roles: Regents' Professor, Scheller College of Business Editorial Leadership: Former Editor-in-Chief of Journal of Marketing , Associate Editor, Area Editor Academic Recognition: AMA Fellow, EMAC Fellow, ISBM Fellow, multiple awards Education: PhD in Business Management, University of Pittsburgh PGDM (MBA), Indian Institute of Management, Calcutta B. Tech in Electrical Engineering, Indian Institute of Technology, Kharagpur Research Interests span market orientation, customer solutions, sales management, and brand management. His work explores how firms adapt to market changes, manage customer relationships, and leverage relational processes for competitive advantage. He emphasizes practical relevance, bridging academic research with industry applications. Scientific Awards and Honors Three honorary doctorates (BI Norwegian Business School, University of St. Gallen, Corvinus University of Budapest) IIM Calcutta’s Distinguished Alumnus Award (2017) AMA/McGraw-Hill/Irwin Career Award (2017) Paul D. Converse Award (2016, termed "Marketing Hall of Fame" by Fortune ) Multiple best paper awards across journals Teaching and Professional Experience: Professor Kohli has taught at Emory University, Harvard Business School, University of Texas at Austin, and several international institutions. He has led executive education seminars globally and received the Jack G. Taylor Teaching Excellence Award at UT-Austin. His industry experience includes consulting with 3M, Accenture, IBM, and Deloitte.

Saibal Mukhopadhyayمشاهده پروفایل

استاد

• VLSI Systems
• Nanotechnology
• Low-Power Electronics
• +۵ مورد دیگر

Dr. Saibal Mukhopadhyay is a Professor in the Department of Electrical and Computer Engineering at the Georgia Institute of Technology, where he joined in 2007. He holds the Joseph M. Pettit Professorship and is recognized as an IEEE Fellow for his contributions to low-power and reliable VLSI systems. Education: BEng (Jadavpur University, India), Ph.D. (Purdue University) Labs: Gigascale Reliable Energy Efficient Nanosystem (GREEN) Lab His research focuses on VLSI Systems , Nanotechnology , and Low-Power Electronics , with emphasis on technology-circuit co-design for energy-efficient computing. Recent work explores Compute-in-Memory (CIM) architectures and Spiking Neural Networks for edge AI. Key article themes include Transformer Model Acceleration , Quantum Computing Calibration , 3D Object Detection , and Device Aging Analysis , reflecting his interdisciplinary approach bridging hardware design and machine learning. Scientific Awards IEEE Fellow (2018) ONR Young Investigator (2012) NSF CAREER Award (2011) IBM Faculty Awards (2009, 2010) Best Paper Awards (IEEE-Nano 2003, ICCD 2004)

Heiner Giefersمشاهده پروفایل

استاد

• Cloud Computing
• Hardware Acceleration
• Field-Programmable Gate Arrays
• +۷ مورد دیگر

Heiner Giefers is a Professor for Cloud Computing at the Department of Computer Science and Natural Sciences at Southwestphalia University of Applied Sciences since 2018. Prior to this position, he worked as a Research Staff Member at IBM Research - Zürich (2013-2018), focusing on hardware acceleration in cloud environments, implementation of big data algorithms on FPGAs, and development of hardware platforms for approximate and in-memory computing. Dr. Giefers received his doctorate (Dr. rer. nat.) from Universität Paderborn in 2012 with a dissertation titled "Design and Programming of Reconfigurable Mesh based Many-Cores." His academic journey at Universität Paderborn includes serving as an Academic Council Member (Akademischer Rat a.Z.) from 2008-2013 and as a Scientific Staff Member from 2006-2012, where he taught digital technology and computer architecture. Professor Giefers' research focuses on energy-efficient computing, particularly through hardware acceleration using FPGAs for cloud and AI workloads. His work spans cloud computing infrastructure, hardware-software co-design, approximate computing, in-memory computing, and energy-efficient implementations of machine learning algorithms. He has made significant contributions to the field of reconfigurable hardware for high-performance computing applications. His recent publications show a strong trend toward applying hardware acceleration techniques to artificial intelligence and machine learning workloads, with a particular focus on energy efficiency. His work bridges the gap between theoretical computer science and practical hardware implementation, often resulting in patented technologies that address real-world computing challenges in cloud environments. Best Paper Award for "Stochastic Matrix-Function Estimators: Scalable Big-Data Kernels with High Performance" (2016) Best Paper Award Nomination for "Energy-Efficient Stochastic Matrix Function Estimator for Graph Analytics on FPGA" (2016) Best Paper Award Nomination for "Analyzing the energy-efficiency of dense linear algebra kernels by power-profiling a hybrid CPU/FPGA system" (2014) Best Paper Award Nomination for "A Triple Hybrid Interconnect for Many-Cores: Reconfigurable Mesh, NoC and Barrier" (2010) Professor Giefers actively supervises numerous Bachelor's and Master's students, with over 50 completed theses covering topics from machine learning and cloud computing to IoT systems and hardware acceleration. He leads the "Energy-efficient AI" project (eki), which aims to increase the energy efficiency of AI systems through approximation techniques for FPGA implementation. Additionally, he collaborates with Prof. Dr. Christian Plessl on the "Digital teaching materials with Jupyter Notebooks" project, creating interactive learning materials that integrate teaching content, program code, and results into a single document. His work extends to practical applications through multiple patents related to FPGA implementations, neural networks, and memory systems, demonstrating his commitment to translating research into real-world solutions.

Dejan Markovicمشاهده پروفایل

استاد

• Implantable neuromodulation systems
• Domain-specific compute architectures
• Design methodologies
• +۳ مورد دیگر

Dejan Markovic is a Professor of Electrical and Computer Engineering at the University of California, Los Angeles (UCLA), holding the Mukund Padmanabhan Term Chair in Electrical Engineering and serving as Area Director for Circuits and Embedded Systems. His research spans implantable neuromodulation systems, domain-specific compute architectures, and energy-efficient design methodologies for biomedical and embedded applications. Dr. Markovic earned his PhD (2006) and MS (2000) from UC Berkeley and BS (1998) from the University of Belgrade, Serbia. His research focuses on ultra-low-power integrated circuits for neural interfaces, including artifact-free stimulation/sensing platforms and neural recording front-ends, alongside domain-specific architectures for sparse linear algebra in IoT and mobile computing. Recent work demonstrates strong trends in medical neuromodulation and energy-efficient VLSI for biomedical signal processing and wireless communications. His scientific contributions have been recognized with prestigious awards including IEEE Fellow (2021), ISSCC Lewis Award (2014), ISSCC Jack Raper Award (2010), and NSF CAREER Award (2009). Additional honors include UC Berkeley's David J. Sakrison Memorial Prize (2007) and multiple best paper awards. Dr. Markovic co-founded semiconductor IP startup Flex Logix Technologies (2014) and leads the DMGroup research lab at UCLA. He teaches core courses including ECE 115C (Digital Integrated Circuits), ECE M216A (VLSI Design), and BME M260 (Neuroengineering), mentoring students in cutting-edge VLSI design for medical and communication applications. The DMGroup lab specializes in developing implantable neuromodulation systems, domain-specific compute engines, and novel design methodologies, with recent projects featured in UCLA's coverage of brain-computer interface technology and Anari AI's $2M funding for personalized AI hardware.

Chadi Jabbourمشاهده پروفایل

استاد

• Analog-to-Digital Converter Design
• Communication Systems
• Mixed-Signal Systems
• +۷ مورد دیگر

Chadi Jabbour is a Professor at Institut Polytechnique de Paris , specializing in analog/digital converter design, communication system linearization, and flexible receiver architectures. He leads the Communication Circuits and Systems (C2S) team at the Information Processing and Communication Laboratory (LTCI) in the Communications and Electronics (Comelec) department.

• Vascular Biology
• Atherosclerosis
• Arterial Stiffness
• +۲ مورد دیگر

Dr. Stella Daskalopoulou is a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) and a Professor in the Department of Medicine at McGill University's Faculty of Medicine and Health Sciences. She specializes in translational cardiovascular research with a focus on vascular health, atherosclerosis, and hypertension management. Senior Scientist, RI-MUHC Glen site Professor, Department of Medicine, McGill University Member, Cardiovascular Health Across the Lifespan Program Research Focus: Her work integrates biomedical technology with clinical investigation to identify early vascular impairment markers. Key areas include: Arterial stiffness and hemodynamic assessment Adiponectin signaling pathways in atherosclerosis Sex-specific cardiovascular risk stratification Biomarker discovery for plaque instability Pregnancy-related vascular complications Machine learning applications in plaque classification Scientific Engagement: Dr. Daskalopoulou contributes to hypertension guideline development (2024 ESC Guidelines) and explores environmental impacts on vascular health (household pollution studies). Her recent publications emphasize: Deep learning for plaque characterization Sex hormone receptor pathways in atherosclerosis Adipokine interactions with HDL metabolism Clinical decision tools for preeclampsia prediction Laboratory: Leads the Vascular Health Unit at RI-MUHC, combining histopathology, immunophenotyping, and advanced imaging for translational research.

• Wireless Communication
• Machine Learning
• Signal Processing
• +۴ مورد دیگر

Prof. Dr. Haris Gačanin is a faculty member at RWTH Aachen University, affiliated with the Institute for Distributed Signal Processing under the College of Electrical Engineering. His research focuses on integrating machine learning with wireless communication systems, particularly in industrial IoT, edge computing, and network optimization. Current academic rank: Professor Contact: harisg@dsp.rwth-aachen.de Research Interests: Wireless systems, machine learning, signal processing, and network optimization. Key contributions include: Adaptive resource allocation in IIoT and vehicular networks AI-driven channel estimation and feedback mechanisms Security-oriented emitter identification via metric learning Federated/transfer learning for edge environments Hardware-efficient deep learning models for mmWave and THz communications Methodological Focus: Combines reinforcement learning, attention mechanisms, and robust neural architectures with practical implementations on FPGA and vehicular systems.