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Ahmad LotfiView profile

Professor

• Computational Intelligence
• Ambient Intelligence
• Robotics
• +7 more

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
• +5 more

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 ChrupałaView profile

Associate Professor

• Computational Linguistics
• Artificial Intelligence
• Cognitive Science
• +3 more

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 YangView profile

Associate Professor

• Artificial Intelligence in Biomedical Imaging
• Deep Learning for Omics Data Analysis
• Pathogen Detection and Diagnostics
• +7 more

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. KohliView profile

Professor

• Customer Centricity
• Sales Management
• B2B Marketing
• +4 more

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 MukhopadhyayView profile

Professor

• VLSI Systems
• Nanotechnology
• Low-Power Electronics
• +5 more

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 GiefersView profile

Professor

• Cloud Computing
• Hardware Acceleration
• Field-Programmable Gate Arrays
• +7 more

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 MarkovicView profile

Professor

• Implantable neuromodulation systems
• Domain-specific compute architectures
• Design methodologies
• +3 more

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 JabbourView profile

Professor

• Analog-to-Digital Converter Design
• Communication Systems
• Mixed-Signal Systems
• +7 more

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
• +2 more

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
• +4 more

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.

• Photonics
• Biophotonics
• Optical Microscopy
• +3 more

Dr. Wolfgang Hübner is a Researcher at the Faculty of Physics at University of Bielefeld, Germany, affiliated with the Biomolecular Photonics Group. His work focuses on advanced optical imaging techniques applied to cellular and molecular structures. He maintains an active research program as evidenced by numerous publications from 2023-2025. His research interests center on photonics, biophotonics, optical microscopy, super-resolution imaging techniques, cellular biophysics, and molecular imaging. Dr. Hübner's work bridges physics and biology, developing and applying cutting-edge microscopy methods to address biological questions at the nanoscale level. His recent publications demonstrate a strong focus on super-resolution microscopy techniques, particularly structured illumination microscopy, fluorescence lifetime imaging, and correlative imaging approaches. His research investigates cellular structures like liver sinusoidal endothelial cells, dystroglycan mutants, and mitochondrial dynamics, revealing how advanced optical methods can visualize biological processes at unprecedented resolution. Dr. Hübner's research shows consistent development in both methodological advances in optical imaging and biological applications. His work spans from fundamental optical engineering to biomedical applications, demonstrating interdisciplinary expertise across physics, engineering, and cell biology.

Luca ModeneseView profile

Senior Lecturer

• Computational biomechanics
• Musculoskeletal modeling
• Neuromuscular modeling
• +2 more

Dr. Luca Modenese is a Senior Lecturer in Biomechanics at the Graduate School of Biomedical Engineering, University of New South Wales (UNSW). A recipient of the prestigious Scientia Fellowship , his research focuses on computational biomechanics with specialization in musculoskeletal and neuromuscular modeling. He has extensive experience across institutions including Imperial College London, Griffith University, and Sheffield University. Education : Mechanical Engineering (summa cum laude), University of Padua (2008) PhD in Structural Biomechanics, Imperial College London (2013) Research Expertise spans musculoskeletal modeling, neuromuscular simulation, orthopaedic biomechanics, and predictive computational methods. His work integrates patient-specific modeling with finite element analysis and predictive simulations. Recent publications highlight advancements in GAN-based motion data generation , electromyography-informed models , and AI-enhanced biomechanical analysis . Scientific Recognition : Scientia Fellowship (UNSW) Athanasiou ABME Award (2021) Publication of the Year (Australia and New Zealand Society of Biomechanics, 2017) Griffith University Awards (2015) OpenSim Fellows Program (Stanford, 2014) Supervision & Collaboration : Currently supervising PhD students Arnault Caillet and Metin Bicer at Imperial College London as external supervisor. Actively involved in research partnerships with institutions including Imperial College London, Stanford University, and the Menzies Health Institute Queensland.

• Human-Computer Interaction
• Wearable Computing
• Augmented Reality
• +5 more

Yuta Sugiura is an Associate Professor in the Department of Information and Computer Science at Keio University's Faculty of Science and Technology. His research focuses on innovative human-computer interaction techniques, particularly in wearable computing, tangible interfaces, and novel input methods. Previously, he worked as a postdoctoral researcher at the National Institute of Advanced Industrial Science. Dr. Sugiura's research interests span Human-Computer Interaction, Wearable Computing, Augmented Reality, Tangible User Interfaces, Gesture Recognition, Ubiquitous Computing, Haptics, and Virtual Reality. His work often explores how everyday objects and environments can become interactive surfaces, with notable projects including the iRing (intelligent ring), SenSkin (skin as interface), and EarHover (mid-air gesture recognition for hearables). He has developed numerous novel interaction techniques that leverage physical properties of materials and human physiology for input and output. His recent publications indicate a strong focus on hearable computing, medical applications of HCI, edible interfaces, and novel authentication methods. The research shows a consistent pattern of exploring unconventional interaction surfaces and leveraging subtle physical phenomena for input sensing. His work has significant implications for healthcare applications, particularly in neurological disorder screening and rehabilitation. Best Paper Award Dr. Sugiura has advised numerous students who have gone on to publish significant work in top-tier HCI venues. His research has been supported by various grants enabling the development of novel interaction techniques and systems. He maintains strong collaborations with researchers across Japan and internationally, particularly in the fields of wearable computing and medical applications of HCI. His laboratory appears to focus on lifestyle computing, developing interfaces that integrate seamlessly into daily activities. Current projects include exploring edible displays, adaptive ear interfaces, and novel authentication methods using wearable devices. Future work seems to be heading toward more medical applications of HCI, particularly in neurological assessment and rehabilitation.

• Manufacturing Engineering
• Welding Technologies
• Non-Destructive Testing
• +5 more

Manuela De Maddis is a Tenured Researcher at the Department of Management and Production Engineering (DIGEP) of the Polytechnic of Turin (PoliTo), where she has worked since 2005. She is also a member of the Interdepartmental Center J-Tech@PoliTo. PhD in Industrial Production System Engineering (2004), Polytechnic of Turin MSc in Management Engineering (2001), University of Calabria Her research focuses on Manufacturing Technologies , particularly Welding Processes and Infrared Thermography for non-destructive testing. She leads projects like TECNOPROTEO (2024-2027) and NDTxW (2024-2025) as Scientific Manager. Her work integrates Machine Learning and High-Fidelity Modeling for digital manufacturing systems. Recent publications analyze active thermography in weld quality, electrode degradation in spot welding, and probabilistic tolerancing methods. She supervises PhD students in Materials Science and Production Engineering . Mentoring Polito Project (M2P) (2023) Learning to Teach (L2T) (2023) Manuela teaches courses like Industrial Welding Processes , Advanced Manufacturing Technologies , and Ergonomics in Production Innovation at both undergraduate and graduate levels. She contributes to interdisciplinary labs focused on Manufacturing Process Innovation and Technological Validation .