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Caitano L. da SilvaView profile

Associate Professor

• Atmospheric Sciences
• Space Sciences
• Geophysics
• +9 more

Caitano L. da Silva serves as Associate Professor of Physics at New Mexico Institute of Mining and Technology (New Mexico Tech), affiliated with the Department of Physics and Langmuir Laboratory for Atmospheric Research. His work bridges atmospheric sciences, space physics, and plasma dynamics with experimental and computational approaches. His research centers on atmospheric and space electricity phenomena, including thunderstorm effects on near-Earth space, lightning physics, electrical discharge plasma modeling, and space plasma wave analysis. Key interests involve narrow bipolar events, sprite dynamics, X-ray/gamma-ray emissions from lightning, and computational tools for geophysical data interpretation. His team investigates high-energy atmospheric processes through laboratory experiments and field measurements. Recent publications (2021-2024) reveal dominant trends in lightning initiation mechanisms, runaway electron production, and electromagnetic wave propagation. Work frequently combines neuromorphic sensors, Geant4 simulations, and 3D interferometry to study high-energy radiation from leaders and sprite current-morphology relationships. The research demonstrates strong interdisciplinary connections between plasma physics and atmospheric electricity. Dr. da Silva leads an active research group at Langmuir Laboratory, mentoring students evidenced by underlined co-authorships in publications. His team collaborates internationally on projects involving rocket-triggered lightning experiments, narrow bipolar event analysis, and ionospheric disturbance studies. The NY Times featured his 2023 research on lightning-related space phenomena.

Manuela NowotnyView profile

Professor

• Sensory Physiology
• Evolutionary Biology
• Acoustic Communication
• +7 more

Prof. Dr. Manuela Nowotny is a Professor of Animal Physiology at the Institute for Zoology and Evolutionary Research, University of Jena, Germany. Her research focuses on understanding sensory adaptations in the animal kingdom, particularly investigating the functions and specializations of insect and mammalian auditory systems. She leads a research group that explores how sensory organs detect and process environmental signals, with implications for understanding perception and behavior regulation. Dr. Nowotny's research interests span several interconnected areas of sensory physiology and evolutionary biology. Her work examines how sensory organs become highly specialized to detect specific environmental signals while ensuring animal survival. A major focus is on convergent evolution in hearing , where she has discovered remarkable similarities between insect and mammalian auditory systems. Her group investigates insect ears , particularly in bushcrickets, revealing specialized adaptations like the auditory fovea - previously thought to exist only in mammals. She also studies mammalian hearing mechanisms and the development of tinnitus following acoustic trauma. Her interdisciplinary approach combines biomechanics, neurophysiology, and evolutionary biology to understand how sensory information is processed at the organ level. Analysis of Dr. Nowotny's recent publications reveals a consistent focus on comparative auditory physiology across species. Her work demonstrates how insects provide valuable models for studying natural diversity in mating behavior and sensory adaptation. A recurring theme is the discovery of convergent evolutionary solutions in hearing mechanisms between phylogenetically distant species. Her research on traveling waves in insect hearing organs shows surprising similarities to mammalian cochlear mechanics, challenging previous assumptions about the uniqueness of mammalian auditory processing. More recent work has expanded into neurotoxicology, examining how pesticides affect insect auditory processing, and biomedical applications through neuromorphic engineering for hearing aids. Adolf-Messer Stiftungspreis 2009 for tinnitus research Multiple Deutsche Forschungsgemeinschaft grants (NO 841/1-1, NO 841/2-1, NO 841/4-1) Funding from Jürgen Manchot Foundation Goethe University's "Nachwuchswissenschaftler/innen im Fokus" project Dr. Nowotny's research is primarily supported by the Deutsche Forschungsgemeinschaft (DFG), with multiple grants focusing on different aspects of auditory physiology. Her work on bushcricket hearing mechanisms (NO 841/1-1 and NO 841/2-1) has revealed fundamental principles of sensory adaptation, while her tinnitus research (NO 841/4-1) explores the connection between inner ear damage and phantom noise perception. She has successfully mentored numerous researchers, with several collaborators (particularly S. Schöneich, J. Scherberich, and M. Kössl) appearing consistently across publications, suggesting a productive mentoring relationship. Her lab utilizes diverse methodologies including biomechanical measurements, neurophysiological recordings, and comparative anatomical studies. Dr. Nowotny leads a research group within the Institute for Zoology and Evolutionary Research that employs interdisciplinary approaches to study auditory systems. Her team combines expertise in entomology, mammalian physiology, biomechanics, and neuroethology to investigate sensory processing across species. The lab maintains collaborations with institutions including Goethe University and appears to have strong connections with researchers studying neurophysiology and acoustic communication. Current projects include examining the effects of pesticides on insect auditory processing and developing neuromorphic engineering applications for hearing aid technology through the NeuroSensEar project.

Xiaolin XuView profile

Associate Professor

• Security
• Machine Learning
• AI Security/Privacy
• +5 more

Xiaolin Xu is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University. His research focuses on hardware and AI security, machine learning privacy, and energy-efficient deep learning. He earned a PhD from the University of Massachusetts Amherst and completed postdoctoral work at the Florida Institute for Cybersecurity Research. Education PhD, Electrical and Computer Engineering, University of Massachusetts Amherst, 2016 M.S., B.E., University of Electronic Science and Technology of China Research Interests : His work spans secure hardware design, AI model protection, and embedded systems security. Notable projects include securing FPGA-based ML accelerators and developing defenses against adversarial attacks. Recent Article Trends : Recent publications emphasize robustness in neural architectures, secure multi-party computation, and lightweight graph-based models for edge devices. Grants & Awards 2025 DAC Under-40 Innovators Award NSF CAREER Award (2023) Multiple NSF grants for hardware security research Advising : Supervises PhD students including Shijin Duan and Jiaxing, focusing on ML security and hardware-software co-design.

Mauro Di MarcoView profile

Associate Professor

• Nonlinear Dynamics
• Chaos Theory
• Memristor Circuits
• +2 more

Mauro Di Marco serves as an Associate Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena, Italy, with office hours held weekly in the San Niccolò Complex (room 209) for student consultations. His research specializes in nonlinear dynamics and chaos theory applied to memristor-based electronic systems, focusing on discrete-time circuit analysis, snap-back repellers, coexisting attractors, and parameter-independent bifurcations. Key contributions include embedding classical chaotic maps into simplified memristor architectures and analyzing convergence in neural network models like the brain-state-in-a-convex-domain. Recent publications demonstrate expertise in designing tunable Chua's circuits using nonvolatile memristors, advancing applications in chaotic signal generation and neuromorphic computing through rigorous mathematical modeling and experimental validation.

• Speech Processing
• Biomedical Image Processing
• Image Processing
• +7 more

Chandra Sekhar Seelamantula is a Professor in the Department of Electrical Communication Engineering at the Indian Institute of Science (IISc), Bangalore, leading the SPECTRUM LAB. His research spans signal and image processing, computational imaging, and AI applications in healthcare, with expertise in Speech Processing, Biomedical Image Processing, Compressed Sensing, and Neuromorphic Imaging. He teaches core courses including Digital Signal Processing and Time-Frequency Analysis. His educational background includes: Postdoctoral fellow, Ecole polytechnique fédérale de Lausanne (2006-2009) Ph.D., Indian Institute of Science, Bangalore (2005) B.E., Osmania University College of Engineering, Hyderabad (1999) Professor Seelamantula's work focuses on advancing Sampling Theory and solving Inverse Problems in Computational Imaging through AI-driven approaches. His research bridges theoretical foundations with practical applications in Digital Healthcare, particularly in Biomedical Image Analysis and Neural Signal Processing, contributing to innovations in medical diagnostics and assistive technologies. His scientific awards and honors include: Outstanding Editorial Board Member Award 2022, IEEE Transactions on Image Processing Digital Health prize at NBEC 2018 Prof. Priti Shankar Teaching Award 2013 Intellectual Ventures Invention Awards (2010, 2011) IBM India Research Labs Research Student Fellowship Award (2001-2004) Multiple IEEE student paper contest prizes Undergraduate honors including Srinivasa Ramanujam Gold Medal (1997-1999) He has advised graduate students and secured research support through prestigious fellowships. His professional service includes leadership roles in IEEE Signal Processing Society chapters and technical committees. He directs the SPECTRUM LAB at IISc, which pioneers research in computational imaging, neuromorphic systems, and AI-driven healthcare solutions.

• Compound Semiconductor Electronics
• GaN Device Technologies
• Terahertz Electronics
• +4 more

Edward Wasige is Professor of High Frequency Electronics in the Division of Electronics and Nanoscale Engineering at the University of Glasgow's School of Engineering, where he leads the High Frequency Electronics (HFE) Group. His research spans compound semiconductor devices, including GaN technologies for power/microwave electronics and InP-based systems for terahertz applications. Education: BSc (Eng.) in Electrical Engineering (First Class Honours), University of Nairobi, 1988 MSc in Microelectronics & Telecommunications, University of Liverpool, 1990 PhD in Electrical Engineering (with Distinction), Kassel University, 1999 Research Focus: His group pioneers high-frequency semiconductor devices with emphasis on neuromorphic photonics (RTD-based spiking neurons), terahertz wireless systems, and GaN HEMT advancements. Current work includes photonic-electronic integration for brain-inspired computing and thermal optimization of wide-bandgap devices. Publication Trends: Recent articles (2023-2024) demonstrate strong focus on terahertz instrumentation (35%), neuromorphic hardware (40%), and GaN device innovation (25%), with emerging themes in cryogenic characterization and 6G communications testbeds. Awards: UNESCO Postdoctoral Fellowship (Technion, Israel) Laboratories: Leads the HFE Group with capabilities in nanofabrication (sub-100nm processes), on-wafer characterization up to 1.7 THz, and semiconductor device testing across temperature ranges (77K–400K).

Mohammad Khaleqi Qaleh JooqView profile

Research Fellow

• Neuromorphic Computing
• ASIC Design
• Emerging Devices
• +7 more

Dr. Mohammad Khaleqi Qaleh Jooq serves as a Postdoctoral Research Fellow at the International Centre for Neuromorphic Systems (ICNS), Western Sydney University. Previously, he held a Brain Pool Postdoctoral Research Fellowship at Inje University, South Korea from 2022 to 2024. His academic background includes: Ph.D. in Electrical Engineering, Lorestan University, Khorramabad, Iran (2019) His research focuses on neuromorphic hardware systems and next-generation electronics, with primary expertise in ASIC design for real-world applications, carbon nanotube-based devices, and fuzzy logic implementations. His work bridges theoretical device modeling with practical image processing solutions through emerging beyond-CMOS technologies and approximate computing paradigms. As an active member of the International Centre for Neuromorphic Systems, he contributes to advancing brain-inspired computing architectures while exploring nanoscale device physics for next-generation hardware implementations.

Andrea SoltoggioView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Lifelong Learning
• +11 more

Dr. Andrea Soltoggio is a Reader in Artificial Intelligence (Associate Professor) and Research Coordinator in the Computer Science Department at Loughborough University's School of Science. He holds a combined BSc and MSc in Computer Science from the Norwegian University of Science and Technology and Politecnico di Milano, and a PhD from the University of Birmingham. His academic journey includes research positions at EPFL, the University of Central Florida, and Bielefeld University where he served as Technical Coordinator for the FP7 European project AMARSi. His research focuses on creating AI systems that learn continuously like biological brains, with particular emphasis on lifelong learning, collaborative knowledge sharing, and energy-efficient AI. Dr. Soltoggio has made significant contributions to the development of algorithms that enable AI systems to share knowledge without centralized control, as demonstrated in his MOSAIC framework published in 2025 and his Nature Machine Intelligence paper on collective AI systems. His recent publications reveal a strong trend toward sustainable AI development, with multiple projects focused on reducing the energy footprint of machine learning systems. His work bridges neuroscience and AI, exploring how biological learning mechanisms can inform more adaptive artificial systems. The research spans from theoretical frameworks to practical applications in robotics, healthcare diagnostics, and edge computing. Fellow of the Higher Education Academy (FHEA) Published in Nature Machine Intelligence (2024) Lead researcher on multiple funded projects including FP7 AMARSi Regular media contributor on AI topics (BBC, The Conversation) Dr. Soltoggio actively supervises PhD students and postdoctoral researchers in the Computer Science Department, with current projects focusing on lifelong learning, neuromorphic computing, and sustainable AI. His research group collaborates with Loughborough Business School on digital decarbonization initiatives and maintains connections with international AI laboratories. The team has access to advanced computational resources including Nvidia A100 GPUs and various robotic platforms for experimental validation of their theories.

• Artificial Intelligence
• Computer Science
• Cellular Automata
• +3 more

Tom Glover is an Assistant Professor in the Department of Computer Science within the Faculty of Technology, Art and Design at Oslo Metropolitan University. His office is located at Stensberggata 29, 0170 Oslo (Office number: SG204) with contact information including mobile: +47 975 38 894 and office: +47 672 37 712. Dr. Glover's research focuses on the intersection of cellular automata, artificial intelligence, and complex systems. His work spans theoretical computer science, artificial life, and practical applications in reservoir computing and control systems. His research group is part of the Innovation, Digital Transformation and Sustainability Research groups within the Department of Computer Science. Analysis of his publications reveals a consistent focus on cellular automata as computational models, with particular emphasis on their application in reservoir computing, network dynamics, and self-organizing systems. His work demonstrates how simple computational rules can generate complex behaviors with applications across multiple domains including control systems and biologically inspired computing. As an active researcher, Glover has published in reputable venues including the International Journal of Parallel, Emergent and Distributed Systems, Complex Systems, and proceedings from the Artificial Life Conference series. His recent work (2023-2024) shows continued development in sensitivity analysis of cellular automata and network topologies.

Silvia Gomez CocaView profile

Lecturer

• molecular magnetism
• supramolecular chemistry
• molecular electronics
• +3 more

Dr. Silvia Gomez Coca serves as a Lecturer in the Department of Inorganic and Organic Chemistry at the University of Barcelona's Faculty of Chemistry, where she integrates computational and experimental methodologies to advance molecular science. Her academic foundation includes degrees from the University of Alicante and University of Barcelona. Her educational pathway comprises: Bachelor of Chemistry, University of Alicante (2007) Master's Degree in Chemistry, University of Barcelona (2010) PhD in Chemistry, University of Barcelona (2013) Research expertise spans molecular magnetism , supramolecular chemistry , and AI-driven materials design , with emphasis on single-molecule magnets for quantum computing applications. Her interdisciplinary approach bridges inorganic synthesis, theoretical modeling, and machine learning to engineer functional molecular systems. Recent publications (2015-2025) reveal a strategic evolution toward computational innovation, particularly in spin dynamics modeling and neural network applications for crystal structure prediction. This trajectory demonstrates increasing integration of artificial intelligence with traditional quantum chemistry methods. Key scientific recognitions include: FPU Fellow (Spanish Government PhD Grant, 2009-2013) Beatriu de Pinós Fellow (Catalan Government Postdoctoral Grant, 2018-2021) Juan de la Cierva Fellowship (Spanish Government Postdoctoral Grant) As Principal Investigator for AGAUR's 'Encapsulation of Mononuclear Single Molecule Magnets' (2018-2021) and co-PI for multiple national grants including 'AI for Quantum and Neuromorphic Magnetic Devices' (2022-2024), she directs significant research funding. Current projects focus on radical-metal magnetic coupling for digital technologies (2024-2026) and theoretical chemistry infrastructure development. She actively contributes to the Electronic Structure Group (GEE) and Institute of Theoretical and Computational Chemistry (IQTC), fostering collaborative research in quantum materials design and computational methodology development.

Sara AchourView profile

Assistant Professor

• Programming Languages
• Compilers
• Runtime Systems
• +2 more

Sara Achour is an Assistant Professor jointly appointed to the Computer Science and Electrical Engineering departments at Stanford University. She earned her PhD in Computer Science from MIT in 2021. Her research develops programming languages, compilers, and runtime systems for emerging analog computing platforms. Dr. Achour leads research in hardware-aware optimization frameworks and novel analog compute paradigms, with applications spanning quantum computing, IoT devices, and neuromorphic systems. Her research focuses on: Bridging software abstractions with unconventional hardware capabilities Energy-efficient computing paradigms for edge devices Cross-layer optimization of analog and hybrid computing systems Publication analysis reveals consistent themes in analog computing architectures, hardware-aware optimizations, and emerging computing platforms. Recent work explores quantum compilation techniques, hyperdimensional computing optimizations, and hardware security metrics. Dr. Achour advises multiple graduate students including: 16 doctoral candidates across computer architecture and quantum computing 10 master's students in software-hardware co-design She maintains active research collaborations through the Stanford SystemX Alliance.

Clara SantatoView profile

Professor

• Sustainable Electronics
• Organic Semiconductors
• Nanostructured Materials
• +4 more

Clara Santato is a Full Professor in the Department of Engineering Physics at Polytechnique Montréal. She holds a M.Sc. from the Università di Bologna and a Ph.D. from the University of Geneva. Her research focuses on sustainable electronics, organic semiconductors, and energy conversion materials. She leads the UNESCO Chair in Green and Sustainable Electronics and is a Tier-1 Canada Research Chair. Her work integrates bio-sourced materials like melanin and tannins into electronic devices to address environmental challenges. Education: M.Sc. in Chemistry, Università di Bologna (1995) Ph.D. in Chemistry, Université de Genève (2001) Research Interests: Sustainable electronics materials (bio-sourced, biodegradable) Charge transport in organic semiconductors Nanostructured photocatalysts for solar energy conversion Electrochemical energy storage Awards & Affiliations: UNESCO Chair in Green and Sustainable Electronics (2023) Tier-1 Canada Research Chair (2020) IEEE Senior Member (2020) Member of Microfabrication Laboratory and Material Surface Analysis (LASM) Grants & Projects: Pan-Canadian CREATE SEED program for sustainable electronics training Natural Sciences and Engineering Research Council (NSERC) funding Collaborations with industry and academic institutions worldwide Labs & Teams: Leads the Santato Research Group focusing on bio-inspired electronics and sustainable materials development.

Milad ZamaniView profile

Assistant Professor

• Integrated Circuits
• Biomedical Engineering
• Wireless Power Systems
• +3 more

Milad Zamani is a Tenure Track Assistant Professor in the Department of Electrical and Computer Engineering at Aarhus University. His research focuses on integrated circuits, biomedical engineering, and wireless power systems with applications in neural engineering and sensor systems. He leads projects such as DONUT (European Doctoral Network for Neural Prostheses and Brain Research) and CorroSense (Self-powered corrosion monitoring). His work spans topics like bio-impedance sensing for wearables, ultrasonic energy transfer for implants, and high-precision analog circuits. Recent projects include thermally-powered leakage detection systems and optogenetic implantable devices. Zamani collaborates on advanced sensor technologies, neuromorphic hardware, and biomedical device miniaturization. His lab develops low-power circuits for medical applications, combining signal processing with cutting-edge microelectronic design.

• Machine Learning
• Artificial Intelligence
• Cyber-Physical Systems
• +3 more

Felix Resch is a PreDoc Researcher at the Cyber-Physical Systems department of Vienna University of Technology (TU Wien). His work focuses on neuromorphic computing and autonomous systems. Education: BSc, Technische Universität Wien Role: Project Assistant (Projektass. Dipl.-Ing.) and PreDoc Researcher Research interests include neuromorphic sensing-processing integration and attention-based neural networks for autonomous applications. Current work involves the NimbleAI project (2022–2026) and AI-driven autonomous racing systems. Recent publications highlight trends in 3D-integrated neuromorphic chips and attention-based neural networks for autonomous systems. He is affiliated with the Cyber-Physical Systems group (E191-01) at TU Wien. Contact: felix.resch@tuwien.ac.at | Phone: +43-1-58801-18225

Cem ErsoyView profile

Professor

• Wireless Networks and Mobile Applications
• Pervasive Health
• Internet of Things
• +12 more

Cem Ersoy is a full Professor at the Department of Computer Engineering, Boğaziçi University, Istanbul, Turkey. He serves as the Vice Director of TETAM and leads the Computer Networks Research Laboratory (NetLab), driving forward research in wireless networks, pervasive health, IoT, 5G, SDN, and emerging air computing paradigms. His research spans cutting-edge domains such as air computing, edge intelligence, wearable stress monitoring, indoor localization, and smart city neurocomputing challenges. By integrating deep reinforcement learning, probabilistic modeling, and IoT systems, his work aims to create unobtrusive, scalable, and adaptive computing solutions for real-life environments. Recent publications reveal a strong focus on air computing as a novel computation paradigm, leveraging multi-agent deep learning and simulation frameworks. Another major trend is wearable-based affect and stress monitoring , where semi-supervised learning and explainable AI reduce labeling burdens while enhancing real-life applicability. Additional work addresses edge computing orchestration , network slicing , and live video streaming optimization using SDN and reinforcement learning. Prof. Ersoy actively advises graduate researchers and leads funded projects in national and international arenas, although specific grant titles and student names are not listed in the source. His lab, NetLab, provides a collaborative environment for innovations in computer networks, IoT, and pervasive health technologies.