Find Academic Supervisors

• Medical Image Processing
• Remote Sensing
• Machine Learning
• +4 more

Jianwu Dang is a faculty member at Lanzhou Jiaotong University's School of Electronic and Information Engineering , with affiliations to the Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphic and Image Processing . His academic career spans multiple institutions including a PhD from Southwest Jiaotong University in 1996. Research Interests : Focused on Medical Image Processing , Remote Sensing , and Wireless Sensor Networks , his work bridges Artificial Intelligence and Transportation Engineering , particularly in railway systems. Publications : Recent articles address Edge Computing coalition structures (2023), Extended Reality in education (2023), and Deep Learning for remote sensing (2022). Collaborations : Frequently co-authors with Yangping Wang and Zhanjun Hao , contributing to journals like IEEE Internet of Things Journal and conferences such as APSIPA .

• Robotics
• Multi-robot Systems
• Control Systems
• +4 more

Lorenzo Sabattini is an Associate Professor at the Department of Engineering Sciences and Methods (DISMI) at the University of Modena and Reggio Emilia, Italy. His research focuses on multi-robot systems, decentralized estimation/control, and human-robot interaction. He holds a Ph.D. in Control Systems and Operational Research from the University of Bologna (2012), and has been a Visiting Researcher at the University of Maryland (2010). He served as a founding co-chair of the IEEE RAS Technical Committee on Multi-Robot Systems from 2014–2021. His work has been recognized with awards such as the Fabrizio Flacco Young Author Best Paper Award (2018) and the IEEE RAS Most Active Technical Committee Award (2018). Research interests include multi-robot coordination, coverage control, human-robot collaboration, and Industry 5.0 applications. Notable projects involve digital twins for operator well-being, AGV fleet management, and socially acceptable robotics. He has organized workshops at IEEE ICRA, RSS, and ERF, and serves as an Associate Editor for International Journal of Robotics Research (2023–2024) and IEEE Robotics and Automation Letters (2015–2018). Publications span topics like connectivity maintenance in robot networks, multimodal stress assessment in HRC, and resilient multi-robot systems. He actively collaborates on industrial automation projects, such as the INCLUSIVE system for adaptive HMIs and autonomous depalletizing systems. His research bridges theory and practice, addressing challenges in logistics, manufacturing, and human-centric robotics.

• Signal Processing
• Data Fusion
• Intelligent Transport Systems
• +3 more

Luis Enrique Díez Blanco is an Assistant Professor at the University of Deusto's Faculty of Engineering, affiliated with the Department of Mechanics, Design and Industrial Organization. He is a member of the 'Deusto Smart Mobility' research group, focusing on intelligent transport systems. His roles include teaching mathematics-related subjects (Calculus, Algebra, Discrete Mathematics, Statistics) across engineering programs. Education: Bachelor's in Telecommunications Engineering, University of Deusto (2005) Master's in Communications Technologies and Systems, Polytechnic University of Madrid (2012) PhD in Engineering for the Information Society and Sustainable Development, University of Deusto (2019) Research Interests: Signal processing, data fusion, and their applications in location-based services, Ambient Assisted Living, and intelligent environments. His PhD thesis, 'Pedestrian Navigation using Wrist-Worn Inertial Sensors,' earned Outstanding Cum Laude and an international recognition. Professional Experience: Researcher at DeustoTech (2014–2022) Research Support Technician at SOFTLAB, University Carlos III of Madrid (2013–2014) Senior IT Consultant at Everis (2005–2011) Publications & Projects: Co-author of 15+ journal articles and 10+ conference papers. Led or contributed to over 10 regional/national/international research projects. Reviewer for ~10 international journals. Lab & Collaborations: Active in the 'Deusto Smart Mobility' group and completed research stays at the Centro de Automática y Robótica (CAR-UPM-CSIC) and DLR's Institute of Navigation and Communications.

Glen RainsView profile

Professor

• Precision Agriculture
• Sensor Technology
• Insect Ecology
• +4 more

Glen Rains is a Professor in the Department of Entomology at the University of Georgia's College of Agricultural & Environmental Sciences (CAES). With a PhD in Agricultural Engineering from Virginia Tech (1992), he combines engineering principles with entomological research to develop advanced sensor technologies for agricultural applications. Co-Director of the USDA-funded Agrability in Georgia project Developed handheld chemical detection instruments (U.S. Patent 7,607,338) Licensed technology for biological sensing using invertebrate learning (U.S. Patent 6,919,202) His research focuses on precision agriculture , insect behavior monitoring , and plant pathogen detection . Recent work includes autonomous robotic systems for cotton harvesting, deep learning-based weed detection, and bioengineered plant volatile emissions for pest management. He also contributes to agricultural safety through extension programs targeting farm injury prevention and youth education. Key publication trends show concentration on machine learning applications in cotton phenotyping, autonomous navigation systems for agricultural robotics, and advanced spray technologies for pest control. His 2025 work includes predictive modeling for cotton development and innovative pest monitoring approaches. 2009 - 7,607,338: Handheld Chemical Monitoring Instrument 2005 - 6,919,202: Biological Sensing via Invertebrate Learning As educator, he developed the course CRSS 4010 - Principles of Sustainable Management and contributes to K-12 outreach through programs like G.I.F.T. and Student Shadowing. His laboratory in Tifton, GA, collaborates with engineers and entomologists on cutting-edge agricultural technology solutions.

• Internet of Things
• Machine Learning
• Data Security
• +4 more

Farhan Amin is a prolific researcher in computer science with a focus on Internet of Things (IoT) technologies, data security, and smart systems. He has published extensively in high-impact journals like IEEE Access and PeerJ Comput. Sci., collaborating with international experts such as Rashid Abbasi and Gyu Sang Choi. His work spans domains including smart city analytics, medical data protection, and next-generation IoT frameworks. Key Contributions: Dynamic trust management in IoT, 3D arthritis detection models, and hybrid data watermarking techniques. Collaborators: Rashid Abbasi, Salabat Khan, Abdul Mateen, Isabel de la Torre Díez. His research bridges theoretical innovation and practical applications, particularly in cybersecurity for IoT, network navigation, and healthcare analytics. Recent publications highlight advancements in zero-knowledge proofs, deep learning for medical imaging, and 6G-enabled healthcare systems. Farhan’s work on anticancer peptide prediction and child custody decision modeling demonstrates interdisciplinary reach. While not explicitly stated, his output suggests a faculty or senior research role at an institution engaged in cutting-edge computational science.

• Biomedical Engineering
• Medical Imaging
• Optical Coherence Tomography
• +3 more

Andrea Curatolo is an Adjunct Research Fellow at the School of Engineering, University of Western Australia, specializing in Electrical, Electronic and Computer Engineering. He holds a PhD from the same university, focusing on improving optical coherence tomography (OCT) and elastography through optical beam shaping and simulations. His research emphasizes biomedical applications, particularly in ophthalmology and cancer diagnostics, contributing to UN Sustainable Development Goals in health and innovation. Key areas include corneal biomechanics, retinal imaging, and telehealth technologies like smartphone-based optical palpation for skin and breast tissue analysis. Collaborations span global institutions, advancing non-invasive diagnostic methods. Education: PhD in Optical Imaging Technologies (UWA, 2017); BSc and MSc from Polytechnic of Milan. Research interests integrate OCT, elastography, and machine learning to address challenges in ophthalmic surgery, cancer margin assessment, and telemedicine. His work bridges engineering and clinical needs, with over 46 publications and 1503 citations, reflecting contributions to high-resolution imaging and biomechanical analysis. Recent articles highlight advancements in spatio-temporal OCT (STOC-T) for retinal hemodynamics, chirped flicker optoretinography, and cross-meridian air-puff OCT for keratoconus detection. Innovations in low-cost imaging systems and robotic tool tracking aim to democratize medical diagnostics. His lab develops handheld elastography probes and smartphone-integrated palpation tools, advancing point-of-care solutions. Awards: While no specific honors are listed, his high citation count and h-index (21) underscore peer recognition. Supervised work includes mentoring students on biomechanical and imaging projects.

Tobias KögelView profile

Researcher

• Radar Localization
• Radar Signal Processing
• Software Defined Radio
• +5 more

Tobias Kögel is a doctoral candidate and researcher at the Institute of Microwaves and Photonics (LHFT) within the Department of Electrical-Electronic-Communication Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His work focuses on advanced radar systems, signal processing, and RF technologies. Kögel holds an M.Sc. in Electrical Engineering and Information Technology (EEI) and has been actively engaged in research since 2020. His research interests span radar localization, radar signal processing in FPGAs, software-defined radio, switched injection-locked oscillators (SILOs), and UHF-RFID systems. He seeks students for projects involving hardware development, FPGA programming (VHDL/Verilog), and Python-based simulation of radar algorithms using Kalman filters. Kögel has contributed to over a dozen peer-reviewed publications since 2019, addressing topics like bistatic radar networks, time-frequency synchronization, and hybrid RFID-odometry localization. His work frequently appears in IEEE journals and conferences such as IEEE Radar Conference and International Microwave Symposium. He advises students on hardware design, FPGA implementation, and algorithm development. His lab (LHFT) focuses on microwave photonics, radar systems, and RFIC design.

• Behavioral Neuroscience
• Neuroscience
• Learning and Memory
• +3 more

Brian Smith is a Professor at Arizona State University (ASU), affiliated with the School of Life Sciences and the Center for Evolution and Medicine. His research focuses on behavioral neuroscience, particularly learning and memory systems in insects and mammals, with applications to neurodegenerative diseases like Alzheimer's and Parkinson's. He investigates how animals use olfactory cues to predict environmental events, combining behavioral studies with electrophysiological, imaging, and computational techniques. Education : Ph.D. in Neuroscience from the University of Kansas (1985). Research Interests : Smith explores how environmental contaminants (e.g., fungicides, heavy metals) impact learning and memory in pollinators like honey bees. His work bridges molecular neuroscience, behavioral ecology, and computational modeling to understand neural mechanisms underlying olfactory processing and decision-making. Grants & Collaborations : Lead or co-PI on multiple NSF, NIH, and international grants (e.g., Ideas Lab Collaborative Research on olfactory coding, NIH-funded studies on dopamine receptors in honey bees). He also collaborates on projects integrating neurotechnology (e.g., virtual odor delivery systems) and environmental policy. Labs & Teams : Directs the Social Insect Research Group, focusing on collective behavior and cognitive ecology. Active in interdisciplinary initiatives like the Interdisciplinary Graduate Program in Neuroscience at ASU.

• Artificial Intelligence
• Neural Networks
• Robotics
• +5 more

Abdullatif Baba is an Assistant Professor in the Department of Computer Engineering at Turkish Aeronautical Association University. His research focuses on interdisciplinary applications of artificial intelligence, robotics, and sustainable energy systems. He develops solutions for smart infrastructure, including AI-driven energy forecasting, autonomous drones for grid maintenance, and hyperspectral imaging techniques. His research interests span: AI/ML Systems : Neural networks, probabilistic forecasting, and FPGA-accelerated deep learning Robotics : Autonomous drones with computer vision for industrial and energy applications Sustainable Energy : Solar-based systems, smart grid optimization, and consumption prediction Security : Chaos-based cryptographic systems for secure communications Recent publications (2020-2024) demonstrate strong trends in practical AI implementations. Key themes include energy forecasting using adaptive neural networks (11 papers), robotics for infrastructure maintenance (4 papers), computer vision for biometrics and imaging (3 papers), and cryptographic systems (2 papers). Methodologies frequently involve hybrid approaches combining ANN, fuzzy logic, and hardware acceleration. No awards, students, or grant details were mentioned in the source material. Research collaborations include institutions in Turkey and the Middle East.

• Remote Sensing
• Hyperspectral Imaging
• UAV Navigation
• +3 more

Oliver Kevin Hasler is a Research Fellow at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His research focuses on developing advanced remote sensing systems with particular emphasis on hyperspectral imaging and unmanned aerial vehicle (UAV) navigation technologies. He designs lightweight sensor payloads and novel georeferencing methods for environmental monitoring applications. Hasler's research spans remote sensing, signal processing, and UAV navigation systems. His interests include hyperspectral data acquisition, robust positioning in challenging environments, coastal ocean mapping, and algal bloom detection using multi-sensor approaches. His work often involves developing cost-effective solutions for environmental monitoring applications. His publications demonstrate a consistent focus on UAV-based remote sensing innovations. Recent work shows strong trends in: hyperspectral imaging system development, signal processing for navigation resilience, coastal/ocean monitoring applications, and multi-sensor data integration. The research consistently addresses practical implementation challenges in field deployments.

Jorge DiasView profile

Professor

• Robotics
• Artificial Intelligence
• Artificial Perception
• +4 more

Jorge Dias is a Full Professor at Khalifa University (Abu Dhabi, UAE) specializing in Robotics and Artificial Intelligence, with a focus on Artificial Perception. He coordinates the Khalifa University Center of Autonomous Robotic Systems (KUCARS) and has contributed to robotics advancements since 1984. Habilitation/Doctor of Science (2011) & PhD (1994) in Electrical Engineering from University of Coimbra, Portugal His research spans Robotics for Sustainability , Computer Vision , and Social Robots , with over 300 publications. Recent work emphasizes autonomous navigation, underwater robotics, and neuromorphic computing. He has led international projects like the ECOBOTICS.sea RISE Marie Curie initiative and coordinated European consortia for elderly-inclusive robotics ("Social Robot", "GrowMeUP"). Current teaching includes courses in Algorithmic Robotics , Autonomous Systems , and Robotic Perception .

• Speech Production
• Linguistics
• Speech Therapy
• +3 more

Douglas Whalen is an Adjunct Assistant Professor in the Child Study Center at Yale School of Medicine. His research focuses on speech production, bilingualism, and the intersection of linguistics with neuroscience and clinical applications. He has contributed to studies on Mandarin Chinese phonetics, ultrasound biofeedback therapies, and the health impacts of Indigenous language revitalization. His work often employs advanced acoustic and articulatory analysis methods. Research Interests Articulatory Phonetics: Investigating tongue and lip movements during speech production using ultrasound imaging. Bilingual Speech: Examining how bilingual speakers navigate phonetic differences between languages. Speech Therapy: Developing biofeedback interventions for children with speech disorders. Language and Health: Exploring how Indigenous language use correlates with mental and physical health outcomes. Recent Work Trends Recent articles highlight Whalen's focus on vocal tract dynamics (e.g., Mandarin rhotics analysis), clinical applications of ultrasound technology, and cross-linguistic studies of perceptual integration. His 2022 review on Indigenous language revitalization underscores his interdisciplinary approach to language and societal health. Grants & Collaborations Collaborations with Haskins Laboratories and international research teams. Funding likely supports projects on speech production mechanisms and clinical interventions.

Bill S. HanssonView profile

Professor

• Neuroethology
• Olfaction
• Evolution
• +6 more

Bill S. Hansson is the Managing Director of the Max Planck Institute for Chemical Ecology (MPICE) in Jena, Germany, and Director of the Department of Evolutionary Neuroethology. Previously, he served as Professor and Head of Chemical Ecology Division at the Swedish University of Agricultural Sciences (SLU), Associate Dean at the Faculty for Landscape Planning, Horticulture and Agricultural Sciences, and held academic positions at Lund University spanning from Assistant to Associate Professor. His research focuses on the neuroethology of insect olfaction, examining its function, anatomy, and evolutionary basis. Key interests include olfactory coding, neural processing of chemical signals, and odor-dependent behaviors in model organisms like Drosophila and moths. His pioneering work includes developing calcium imaging in moth brains and demonstrating functional organization in insect olfactory systems. Hansson's extensive publication record (200+ papers) reveals consistent focus on insect sensory biology, with recent work exploring neural correlates of odor valence, deceptive pollination systems, and molecular mechanisms of odorant reception. His research integrates neurophysiology, molecular biology, and behavioral ecology approaches. Major Honors and Awards: ISCE Silverstein-Simeone Lecture Award (2014) AChemS Givaudan Lecture Award (2013) Letterstedt Prize (2009) Swedish Linnaeus Grant: €1M/year for 10 years (2006) Elected Fellow/Member of 5 national academies including Royal Swedish Academy of Sciences He leads a research department of approximately 60 members at MPICE, where he established evolutionary neuroethology as a core discipline. His team investigates olfactory modulation across evolutionary timescales using Drosophila and hawk moth models, supported by major funding including the Linnaeus Grant.

• Multi-target Tracking
• Bayesian Filtering
• Sensor Fusion
• +3 more

Professor Daniel Clark is a member of the University of Southampton's academic staff, specializing in multi-target tracking, Bayesian methods, and sensor fusion. His research focuses on advancing algorithms for aerospace systems, robotics, and statistical inference. He supervises PhD students in electronic engineering and is affiliated with the Vision, Learning and Control Centre for Robotics. His work bridges theoretical foundations with practical applications in tracking systems and cybersecurity. Recent contributions include advancements in covariance intersection, adversarial risk formulations, and sensor data fusion techniques. Research Interests: His expertise spans multi-object tracking, stochastic guidance systems, and information-theoretic bounds. He explores applications in maritime surveillance, robotics navigation, and secure algorithm design. Advising & Grants: Currently supervising Chuanhang Qiu (PhD in Electronics). His research has been published in top-tier journals like IEEE Transactions on Aerospace and Electronic Systems. Labs & Teams: Active member of the Vision, Learning and Control Centre for Robotics, contributing to interdisciplinary projects in autonomous systems and data fusion.

Spencer BalayView profile

Researcher

• Neuroscience
• Developmental Biology
• Sensory Systems
• +3 more

Spencer Balay, PhD, is a Researcher affiliated with the Keays Lab at the Faculty of Biology of Ludwig-Maximilians-Universität München. His research focuses on sensory and developmental neuroscience, particularly in photoreceptor development, retinal biology, and neurogenesis. He investigates mechanisms underlying retinal cell specification, magnetoreception, and molecular pathways in zebrafish models. His work spans topics such as cryptochrome proteins' roles in vision and navigation, genetic regulation of adult-born neurons, and retinal morphogenesis in mutants. Balay's contributions include studies on CRY2 proteins in pigeons, capicua gene regulation in hippocampal neurogenesis, and NRL's role in photoreceptor development across vertebrates. He is part of the Sensory and Developmental Neuroscience group, collaborating on projects involving zebrafish as a model organism for understanding developmental and sensory processes. His research integrates molecular biology, genetics, and systems-level analysis to address fundamental questions in neurobiology.