Find Academic Supervisors

Margaret LechView profile

Professor

• Machine Learning
• Signal Processing
• Speech Processing
• +3 more

Professor Margaret Lech holds a position as Discipline Leader in the Department of Electrical & Electronic Engineering at RMIT University's School of Engineering. She has been at RMIT since 1998, progressing from a Research Fellow to her current role as Professor. Her expertise spans machine learning, signal processing, speech and image processing, and biomedical applications. Education: MSc in Physics from the University of Maria Curie-Sklodowska (Poland), PhD in Electrical Engineering from the University of Melbourne. Research highlights include groundbreaking emotion detection from speech signals, clinical depression analysis, and conversational trust modeling. She has co-authored over 160 papers and holds an international patent for her work on emotion detection. Awards: Telstra Innovation Challenge 2010, Vice-Chancellor's Research Supervision Excellence Award (2013), RMIT Award for Excellence in Graduate Research (2019). Grants: VPAC, ARC Linkage, DSI, AOARD, DSTG, and current co-investigator on Office of National Intelligence and ARC Discovery grants. Her research focuses on applications of AI and machine learning in healthcare, cybersecurity (e.g., Smart Grids), robotics (multi-agent systems), and fine art analysis. She has supervised over 30 PhD students and pioneered techniques in real-time speech emotion recognition and sleep stage classification. Labs/Teams: Leads interdisciplinary teams working on neuromorphic sensing, neural network systems, and computational inference of social signals. Active in collaborative projects involving industry and international partners.

• Applied Artificial Intelligence (AI)
• Computer Vision
• Disaster Management
• +4 more

Dr. Umair Iqbal is a Researcher in the School of Engineering at the University of Newcastle, specializing in Applied Artificial Intelligence (AI) with a focus on Computer Vision and Edge-Computing solutions for real-world challenges like disaster management and water resource optimization. He holds a PhD from the University of Wollongong and is an NVIDIA DLI Ambassador, delivering workshops on deep learning and AIoT technologies. His research emphasizes AI-driven video analytics for infrastructure monitoring (e.g., culvert blockage detection), public safety (e.g., violence detection in transit systems), and environmental applications (e.g., flood risk mitigation). His work combines interdisciplinary approaches, leveraging tools like TensorFlow, NVIDIA frameworks, and edge devices (Jetson platforms). Key contributions include developing an AIoT solution for pipeline protection, a real-time edge-computing system for public transport safety, and bibliometric reviews on drones and computer vision in flood management. Dr. Iqbal has secured $114,814 in grants, including a 2023 project on floodborne debris identification and a 2025 initiative for kerbside waste management. He actively supervises graduate students and leads projects like StopBlock (culvert blockage detection) and iMOVE (transport safety analytics). Research interests span AIoT frameworks, generative AI, and geotechnical applications. His publications (23+ journal articles, 3 conference papers, 2 book chapters) address hydraulic infrastructure resilience, machine learning in civil engineering, and disaster response technologies. He collaborates with industry partners like Remondis and fosters innovation through workshops and course coordination at undergraduate/postgraduate levels.

Won-Jae YiView profile

Academic

• Internet of Things (IoT)
• Wireless Body Sensor Networks
• Wearable Devices for Health Monitoring
• +7 more

Won-Jae Yi is an Associate Teaching Professor of Electrical and Computer Engineering at the Illinois Institute of Technology (Illinois Tech), part of the Armour College of Engineering. He holds a B.S., M.S., and Ph.D. in Computer Engineering from Illinois Tech, completed in 2010, 2012, and 2017, respectively. In addition to his teaching role, Yi serves as the Undergraduate Laboratory and Computing Facilities Supervisor in the Department of Electrical and Computer Engineering. He has over 13 years of experience in research focusing on IoT, wireless sensor networks, wearable devices for health monitoring, FPGAs, cyber-physical systems, and edge computing. Education: B.S. in Computer Engineering (cum laude, 2010), Illinois Tech M.S. in Computer Engineering (2012), Illinois Tech Ph.D. in Computer Engineering (2017), Illinois Tech Research Interests: Yi’s work spans IoT-enabled systems, AI-driven smart devices, cybersecurity for embedded systems, and assistive technologies for visually impaired individuals. His research emphasizes practical applications such as smart home automation, wearable health monitoring, and real-time data fusion for IoT systems. He consistently integrates his expertise in hardware-software co-design, including FPGAs and SoCs, to create robust, low-power solutions. Teaching Contributions: Yi teaches undergraduate and graduate courses in Software Engineering, Internet of Things, Cybersecurity, and Artificial Intelligence. His teaching excellence was recognized with the 2023 Bauer Family Excellence in Undergraduate Teaching Award. Labs and Facilities: As Laboratory Supervisor, Yi manages computing facilities and oversees the development of experimental setups for student projects in IoT, embedded systems, and AI. His lab focuses on prototyping smart systems that bridge theoretical concepts with real-world applications.

Antonio ServettiView profile

Assistant Professor

• Speech and Audio Processing
• Multimedia Communications
• Real-Time Multimedia Network Protocols
• +7 more

Antonio Servetti is an Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy, where he has been a faculty member since 2007. He is affiliated with the Internet Media Group (IMG) and the Interdepartmental Center PIC4SeR for Service Robotics. His work bridges multimedia processing, network communications, and web technologies. MS in Computer Engineering, Politecnico di Torino, 1999 PhD in Computer Engineering, Politecnico di Torino, 2004 Visiting Scholar, University of California, Santa Barbara, 2003 His research focuses on speech and audio processing , multimedia communications over wired and wireless networks , and real-time web-based multimedia applications . Key interests include WebRTC, Web Audio, HTTP adaptive streaming, and perceptual quality assessment. He has contributed to the development of secure multimedia transmission techniques, including selective encryption of speech and audio. The recent publications highlight a strong trend toward AI-driven modeling of subjective quality in multimedia, especially through deep learning for image and video quality prediction, understanding observer behavior, and remote music performance systems. His work often involves collaboration with researchers in the VQEG JEG-Hybrid group and the NEXA Center. Best Paper Award, Web Audio Conference 2021 Dr. Servetti has led and contributed to several research projects, including BRIC-2024 (acoustics in educational settings), PNRR HiFiReM (remote music education), and INAR (artistic research). He teaches courses such as 'Web Applications', 'Machine Learning for Vision and Multimedia', and 'Digital Audio Processing' across various engineering programs. He is also involved in educational governance as a member of academic councils for multiple degree programs. He is a core member of the Internet Media Group (IMG) , which focuses on multimedia processing and transmission, and contributes to the VQEG JEG-Hybrid working group on video quality assessment, where he develops frameworks for reproducible research and modeling of human perception.

Ivan SmirnovView profile

Assistant Professor

• Computational Social Science
• Generative AI
• Artificial Intelligence
• +10 more

Ivan Smirnov is a computational social scientist currently serving as the AI Lead in Research and Researcher Training at the Graduate Research School, University of Technology Sydney (UTS). He is also an External Faculty Member at the Complexity Science Hub in Vienna. His work spans the intersection of AI, sociology, and education, with a focus on Generative AI's role in research and doctoral training. University: University of Technology Sydney School: Graduate Research School Previous Positions: Assistant Professor, University of Mannheim; Group Leader, Higher School of Economics, Moscow Smirnov’s research explores how digital traces and machine learning can illuminate social dynamics such as inequality, gender bias, and academic performance. He employs computational methods to study topics like online toxicity, student wellbeing, and the digital representation of gender. His methodological expertise includes natural language processing, social network analysis, and predictive modeling using social media data. His recent publications reveal a consistent trend in using large-scale digital data to address pressing social questions, particularly in education and mental health. He frequently publishes in leading interdisciplinary journals such as Proceedings of the National Academy of Sciences , EPJ Data Science , and Royal Society Open Science , and presents at major conferences including IC2S2 and ICWSM. His scientific contributions have been recognized through media coverage in Nature , MIT Technology Review , and The Times , as well as a Best Course Award at HSE for his pioneering teaching in computational social science. Best Course Award at Higher School of Economics Media features in Nature, MIT Technology Review, The Times, ABC TV Smirnov is actively involved in research leadership and training, having led AI initiatives at UTS and co-organized the Summer Institute in Computational Social Science. He has secured funding from the European Commission and the Russian Science Foundation. He supervises research students and has developed the open educational course Getting Started with Generative AI in Research , reflecting his commitment to empowering the next generation of researchers. He also contributes to the academic community through peer review for top conferences and journals. He is affiliated with professional groups including the Human-AI Collaborative Knowledgebase for Education and Research (HACKER) and the SDG Classification Expert Group, and leads initiatives focused on integrating AI into research training and supporting HDR student wellbeing.

• Robotics
• Mechatronics
• Control Theory
• +4 more

Péter Korondi is a Professor at the University of Debrecen in Hungary, affiliated with the Department of Electrical Engineering and Mechatronics . His work spans robotics, control theory, and industrial automation, with a focus on bio-inspired systems and human-robot interaction. Research Interests : Robotics, Mechatronics, Control Theory, Human-Robot Interaction, Industrial Automation, Sensor Fusion Recent Article Trends : Sliding mode control, friction compensation in micro-telemanipulation, path planning for mobile robots, smart industrial systems Collaborations : Co-authored works with Gabor Sziebig, Ferenc Tajti, Géza Szayer, and international researchers in IEEE Transactions , Sensors , and Acta Polytechnica Hungarica . Technological Focus : Development of rehabilitation devices, holonomic drive systems, and ethorobotics models inspired by animal behavior.

• Biomedical Engineering
• Medical Devices
• Sensor Technology
• +5 more

Mustafa GEÇİN is a Lecturer at the Faculty of Engineering and Natural Sciences of Suleyman Demirel University, affiliated with the Department of Electrical and Electronics Engineering . He holds a PhD in Electronics and Communications Engineering (2022) from the same institution. His academic career includes roles as a Research Assistant since 2016 and contributions to multiple interdisciplinary projects. Education: Bachelor's in Electronics and Communications Engineering (2013) Master's in Electronics and Communications Engineering (2015) Doctorate in Electronics and Communications Engineering (2022) Research Interests: Development of precision measurement systems for healthcare applications (e.g., postural disorder diagnosis) 3D-printed sensor technologies for industrial monitoring (e.g., water level detection in PVC pipes) Electromagnetic field analysis in clinical and traffic safety environments Publications: His work includes peer-reviewed articles in SCI-Expanded journals focusing on biomedical engineering and telecommunications. Notable contributions include advancements in wound healing via electromagnetic fields and microwave sensor design. Projects: "Precision Measurement Technologies for Postural Disorders" (2018–2022) "Water Level Detection Systems Using 3D-Printed Sensors" (2018–2021) Grants and Awards: Supported by national research grants from universities and public institutions. Currently maintains an H-index of 3 with 21 citations (Google Scholar).

Karon MacLeanView profile

Professor

• Haptic Interfaces
• Human-Computer Interaction (HCI)
• Multisensory Interaction
• +6 more

Karon MacLean is a Professor of Computer Science and Director of the SPIN (Sensory Perception and Interaction Research Group) at the University of British Columbia. She joined UBC in 2000 after working at Interval Research Corp. in Palo Alto. Her research focuses on restoring physicality to human-computer interaction through haptic interfaces, multisensory interaction, and affective communication. She holds a Bachelor's degree from Stanford University and graduate degrees from MIT. Her work emphasizes application-driven design, exploring haptic feedback in robotics, embedded systems, and healthcare contexts. Current projects include developing Calmer, a robotic device for preterm infant pain management, and CuddleBits, affective robot pets. She leads the SPIN Lab, which investigates haptic languages, low-power interfaces, and evaluation techniques for tangible computing. Her academic contributions span over two decades, with key areas including physical user interfaces, parasitic power systems, and the integration of haptics into medical and everyday technologies. She advises students on HCI topics and collaborates internationally on projects that merge engineering, psychology, and design.

• Quantum Physics
• Atom Interferometry
• Quantum Technology
• +4 more

Sir Peter Knight is a Visiting Professor in the Department of Physics within the Faculty of Science at the University of Strathclyde, United Kingdom. He is actively engaged in advanced research in quantum technologies, particularly in the domain of atom interferometry and precision measurement systems. His research focuses on quantum physics , atom interferometry , and quantum sensing , with significant contributions to large-scale interferometric systems for fundamental physics exploration. His work intersects with material science and advanced instrumentation, aiming to push the boundaries of measurement precision and test foundational physical theories. The recent publication trend highlights a strong emphasis on collaborative, large-scale projects in terrestrial very-long-baseline atom interferometry , indicating a focus on next-generation quantum sensors for gravitational and inertial measurements. These efforts are part of an international effort to develop quantum technologies for fundamental and applied science. While no scientific awards are listed in the provided text, his involvement as a co-author in high-impact collaborative reviews underscores his respected position in the global quantum research community. Peter Knight has contributed to research advising and collaborative networks, though specific students or grant details are not mentioned. His work is embedded within extensive international research collaborations, particularly in the development of advanced quantum interferometers and their applications in fundamental physics and sensing. He is affiliated with a dynamic research environment in quantum technology at the University of Strathclyde, participating in a broad network of experts working on atom interferometry and quantum measurement systems, as reflected in the large multi-institutional authorship of his recent work.

Jaafar AlghazoView profile

Associate Professor

• Machine Learning
• Deep Learning
• Medical Image Analysis
• +7 more

Dr. Jaafar Alghazo is an Associate Professor in the Math, Science and Technology Department at the University of Minnesota. He currently teaches courses in Information Technology Management and Software Engineering, including ITM 3900-E90: Internship, SE 2200-001: Intro to Software Engineering, and SE 4500-001: Senior Project I. Research Focus: Machine Learning, Deep Learning, Medical Image Analysis, Cybersecurity, IoT, UAV Communications Key Publication Trends: 15 most recent works span 2025–2023, emphasizing neural network optimization, Arabic sign language recognition, flood detection, and secure medical imaging techniques

Hrushikesh MhaskarView profile

Research Professor

• Approximation Theory
• Computational Harmonic Analysis
• Machine Learning
• +3 more

Hrushikesh Mhaskar is a Research Professor of Mathematics at Claremont Graduate University (CGU) since 2012, with a prior 32-year tenure at California State University, Los Angeles. He holds a PhD in Mathematics from Ohio State University, alongside an MS in Computer Science and an MSc from the Indian Institute of Technology, Mumbai. His research focuses on approximation theory, computational harmonic analysis, machine learning, and signal processing, with significant contributions to neural network theory and kernel-based methods. Mhaskar has authored over 150 papers, two books, and five edited volumes. His work includes pioneering studies on weighted polynomial approximation, Fourier domain conversions, and manifold learning. He currently serves on editorial boards for journals like Applied and Computational Harmonic Analysis and Journal of Approximation Theory , and collaborates with institutions like the University of California, Santa Barbara. Awards include five Alexander von Humboldt Fellowships and a John von Neumann Distinguished Professorship. His research is supported by the NSF and previously by the U.S. Air Force and intelligence agencies. Notable contributions include developing eignets for function approximation on manifolds and analyzing deep vs. shallow networks' approximation capabilities. His work bridges theoretical mathematics with practical applications in biomedical data analysis (e.g., blood glucose prediction) and signal processing.

Diana Pamela Moya OsorioView profile

Associate Professor

• Wireless Communications
• Signal Processing for Wireless Communications
• Physical Layer Security
• +7 more

Diana Pamela Moya Osorio is Associate Professor at the Communication Systems Division, Department of Electrical Engineering, Linköping University, Sweden, and an ELLIIT recruited faculty. She previously held positions as Senior Research Fellow and Adjunct Professor at the Centre for Wireless Communications, University of Oulu, Finland, and Assistant Professor at the Federal University of São Carlos, Brazil. Education: B.Sc. in Electronics and Telecommunications Engineering, Armed Forces University, Ecuador (2008) M.Sc. in Electrical Engineering (Telecommunications and Telematics), University of Campinas, Brazil (2011) D.Sc. in Electrical Engineering (Telecommunications and Telematics), University of Campinas, Brazil (2015) Her research focuses on wireless communications , particularly signal processing for wireless systems , physical layer security , and integrated sensing and communications (ISAC) . These areas are central to the development of secure and efficient 6G networks. She investigates how wireless signals can be leveraged for both communication and environmental sensing, enhancing network intelligence and security through physical layer techniques. Her recent publications explore advanced topics such as fluid antenna systems , bistatic backscatter communication , beamforming design , and radio-over-fiber propagation . These works reflect a strong trend toward energy-efficient, secure, and high-resolution wireless systems, aligning closely with the goals of next-generation 6G networks. The integration of sensing and communication functionalities is a recurring theme, indicating a forward-looking research agenda focused on dual-use technologies. Scientific Service and Recognition: Associate Editor, IEEE Wireless Communications Letters Associate Editor, IEEE Communications Letters Associate Editor, IEEE Transactions on Information Forensics & Security Working Group Leader, Trustworthy 6G, Cost Action 6G-PHYSEC Diana Moya Osorio actively mentors PhD students and leads significant research initiatives. She is Principal Investigator (PI) for projects including HIGH-SENSE (ELLIIT), ALERT (WASP), and CO-ISAC (Vinnova), and holds leadership roles in 6GTANDEM (HORIZON-JU). Her grants are funded by major national and international agencies, reflecting the high impact and competitiveness of her work. As main supervisor, she advises Henrik Åkesson and Palatip Jopanya; as co-supervisor, she supports Ahmet Kaplan and Dexin Kong. She contributes to academic education by teaching graduate courses such as Information and Communications Engineering , Sensor Array Systems , and a PhD course on Modern Radar Systems . Her lab and research group are embedded within the Communication Systems Division at Linköping University, focusing on next-generation wireless technologies, particularly in the context of 6G and ISAC systems.

• Wireless Systems and Networks
• Internet of Things (IoT)
• Digital Twin
• +9 more

Luciano Bononi is a Full Professor and Deputy Head of the Department of Computer Science and Engineering at the University of Bologna. He holds a PhD in Computer Science (2002) and has been active in academia since 2001, progressing through roles like Researcher, Senior Researcher, Associate Professor (2011), and Full Professor (2020). His research focuses on Wireless Systems, IoT, Digital Twins, Smart Cities, and Mobile Applications , with over 160 peer-reviewed publications and major contributions to EU projects like Arrowhead and IoE. Education: MS (Laurea) in Computer Science, University of Bologna (1997, Summa cum Laude) PhD in Computer Science, University of Bologna (2002) Research Interests: Bononi's work spans Wireless Protocols, IoT Platforms, Digital Twin Integration with AI, Smart Mobility/ Energy Systems, and Edge Computing . He leads the WiLMA Lab and the ALMA-AI CoInnovation Lab , focusing on real-world IoT deployments and smart city solutions. Key Contributions: Coordinated EU projects like Arrowhead (2013-2017) and national initiatives like PNRR-Mobility-Spoke 7 Recipient of 4 Best Paper Awards and top rankings in global scientist databases Editorial roles at 7 journals including Wiley's Wireless Communications and Elsevier's Ad Hoc Networks Organized over 15 international conferences as Chair and participated in 200+ TPC roles Labs & Teams: Directs the WiLMA Lab (Wireless Systems and Mobile Apps) and the ALMA-AI CoInnovation Lab , emphasizing interdisciplinary collaboration between academia and industry.

Andrea M. TonelloView profile

Professor

• Power Line Communications
• Wireless Communications
• Embedded Communication Systems
• +12 more

Andrea M. Tonello is a Full Professor at the Institute of Networked and Embedded Systems, University of Klagenfurt, Austria, where he chairs the Embedded Communication Systems Lab. He previously held positions at the University of Udine, Italy, where he was an Associate Professor and founded the Wireless and Power Line Communication Lab (WiPLi Lab). His research spans power line communications, wireless systems, embedded communications, smart grids, and machine learning applications in signal processing. Doctor of Engineering, University of Padova (1996) Doctor of Research, Telecommunications, University of Padova (2003) His research interests focus on next-generation communication systems, including power line and wireless networks, signal processing, machine learning for communications, UAV systems, and smart grid technologies. He has made significant contributions to PLC channel modeling, full-duplex communications, and information-theoretic learning for communication systems. His work integrates theoretical innovation with practical implementation in real-world networks. The most recent publications highlight a strong trend toward integrating machine learning and information theory into communication systems, particularly in power line and wireless networks. Themes include f-divergence based classification, mutual information estimation, neural decoding (MIND), noise-robust receivers, and topology-aware machine learning for PLC quality prediction. There is also a notable focus on UAV control, full-duplex PLC, and digital pre-distortion techniques for high-speed converters. IET 2016 Premium Award Best Paper Award, ISPLC 2016 Best Student Paper Award, ISPLC 2016 Aerospace Best Paper Award, 2018 Best Paper Award, ISPLC 2021 Best PhD Dissertation Award, 2019 IEEE ComSoc Distinguished Lecturer (2018) Two Awards from IEEE ComSoc TC-PLC (2019) University of Klagenfurt Technology Scholarships (2019) Dr. Tonello has supervised numerous PhD and Master’s students, including notable advisees such as Nunzio A. Letizia, Davide Righini, and Babak Salamat. He has led over 10 institutional and multiple industrial research projects with a total funding exceeding 20 million euros. He played a key role in promoting international academic collaboration, including Erasmus agreements, joint PhD programs with INSA Rennes and Ecole Polytechnique de Grenoble, and a joint master’s program with the University of Klagenfurt. He founded and led the WiPLi Lab at the University of Udine, which received around 3 million euros in funding and involved over 60 researchers and students. He also founded WiTiKee s.r.l., a spin-off company specializing in PLC for smart grids. Currently, he chairs the Embedded Communication Systems Lab at the University of Klagenfurt, focusing on next-generation networked and embedded communication technologies.

Elias N. ZoisView profile

Associate Professor

• Digital Signal Processing
• Image Processing
• Pattern Recognition
• +4 more

Elias N. Zois is an Associate Professor in the Department of Electrical & Electronics Engineering at the University of West Attica, where he has taught since 2019. Previously, he held positions as Lecturer (since 2009), Assistant Professor (2015-2022), and Adjunct Professor at multiple institutions including the Hellenic Army Academy and Hellenic Police Academy. He received his B.Sc. (1994), M.Sc. (1997), and Ph.D. (2000) in Physics and Electronics Engineering from the University of Patras, Greece. His research focuses on digital signal processing , image processing , pattern recognition , and specialized applications in handwriting biometry and offline signature verification . Recent work extends to smart grid optimization , including load forecasting and non-technical loss detection using machine learning techniques. Analysis of his 15 most recent publications reveals strong interdisciplinary trends: 60% focus on advanced biometric verification using Riemannian geometry and metric learning, while 40% apply machine learning to energy systems. Key methodologies include sparse coding, manifold learning, and neural network ensembles, with consistent applications in security systems and smart grid resilience. He has led multiple funded projects including: BioControl (2021-2023): Experienced Researcher for biometric systems Ireact-NG (2018-2021): Experienced Researcher in smart grid technologies ESA SimSat Engine Enhancement (2011-2015): Theoretical Project Manager for aerospace simulations He directs research at the TELSIP Laboratory (Building Z, University of West Attica), specializing in signal processing and pattern recognition systems.