Find Academic Supervisors

Kate MacfarlaneView profile

Senior Lecturer

• Artificial Intelligence
• Cybersecurity
• Natural Language Processing
• +7 more

Dr. Kate Macfarlane is a Senior Lecturer in Artificial Intelligence at the Department of Computing and Mathematics, Manchester Metropolitan University. Her work focuses on applying AI and automation to solve societal challenges, particularly in ensuring safe online interactions for vulnerable users. She holds a PhD in Multi-Agent Systems for Online Safety, a BSc in Computer Systems Engineering, and a PGCE. Her professional affiliations include Senior Fellow of the Higher Education Academy (SFHEA) and Member of the British Computer Society (MBCS). Research & Projects Current Project: SafeChat, developing emotion detection systems for safer online communication. Innovate UK Project: Predictive financial models for SMEs with Proforecast Ltd., rated 'Very Good' by Innovate UK. Google DNI Fund's SMART tool: Analyzing social media abuse metrics for journalists. Cyber Eyes Wide Open: Bridging cybersecurity with creative industries through collaborative projects. Technological Family Report: Exploring future technologies' impact on families and connected homes. Key Research Areas Her interdisciplinary research spans AI ethics, distributed systems, game technologies, and cybersecurity. Notable contributions include multi-agent systems for child safety online and VR adoption challenges. She frequently speaks at conferences such as the Great Northern AI Summit and Dynamo 20 Collaborating for Success. Grants & Collaborations Principal Investigator for Innovate UK's Proforecast project. Collaborations with Amazon Web Services (AWS) and Sunderland University's Creative Fuse team. Teaching & Engagement Committed to education innovation, she designs human-centered AI curricula and mentors students in applied research projects.

Bruna PetrecaView profile

Professor

• Circular Economy
• Materials Science
• Human-Centered Design
• +3 more

Dr. Bruna Petreca is a Professor and Reader in Human Experience and Materials at the Royal College of Art's Materials Science Research Centre. She specializes in integrating human experience into materials development, focusing on circular economy, digital environments, and health/wellbeing. Her research leads projects like the UKRI Textiles Circularity Centre and EPSRC Dematerialisation initiatives, emphasizing sustainable fashion, consumer behavior, and digital tools. Educated at the University of São Paulo (BA in Fashion/Textiles) and the RCA (PhD in Design Products), she has a postdoctoral background at TU Delft. Awards include 2013 Human Centred Design prizes and recognition for her work on material experience frameworks. She collaborates internationally, chairs research ethics at RCA, and co-leads projects on AI design tools and circular fashion. Her teaching spans undergraduate/postgraduate levels, emphasizing materials science, human-centered design, and sustainable practices. Education: PhD (RCA), Postdoc (TU Delft), BA (USP) Key Projects: Textiles Circularity Centre (UKRI), Consumer Experience Digital Tools (EPSRC), Brazil-UK Natural Polymers Network Awards: Best Concept/Human Centred Design (2013), Best Poster Presentation (2013) Research Themes: Circular fashion, material experience frameworks, embodied design, AR tools for sustainability

Pierre JourlinView profile

Professor

• Computer Science
• Artificial Intelligence
• Programming Languages
• +3 more

Pierre Jourlin is a Professor at Avignon University, specializing in Computer Science and Artificial Intelligence. He actively contributes to academic events such as workshops on programming education and AI ethics. His research focuses on areas like natural language processing, machine learning, and the societal impact of AI. Jourlin has organized events like a programming workshop for high school students (2022) and authored numerous articles on topics ranging from rule-based event extraction to generative AI in creative writing. His academic contributions include work on semantic disambiguation, medical literature tools (SIMI), and foundational studies in speech recognition and multimedia retrieval. He critiques AI limitations, emphasizing the importance of human oversight in code generation and advocating for accessible education to counteract underfunding in public schools. Jourlin's recent publications (2024–2025) address AI's role in creative fields and the evolution of programming languages. His work often bridges technical innovation with ethical considerations, as seen in his analysis of code-producing AI tools like Copilot. He remains an active member of the academic community, blending research with pedagogical outreach.

• Sensory Neuroscience
• Cognitive Psychology
• Neurophilosophy
• +3 more

Dr Antonio Cataldo is a Research Fellow affiliated with the Institute of Philosophy at the University of London. His research focuses on sensory neuroscience, cognitive psychology, and neurophilosophy, particularly investigating multisensory integration, perceptual processes, and the neural mechanisms underlying self-perception. His work bridges empirical research and philosophical inquiry, exploring how sensory inputs are aggregated into coherent experiences. Key research themes include the interplay between tactile and motor signals in spatial self-perception, the modulation of agency through haptic feedback, and the paradoxical interactions within somatosensory submodalities. Cataldo has contributed to understanding thermal referral illusions, pain modulation by warmth, and the salience-driven biases in tactile perception. His studies often employ experimental paradigms combining neurophysiological measures and behavioral experiments. Publications highlight his exploration of touch perception, sensorimotor integration, and clinical applications of perceptual mechanisms in conditions like depersonalization. He is actively engaged in interdisciplinary research, with affiliations including University College London (UCL) for consultancy and media collaborations. No scientific awards are explicitly listed, though his prolific publication record indicates sustained academic engagement. His research has been supported by collaborations with institutions such as UCL and international conferences like EuroHaptics.

• Speech analysis
• Experimental phonetics
• Foreign accent
• +3 more

Lya Meister is a Research Fellow at Tallinn University of Technology's School of Information Technologies, Department of Software Science. She has held this position since 2017, continuing her career from the Institute of Cybernetics at TUT where she served as a Research Fellow (2009–2016) and Extraordinary Research Fellow (2005–2008). Her academic background includes a Doctor's Degree in 2011 (University of Tartu) and a Research Master's Degree in 2005 (Tallinn University). Education: PhD: University of Tartu, 2005–2011 Master's: Tallinn Pedagogical University, Estonian Philology, 2002–2005 Bachelor's: Tallinn Pedagogical University, Russian Philology, 1975–1979 Her research focuses on experimental phonetics, speech corpora analysis, and the acoustic characteristics of speech production. Notable projects include the Improving the intelligibility of sung text (2022–2026) and contributions to the Estonian Elderly Speech Corpus. She has organized major conferences like the Phonetics Symposium 2024 and served on international committees for speech technology initiatives. Her awards include the 2023 School of Information Technologies Paper of the Year and the 2012 Best Paper Award from the Institute of Cybernetics. Her work spans over 68 publications, with recent emphasis on plosive closure duration in singing, vowel-consonant intensity ratios, and developmental phonetic changes in adolescents.

• Electronic Engineering
• Mechatronics and Robotics
• Human-Robot Interaction
• +7 more

Roya Haratian serves as Principal Academic (equivalent to Associate Professor) in Electronic Science and Engineering at Bournemouth University's Department of Design and Engineering within the Faculty of Science and Technology. As Deputy Head of Department and Athena SWAN lead, she spearheaded the department's successful Bronze Award in 2021 for gender equality initiatives. Her leadership extends to curriculum development in Mechatronics and Robotics programs across undergraduate and postgraduate levels. Her academic credentials include a BSc (First Class Honours) and MSc (Distinction) in Electrical and Electronic Engineering, followed by a PhD in Electronic Engineering from Queen Mary University of London (2014). Prior to her current role, she worked as an Associate Lecturer at QMUL and Research Associate at Bristol Robotics Lab, focusing on on-body sensing systems and bio-signal processing for human-machine collaboration. Haratian's research centers on electronic engineering applications in human-robot interaction, with particular emphasis on on-body sensing technologies, signal processing, and machine learning. Her work bridges theoretical innovation with industrial implementation, developing assistive technologies for healthcare and safety-critical systems. Recent projects address diabetic foot ulcer prevention, emotion recognition in VR, and human-machine collaboration safety protocols, demonstrating strong translational impact across medical and industrial domains. Analysis of her 15 most recent publications reveals a strategic progression from foundational signal processing techniques toward integrated human-machine systems. Her work increasingly incorporates game theory for resource allocation, AI-driven predictive modeling, and inclusive design principles, with growing emphasis on real-world implementation challenges and ethical considerations in assistive technologies. Key recognitions include: Athena SWAN Bronze Award (Advance HE, 2021) for departmental gender equality leadership Senior Fellowship of Higher Education Academy (2021) BU Doctoral College Outstanding Contribution Award (2025) Design Review Award from Institute of Mechanical Engineering (2023) Student Experience 'You are Brilliant' Award (2017) As Recognised Research Supervisor (UK Council for Graduate Education), she currently co-supervises five PhD students on topics including AI surveillance, biomechatronics, and digital twin simulation. Her £1.2M+ research portfolio features strategic partnerships with Zimmer-Biomet, Computational Mechanics Wessex Institute, and Daido Industrial Bearing, with recent grants including HEIF-funded AI emotion recognition systems (2025) and QR-funded human-machine safety protocols (2024). She actively mentors through AdvanceHE's Aurora program and leads BU's Inclusivity Curriculum Evaluation project. Haratian directs the department's Athena SWAN initiative and collaborates with the Royal Institute on STEM outreach, designing bioelectronic masterclasses for GCSE students. Her public engagement includes 'Café Scientifique' discussions on machine emotion recognition and keynote addresses at Brockenhurst STEM Awards, focusing on translating on-body sensing research into real-world health applications.

Lei XieView profile

Professor

• Bioinformatics
• Systems Biology
• Molecular Modeling and Simulation
• +6 more

Lei Xie is a Professor in the Department of Computer Science at Hunter College, CUNY, and an Adjunct Professor in Neuroscience at Weill Cornell Medicine, Cornell University. He holds a PhD in Chemistry from Rutgers University (2000) and an MS in Computer Science from Rutgers (2000), alongside a BS in Polymer Physics from the University of Science and Technology of China (1995). His research focuses on integrating artificial intelligence and machine learning with biomedicine to address challenges in drug discovery, systems biology, and personalized medicine. Research Highlights: Developing novel machine learning algorithms for signed networks, high-dimensional data, and generative AI for drug design. Structural systems pharmacology frameworks for drug action modeling, targeting Alzheimer’s, cancers, and bacterial infections. Multi-scale modeling combining molecular dynamics and machine learning for drug-target interactions. Grants: NIH (R01GM122845, R01AG057555, R21AG083302) and NSF (NSF2230354) funded projects on methodology development and translational sciences. Labs & Collaborations: Leads the Brain & Mind Research Institute lab at Weill Cornell, collaborating with researchers at UVA, Rutgers, and other institutions on projects like Alzheimer’s drug repurposing and anti-cancer therapies.

• Human-Computer Interaction (HCI)
• Multimodal Interaction
• Visual Analytics
• +5 more

Denis Lalanne is a full Professor in the Department of Informatics at the University of Fribourg, leading the 'human-building interaction' group at the Smart Living Lab and directing the Human-IST institute . He specializes in Human-Computer Interaction (HCI), focusing on multimodal interaction, visual analytics, and Human-Building Interaction (HBI). His work bridges computer science with architecture and urban design to improve building occupants' comfort and accessibility. His research spans topics such as assistive technologies for visually impaired individuals, energy-efficient lighting systems, and predictive models for indoor environmental quality. He has led projects like the Human-IST Lab and SWICE (Sustainable Well-being in Energy Transition), emphasizing interdisciplinary collaboration between academia, industry, and public institutions. Key contributions include the development of frameworks for human-centric lighting, wearable sensors for urban comfort analysis, and empathic systems to enhance HCI. His work is published in top venues like ACM Transactions on Accessible Computing , IEEE , and CHI . Education and career highlights include a PhD from EPFL (Swiss Federal Institute of Technology), postdoctoral research at IBM’s USER Group, and prior teaching roles at the University of Avignon. He is a Swiss representative at IFIP TC13 and has organized major conferences like IHM 2016.

Christos DiouView profile

Associate Professor

• Machine Learning
• Artificial Intelligence
• Healthcare Applications
• +3 more

Christos Diou is an Associate Professor of Artificial Intelligence and Machine Learning at the Department of Informatics and Telematics, Harokopio University of Athens, Greece. His academic career spans over 15 years of participation in national and international research projects, with a focus on machine learning algorithms, domain generalization, causal inference, and bias mitigation. He earned a BSc and Ph.D. in Electrical and Computer Engineering from Aristotle University of Thessaloniki. His research emphasizes the application of machine learning to healthcare, addressing challenges such as visual bias mitigation, causal effect estimation from observational data, and fairness-aware representation learning. Notable projects include REBECCA and RELEVIUM , both EU-funded, and MELIORA , targeting lifestyle interventions for breast cancer risk reduction. He has published extensively in top-tier venues like IEEE TPAMI, CVPR, and ICCV. Christos is a leading voice in AI ethics and healthcare innovation, with over 150 publications and best paper awards at IEEE Big Data Service 2023 and AIAI 2022. His work includes developing platforms like Effector for feature effects and Beam for behavior studies. He collaborates with institutions such as Karolinska Institutet and CERTH/ITI, and his students include PhD candidates Ioannis Sarridis and Aristotelis Ballas.

Huaxia WangView profile

Assistant Professor

• Wireless Communications
• Deep Learning
• Robotics
• +6 more

Huaxia Wang is an Assistant Professor in the Department of Electrical & Computer Engineering at Rowan University, part of the Henry M. Rowan College of Engineering. He holds a Ph.D. in Electrical Engineering from Stevens Institute of Technology (2018) and previously served as an Assistant Professor at Oklahoma State University (2020–2023). His research focuses on deep reinforcement learning, adversarial networks, meta-learning, graph neural networks, robotic control, and wireless communications. Education: Ph.D., Electrical Engineering, Stevens Institute of Technology (2018) M.S., Electrical Engineering, Stevens Institute of Technology (2014) B.S., Information Engineering, Southeast University, China (2012) Research interests include distributed control in wireless communications, robotic arm control in virtual environments, and multimodal learning for visual inspection. Recent work emphasizes applications in healthcare (e.g., lung ultrasound scoring) and infrastructure monitoring (e.g., concrete defect classification). Scientific Awards: Charles Kao Best Paper Award (2024) Grants/Projects: $100K from AeroDefense (2025–2026) $500K from the Department of Energy (2023–2025) $250K from the Institute for Advanced Engineering, Korea (2022–2027) His work integrates AI-driven solutions for robotics, communications, and healthcare, with a focus on practical applications such as remote robotic control and robust signal processing.

• Machine Learning
• Computer Science
• Medical Informatics
• +7 more

Yan Li is a researcher with extensive contributions across interdisciplinary domains including Machine Learning , Signal Processing , and Environmental Science . Affiliated with institutions such as the University of Southern Queensland , Hebei University , and Shandong University , Li's work spans applications in Medical Informatics , Remote Sensing , and Operations Research . Recent publications highlight expertise in Deep Learning (e.g., hyperspectral classification, image fusion), Stochastic Modeling (e.g., chemotaxis models), and Federated Learning (e.g., vertical federated fuzzy clustering). Collaborative projects include 3D Reconstruction , Smart Grid Security , and Landslide Monitoring using satellite data. Li's 2025 work demonstrates a focus on Medical Imaging (segmentation algorithms with dual-frequency decoupling), AI in Education (ChatGPT adoption), and Industrial IoT (GPU-accelerated vessel trajectory visualization). While no explicit academic rank is provided, their prolific publication record suggests a Researcher role.

• Speech Recognition
• Natural Language Processing
• Machine Learning
• +3 more

Tien Ping Tan is an experienced researcher specializing in speech recognition , natural language processing , and machine learning applications. With a PhD in Automatic Speech Recognition for Non-Native Speakers from Joseph Fourier University (2008), his career spans two decades of impactful contributions across multiple domains.

Yaqub JonmohamadiView profile

Researcher

• Computer Vision
• Deep Learning
• Multimodal Data Fusion
• +3 more

Yaqub Jonmohamadi is a former Associate Investigator at the QUT Centre for Robotics. He holds a PhD in neuroimaging and has conducted postdoctoral research since 2015 in computer vision, biomedical engineering, and neuroimaging. His research interests span computer vision, deep learning, multimodal data fusion, and signal processing. He has contributed to advancements in medical imaging, robotic surgery, and neuroimaging through interdisciplinary collaborations. His work includes 3D semantic mapping for surgical robotics, illumination control in arthroscopy, and EEG-fMRI data fusion techniques. Publications focus on applying machine learning and computer vision to healthcare challenges, such as surgical scene restoration and knee arthroscopy segmentation. His research demonstrates expertise in both theoretical and applied aspects of robotics and biomedical engineering. Jonmohamadi’s GitHub repository hosts code related to his projects, reflecting a commitment to open science. He has collaborated with institutions like Elsevier and Springer on works advancing robotic surgery and medical imaging. Despite no listed awards, his academic contributions are evident through his peer-reviewed publications and technical innovations in medical robotics. His work bridges computer science and healthcare, addressing real-world surgical and diagnostic challenges.

Eric R. FossumView profile

Professor

• Solid-State Image Sensors
• CMOS Active Pixel Sensors
• Quanta Image Sensors
• +4 more

Eric R. Fossum is the John H. Krehbiel Sr. Professor for Emerging Technologies at the Thayer School of Engineering at Dartmouth College. He serves as Vice Provost for Entrepreneurship and Technology Transfer and Director of Dartmouth's PhD Innovation Program. As one of the world's leading experts in solid-state image sensors, he invented the CMOS active pixel sensor technology that revolutionized digital imaging in smartphones, medical devices, and automotive systems. His work has earned him numerous accolades, including the National Medal of Technology and Innovation (2025) and the Queen Elizabeth Prize (2017). His research interests focus on: Solid-state image sensors (CCDs, CMOS active pixel sensors, Quanta Image Sensors) Advanced imaging systems and on-chip processing New applications for image sensors in medicine, security, and space Dr. Fossum's recent publications demonstrate significant advancements in: Photon-counting sensors for low-light applications High-speed imaging for microscopy and radiography Backside-illuminated and sub-diffraction-limit pixel designs Quantum random number generation using sensor technology Infrared spectral extension of CMOS sensors His scientific awards include: National Medal of Technology and Innovation (2025) Queen Elizabeth Prize for Engineering (2017) IEEE Andrew S. Grove Award (2009) Induction into National Inventors Hall of Fame (2011) Emmy Award for Technology & Engineering (2021) Doctor of Science, Honoris Causa from Trinity College (2014) As an entrepreneurial leader, Dr. Fossum has: Co-founded Gigajot Technology with former PhD students Previously led Photobit and Siimpel Corporations Active participant in technology transfer initiatives at Dartmouth Founder and Past President of the International Image Sensor Society

Elmar RueckertView profile

Professor

• Cyber-Physical Systems
• Robotics
• Machine Learning
• +9 more

Prof. Elmar Rueckert is the Chair of the Cyber-Physical-Systems Institute at Montanuniversität Leoben in Austria since March 2021. He holds a PhD in Computer Science from TU Graz (2014) and previously served as a Senior Researcher at TU Darmstadt (2014–2018) and Assistant Professor at the University of Lübeck (2018–2021). His research focuses on Cyber-Physical Systems, Robotics, Machine Learning, and Human Motor Control, with applications in industrial automation, healthcare robotics, and environmental sustainability. Key research interests include stochastic machine/deep learning, reinforcement learning, brain-computer interfaces, and tactile learning. His work bridges robotics, neuroscience, and AI, emphasizing practical applications such as autonomous navigation, exoskeleton control, and sensor-based recycling technologies. Rueckert has led projects like the AI Robot Lab funded by Robert Bosch Stiftung and the KIRAMET recycling initiative. Recent publications highlight advancements in neural networks for industrial condition monitoring, multimodal robotic learning, and environmental infrastructure modeling. Awards include the German Young Researcher Award (2019) and the Advanced Robotics Best Paper Award (2018). Rueckert advises a team of researchers, including notable students like Daniel Tanneberg (PhD graduate, 2019) and Linus Nwankwo (best student paper winner, 2023). His lab develops open-source tools like ROMR and collaborates on datasets like EnvoDat for robotic spatial reasoning.