Find Academic Supervisors

Grzegorz ChrupałaView profile

Associate Professor

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

Grzegorz Chrupała is an Associate Professor at the Department of Cognitive Science and Artificial Intelligence , Tilburg University, where he leads research in computational approaches to multimodal communication. Previously, he was a postdoctoral researcher at Saarland University's Spoken Language Systems group and earned his PhD from Dublin City University's School of Computing. His research bridges biological and artificial computation , focusing on enabling machines to learn language from multimodal data (speech, gestures, visual-auditory stimuli) as children do naturally. This involves developing and interpreting deep learning architectures, analyzing emergent representations, and advancing speech technology for under-resourced languages. Key themes include Visually grounded speech modeling Feature attribution and model interpretability Human-inspired learning paradigms BlackboxNLP workshop leadership His recent publications examine speech model reliability , lexical tone encoding , and contextual dependencies in NLP systems. He mentors a team of PhD candidates and alumni working on topics like user-centric interpretability, bioacoustics, and disentangled speech representations. He also serves on the board of the Dutch Open Speech Technology Foundation, chairs Interspeech 2025 tutorials, and contributes as an Action Editor for TACL.

Benoît LemaireView profile

Lecturer

• Computational Cognitive Modeling
• Working Memory
• Eye Movement Research
• +6 more

Benoît Lemaire is a permanent Lecturer at the University of Grenoble Alpes, affiliated with the Laboratoire de Psychologie et NeuroCognition (LPNC) and the CoMMet team (Consciousness, Memory and MetaCognition). His academic career spans computational cognitive modeling, with a focus on working memory, eye movement research, and educational technology applications. PhD in Computer Science/AI, Université Paris-Sud (1989-1992) Postdoctoral Research: University of Pittsburgh (1993), Swedish Institute of Computer Science (1994) Academic Roles: Maître de conférences (1996-), transitioning through Laboratoire des Sciences de l'Éducation (1994-1996), Laboratoire Leibniz (2004-2006), TIMC (2006-2010), and LPNC (2010-). Lemaire’s research integrates computational modeling with empirical studies across multiple domains: Working Memory : Time-based decay, interference effects, semantic compression, and attentional refreshing mechanisms. Eye Movements : Information search in texts, reading strategies, and visual-semantic integration. Educational Applications : Text assessment, metaphor comprehension, and adaptive learning systems. Inductive Learning : MDL-based models for concept learning and lexical knowledge acquisition. His recent publications (2021–2025) emphasize computational models of mental arithmetic, semantic knowledge impacts on memory, and similarity-based compression techniques. All work aligns with cognitive science and AI methodologies. Current affiliations include: Laboratoire de Psychologie et NeuroCognition (LPNC) – 2010- CoMMet team (Consciousness, Memory and MetaCognition) University of Grenoble Alpes – Permanent Lecturer

F. Richard YuView profile

Professor

• Machine learning and artificial intelligence
• Connected and autonomous vehicles
• Blockchain and distributed ledger technology
• +2 more

F. Richard Yu is a Professor at the School of Information Technology , Carleton University , Canada, since 2016. He served as Assistant/Associate Professor at the same institution from 2006 to 2015. His academic work spans machine learning, blockchain, autonomous vehicles, and network security. Ph.D., Electrical Engineering, University of British Columbia (2003) M.A.Sc., Computer Engineering, Beijing University of Posts & Telecomm. (1998) B.A.Sc., Electrical Engineering, Dalian University of Technology (1995) His research focuses on machine learning , blockchain , autonomous vehicles , network security , and mobile wireless networks . Trends in his publications include deep reinforcement learning for computation offloading , blockchain applications in edge computing , and network optimization for IoT and 5G systems . Highly Cited Researcher (2019-2023), Clarivate Electronics and Electrical Engineering Leader in Canada (2023), Research.com Fellow of Canadian Academy of Engineering (CAE) (2021), Engineering Institute of Canada (EIC) (2019), IEEE (2017), and IET (2016) Best Paper Awards: IEEE ICC (2022), IEEE GLOBECOM (2020), IEEE VTC (2017), IEEE TAOS (2012), IEEE TrustCom (2009) Research Achievement Award, Carleton University (2021, 2012) Early Researcher Award (2011), Ontario; Leadership Opportunity Fund Award (2009), Canada Foundation for Innovation His work has resulted in 800+ papers , 30 patents , and 48,000+ citations (H-index 107), with grants including the 2009 Canada Foundation for Innovation award.

Nico PalleitView profile

Researcher

• MIMO Communication Systems
• Channel Estimation
• Signal Processing
• +3 more

Dr.-Ing. Nico Palleit is affiliated with the University of Rostock's Institute of Communications Engineering, part of the Faculty of Computer Science and Electrical Engineering. His research focuses on MIMO (Multiple-Input Multiple-Output) systems, channel estimation, and prediction techniques to enhance spectral efficiency. He holds a PhD titled Channel Prediction in Multi-Antenna Systems (2011) and has contributed to advancements in MIMO channel analysis, including frequency/time prediction and interference management. Research Interests: Nico's work addresses challenges in modern radio transmission systems, emphasizing the development of robust channel estimation strategies. Key areas include MIMO channel modeling, non-line-of-sight (NLOS) positioning, and optimizing transmitter-side channel state information. His research bridges theoretical frameworks with practical implementations in wireless communication systems. Publications Overview: His 15+ publications (2006–2012) span topics like MIMO channel prediction, antenna array design, and interference channel optimization. Recent work emphasizes frequency/time-domain channel prediction and power allocation strategies for maximizing system capacity. These contributions highlight interdisciplinary approaches combining signal processing with electrical engineering principles. Affiliations & Labs: As part of the Radio Communication Research Group, he collaborates on projects within the Institute's advanced wireless communication initiatives. His work supports next-generation radio systems through innovative solutions for MIMO-FDD and OFDM-based architectures.

• Electromagnetic Compatibility
• Computer Simulation
• Radiated Emissions
• +3 more

Kevin Fynn is an Adjunct Professor at the School of Engineering , The University of Western Australia, specializing in Electromagnetic Compatibility and Computer Simulation . His work intersects with technical domains like PCB Design and Signal Integrity , alongside broader contributions to UN Sustainable Development Goals (SDGs) for sustainable development and environmental protection. Research Interests : Modeling electromagnetic interference in microstrip and power ground planes Radiated emissions analysis in printed circuit boards Efficient simulation techniques for electromagnetic compatibility Experimental validation of shielding effectiveness in enclosures Adaptive algorithms for PCB frequency point selection Applications to SDGs like affordable clean energy and sustainable industrialization Article Trends : His publications (2002-2005) focus on electromagnetic simulation, radiated emissions, and PCB design, emphasizing methodologies for fringing effects, port termination analysis, and shielding validation. These works align with Electromagnetic Compatibility and Signal Integrity subfields. Grants : The Last Metre Problem (2005-2007): Technology diffusion research funded by NICTA. Simulation of PCB Radiated Emissions (2004): Short-term research supported by Sundry Grants. DSTO Mode Stirred Chamber Simulation (2002): Project for Defence Science and Technology Group.

• Flow in underground porous media
• Geoenergy
• Underground energy storage
• +12 more

Dario Viberti is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Environmental, Land and Infrastructure Engineering (DIATI). He is a member of the Interdepartmental Center Ec-L - Energy Center Lab and actively contributes to the Master's and Continuing Education School. He serves as Coordinator for both Master’s levels I and II of the Natural Resources Development and Storage program and participates in doctoral colleges for Civil and Environmental Engineering and Materials, Sustainable Processes, and Systems for the Transition. His research focuses on flow in underground porous media , geoenergy , and underground energy storage , particularly hydrogen and CO₂ storage. His expertise spans numerical modeling, reservoir engineering, fluid mechanics, well testing, and energy transition systems. He is involved in commercial research projects with ENI Corporate University and leads initiatives related to sustainable energy applications. His recent publications reveal a strong trend in underground hydrogen storage , biogeochemical modeling , pore-scale simulation , and PVT analysis of gas mixtures . These works emphasize safety, efficiency, and long-term integrity of subsurface storage systems using advanced computational and experimental methods. Scientific Manager, Underground CO2 Storage Project (2022) Scientific Manager, Reservoir Modeling Project (2022) Coordinator, Master’s Program in Natural Resources Development and Storage Member, SEASTAR Competence Center Committee (2020–2025) He mentors several PhD students, including Michel Tawil, Marialuna Loffredo, Alice Raeli, and Alice Massimiani, supporting research in microfluidics, Lattice Boltzmann simulations, and thermodynamic characterization. He teaches courses such as Numerical Modeling for Multiphase Flow , Underground Energy Storage , and Well Logging and Testing across multiple degree programs. His work aligns with UN SDGs 7 (Affordable and Clean Energy), 9 (Industry, Innovation, and Infrastructure), and 13 (Climate Action).

• Biomechanics
• Human Balance and Movement
• System Identification
• +7 more

Massimo Cenciarini is a Senior Lecturer in the Department of Mechanical Engineering at the Universitat Politècnica de Catalunya (UPC), affiliated with the School of Industrial Engineering (ETSEIB). He is an active member of the BIOMEC - Biomechanical Engineering Lab, TecSalut - Health Technologies Research Group, and CDEI - Industrial Equipment Design Centre. His work bridges engineering and biomedical applications, focusing on human movement and assistive technologies. Research Interests: Biomechanics and human balance Wearable robotics and exoskeletons System identification and control Assistive mobility technologies Mechatronics and simulation Postural control and motor adaptation His recent publications show a strong trend in wearable robotic devices, particularly knee exoskeletons, with emphasis on human-exoskeleton interaction, misalignment compensation, impedance identification, and gait assistance. His work integrates biomechanical modeling, experimental validation, and translational research for rehabilitation and mobility enhancement. Scientific Awards: 3r Premi UPC al Compromís Social He has participated in competitive R&D projects such as Xartec Salut and technology transfer initiatives, including the development of wearable knee exoskeletons. While no formal students are listed, his collaborative projects suggest mentorship roles within multidisciplinary teams. He is involved in research networks focused on health technologies and Industry 4.0 educational environments. Laboratories and Research Groups: BIOMEC - Biomechanical Engineering Lab (UPC) TecSalut - Health Technologies Research Group CDEI - Centre de Disseny d'Equips Industrials

• Acoustic Signal Processing
• Blind Source Separation
• Digital Signal Processing
• +6 more

Shoji Makino is a Professor at Waseda University's Graduate School of Information, Production and Systems. He has held academic and research positions at institutions such as the University of Tsukuba and NTT Communication Science Laboratories. His work spans acoustic signal processing, blind source separation, and adaptive filtering. Education: Ph.D., Tohoku University (1993.03) Mechanical Engineering, Tohoku University Graduate School of Engineering (1979.04–1981.03) Engineering, Tohoku University Faculty of Engineering (1975.04–1979.03) Research Interests: His research focuses on acoustic signal processing for speech and audio, including blind source separation (BSS) , beamforming , and adaptive filtering . He pioneered methods for solving permutation alignment in frequency-domain BSS and developed geometrically constrained ICA techniques. Scientific Awards: Hoko Award (2018.10, Hattori Hokokai Foundation) Outstanding Contribution Award of the Institute of Electronics, Information, and Communication Engineers (2018.06) IEEE Signal Processing Society Best Paper Award (2014.01) IEEE Fellow (2004.01) IEICE Achievement Award (1997.05) Committee Memberships: He has served as Chair of the IEEE CAS Society's Blind Signal Processing TC, General Chair of IEEE WASPAA2007, and Associate Editor of IEEE Trans. SAP. He is actively involved in EURASIP, APSIPA, and the Acoustical Society of Japan.

Chaminda WijethilakeView profile

Senior Lecturer

• Environmental Accounting
• Social Accounting
• Sustainability Management Accounting
• +5 more

Dr. Chaminda Wijethilake serves as a Senior Lecturer in Accounting at Essex Business School, University of Essex, where he contributes to sustainability accounting education and research. His academic journey spans Sri Lanka, Taiwan, and Australia, culminating in impactful work at the intersection of accounting, sustainability, and governance across diverse global contexts. Education: Bachelor of Commerce with First Class Honours, University of Peradeniya, Sri Lanka (2007) Master of Business Administration, National Cheng Kung University, Taiwan (2011) PhD in Accounting and Corporate Governance, Macquarie University, Australia (2016) Chaminda's research pioneers the application of accounting frameworks to urgent sustainability challenges, particularly examining how management control systems mediate organizational responses to environmental pressures. His work spans waste management governance, sustainable supply chains in emerging economies, and accountability mechanisms during disasters, consistently revealing how formal control systems interact with cultural and institutional factors to drive (or hinder) sustainability outcomes. Current projects investigate digitalization in NGOs and sustainability core values in risk management. His publication portfolio demonstrates a clear trajectory toward increasingly complex global sustainability challenges, evolving from firm-level sustainability controls to transnational waste governance and pandemic response systems. Recent work shows growing emphasis on Global South contexts and the political dimensions of environmental accountability. Scientific Awards: President’s Award for Scientific Research by the Government of Sri Lanka Best International Impact Research Award by the University of Essex Chaminda actively supervises four PhD candidates researching sustainability management accounting in healthcare, Thailand's primary care system, and public sector accountability. His research program is supported by significant grants from PEFA-World Bank Group, Innovate UK, and the Global Challenges Research Fund, including a 2021 ESRC IAA project developing an Essex employability toolkit and a 2020 GCRF project integrating climate change into South Asian public finance policies.

Hangfeng HeView profile

Assistant Professor

• Machine Learning
• Natural Language Processing
• Reasoning
• +4 more

Hangfeng He is an Assistant Professor of Computer Science and Data Science at the University of Rochester , affiliated with the Hajim School of Engineering & Applied Sciences. He holds a PhD from the University of Pennsylvania and focuses on machine learning and natural language processing. His research emphasizes incidental supervision for natural language understanding, interpretability of deep neural networks, and reasoning in natural language. Education : PhD in Computer Science from University of Pennsylvania Research Interests : Machine Learning (especially deep learning theory, generalization, and optimization) Natural Language Processing (incidental supervision, language understanding, and multimodal reasoning) Reasoning (inductive biases, temporal data analysis, and model interpretability) Research Trends : His work spans foundational AI research and applied NLP, with recent focus on large language models, multimodal systems, and constraint-aware methods. He explores how models generalize from limited supervision and mitigate biases in real-world data. Key themes include improving model robustness, understanding inductive mechanisms, and applying AI to financial and social text analysis. Labs/Teams : While specific lab affiliations aren’t listed, his work aligns with the Department of Computer Science’s research clusters in AI, machine learning, and data science.

Michael LässigView profile

Professor

• Biophysics
• Quantitative Biology
• Evolutionary Systems
• +4 more

Michael Lässig is a Professor at the University of Cologne, leading research in biophysics and quantitative biology with a focus on evolutionary systems. His work combines genomic data analysis with statistical physics, evolutionary genetics, and information theory to predict dynamics of fast-evolving pathogens like human influenza. Research Areas: Biophysics, Quantitative Biology, Evolutionary Systems, Genomic Data Analysis Selected Projects: Predictive Analysis of Human Influenza Virus, Clonal Interference in Evolution, Fitness Flux Modeling His publications span evolutionary theory, molecular adaptation, and computational biology. He is affiliated with the Center for Data and Simulation Science and maintains a laboratory at Zülpicher Str. 77, Cologne.

Rachel TannerView profile

Associate Professor

• Tuberculosis vaccine research
• Immune correlates of protection
• Humoral immune response
• +5 more

Rachel Tanner is an Associate Professor and Lecturer in Human Sciences at Wadham College, University of Oxford, with additional appointments as Research Fellow at Wolfson College and Access Officer for the Institute of Human Sciences. Her research focuses on tuberculosis vaccine development through analysis of immune correlates, particularly the humoral response to BCG vaccination and development of functional in vitro assays. Education MA in Biological Sciences, University of Oxford DPhil in Clinical Medicine, University of Oxford Her work addresses critical gaps in TB vaccine development by: Identifying humoral immune correlates of protection Developing in vitro mycobacterial growth inhibition assays (MGIA) to reduce animal use Investigating controlled human infection models Exploring non-specific effects of BCG vaccination Advancing bovine TB vaccine research She leads initiatives aligning with the 3Rs principles for animal research. Notable scientific awards include: TBVI Young Scientist Award (2017) CTVD Early Career Scientist Award (2018) 'Women of the Future' Award for Science (2019) Current research projects involve: Comparative analysis of BCG and MTBVAC vaccines Route-specific antibody functionality Development of novel TB vaccine candidates Standardisation of functional immune assays She contributes to scientific governance through roles on: British Society for Immunology Vaccine Affinity Group Acid Fast Club committee Oxford University Animal Care and Ethical Review 3Rs subcommittee Scientific Reports Editorial Board

Pierrick LottonView profile

Research Professor

• Electroacoustics
• Thermoacoustics
• Audio Transducers
• +4 more

Pierrick Lotton serves as a CNRS Research Director at Le Mans University's Institute of Acoustics (LAUM), a joint research unit between CNRS and the university. He leads critical work within LAUM's Transducers team, focusing on fundamental and applied research in electroacoustics and thermoacoustics. His institutional affiliation places him at France's premier acoustics research laboratory, which maintains extensive facilities for acoustic measurements, ultrasonic experimentation, and transducer development across multiple specialized domains including materials science, opto-acoustics, and bioacoustics. Lotton's research program centers on two interconnected pillars: electroacoustics and thermoacoustics. His electroacoustic investigations pioneer advanced modeling, development, and characterization of audio transducers with particular emphasis on nonlinear behaviors in loudspeakers and electric guitar pickups. Simultaneously, his thermoacoustic research explores acoustic refrigeration systems, complex couplings between acoustic and thermal energy fields, and transient nonlinear phenomena. This dual focus enables innovative cross-pollination between audio engineering and thermal physics, driving advancements in both fundamental understanding and practical applications of acoustic energy conversion. Analysis of his 2019-2024 publications reveals a consistent trajectory in transducer physics, particularly MEMS-based piezoelectric speakers, voice coil dynamics in magnetic environments, and digital acoustic projection systems. His work demonstrates exceptional methodological diversity spanning analytical modeling, experimental validation, and educational innovation. Notable contributions include the ASKNOWN project's open-access acoustics courseware and breakthroughs in understanding transducer nonlinearities for both consumer audio and specialized applications like fish sound localization. No major scientific awards were documented in the available institutional materials, though his sustained publication record in high-impact journals and presentations at European Acoustics Association forums indicate significant peer recognition. His collaborative research network spans France, Germany, Italy, and the Czech Republic, reflecting strong international engagement. Lotton's academic supervision activities aren't explicitly detailed, but his educational initiatives like the ASKNOWN project demonstrate commitment to pedagogy. His research is supported through LAUM's institutional framework and collaborative projects including European initiatives and ANR-funded programs. Current work appears concentrated on advancing MEMS transducer technology, refining thermoacoustic cooling systems, and developing next-generation educational resources for acoustics. As a core contributor to LAUM's Transducers team, Lotton operates within one of Europe's leading acoustics laboratories. His current projects align with LAUM's strategic focus on transducer innovation and thermoacoustic applications, positioning him at the forefront of both theoretical acoustics research and practical engineering solutions. The laboratory's comprehensive infrastructure supports his work from fundamental wave propagation studies to applied device development.

Adi NatanView profile

Researcher

• Ultrafast X-ray Imaging
• Quantum Dynamics
• Light-Matter Interaction
• +5 more

Dr. Adi Natan is a Staff Scientist at SLAC National Accelerator Laboratory and Principal Investigator at Stanford PULSE Institute, Stanford University. His research focuses on imaging ultrafast atomic motion and quantum dynamics in complex systems using X-ray free-electron lasers (LCLS) and advanced computational tools. Education: PhD in Physics, Weizmann Institute of Science M.Sc. in Biological Physics, Weizmann Institute B.Sc. in Physics, Hebrew University Dr. Natan’s work uncovers light-matter interactions at atomic scales, particularly in strong-field environments and transition metal catalysis . His team develops real-space inversion and super-resolution methods to bypass traditional diffraction limits, enabling spatiotemporal imaging of molecular processes like photodissociation , non-adiabatic transitions , and electron delays . Key findings include: Observing Fe(CO)₅ photodissociation dynamics and energy redistribution. Characterizing deformational isomers in bridged metal complexes using ultrafast X-ray solution scattering. Mapping sub-femtosecond molecular vibrations and attosecond electron motion . His methodologies integrate X-ray scattering , Legendre decomposition , and Fourier analysis to resolve quantum processes in real space , advancing applications in catalysis , quantum control , and ultrafast chemistry . Dr. Natan’s group at PULSE includes postdoctoral researchers , graduate students , and collaborators , focusing on experimental and computational protocols for emerging X-ray facilities like LCLS-II.

Scott F. MidkiffView profile

Professor

• Networking
• Telecommunications
• Computer Engineering
• +4 more

Scott F. Midkiff is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on networking, telecommunications, and cybersecurity, with particular emphasis on 5G, O-RAN, edge cloud computing, and interference management in wireless networks. He holds a Ph.D. from Duke University (1985), an M.S.E.E. from Stanford University (1980), and a B.S.E. from Duke University (1979). Midkiff’s work spans theoretical and applied domains, including stochastic optimization for RAN intelligent controllers, network slicing, and wireless control plane design. He has contributed to advancements in interference alignment, MIMO systems, and secure spectrum sharing. His awards include the ORBIE Award and Capital CIO of the Year. Awards: ORBIE Award, Capital CIO of the Year Service: Member at Large, IEEE Committee on Engineering Accreditation Activities; ABET Program Evaluator His research group explores cutting-edge topics like software-defined cellular networks, distributed scheduling in underwater networks, and energy-efficient routing in sensor networks. Midkiff is affiliated with Virginia Tech’s research initiatives in pervasive computing and sustainable wireless systems.