Find Academic Supervisors

Brett HarrisView profile

Professor

• Geophysics
• Hydrogeology
• Mineral Exploration
• +4 more

Professor Brett Harris is a faculty member at Curtin University, affiliated with the School of Earth and Planetary Sciences (EPS) within the Faculty of Science and Engineering. He holds a prominent role in the Office of the Provost. His research focuses on subsurface resource technologies, including mineral exploration, CO2 sequestration, and geothermal energy. He has led major initiatives like the DET CRC and MinEx CRC projects, advancing in-hole electromagnetic sensing and distributed acoustic sensing techniques. His expertise spans hydrogeology, geophysics, and environmental geoscience, with notable contributions to aquifer characterization, fault zone dynamics, and CO2 storage monitoring. He coordinates undergraduate courses in electromagnetism, potential fields, and environmental geophysics, while supervising multiple PhD students. Key collaborations include work with government agencies on fractured aquifer detection and geothermal systems. Recent research emphasizes innovative sensor technologies for subsurface imaging, CO2 leakage monitoring, and groundwater sustainability. His work bridges geophysics with applied engineering solutions for resource exploration and environmental stewardship.

• Machine Learning for Music
• Music Modeling and Generation
• Ethics of AI in Music
• +4 more

Bobby Lee Townsend Sturm JR is an Associate Professor at KTH Royal Institute of Technology, leading the MUSAiC project (ERC-2019-COG). He holds a PhD in Electrical and Computer Engineering from UC Santa Barbara (2009), followed by postdoctoral research at LAM, Paris 6, and academic roles at Aalborg University and Queen Mary University of London. His research focuses on AI ethics in music, generative AI for music, and folk music preservation. Current roles at KTH include teaching and supervising in Machine Learning, Music Informatics, and AI Ethics. He has pioneered AI music generation challenges (e.g., 2020 Double Jigs Challenge) and investigates societal impacts of AI on traditional music cultures. His work bridges technical innovation with cultural and ethical considerations, addressing issues like data colonialism, algorithmic bias, and human-AI collaboration in creative contexts. Education: PhD (UCSB, 2009), Postdoc (Paris 6), Academic appointments at Aalborg University (2010–2014) and Queen Mary University (2014–2018) Key Projects: MUSAiC (ERC), Virtual Session System for Irish Music, Traditional Music Dataset Analysis Teaching: Courses in Machine Learning, Music Acoustics, and ICT Innovation Publications span peer-reviewed journals and conferences, emphasizing ethical AI, music generation, and interdisciplinary research in MIR (Music Information Retrieval). He actively collaborates with musicians, anthropologists, and technologists to ensure culturally informed AI development.

Andrea W. LuangrathView profile

Associate Professor

• Consumer Behavior
• Nonverbal Influence
• Sensory Marketing
• +7 more

Andrea W. Luangrath is an Associate Professor of Marketing and Henry B. Tippie Research Fellow in the Tippie College of Business at the University of Iowa. She holds a PhD in Marketing from the University of Wisconsin–Madison and teaches consumer behavior at both undergraduate and doctoral levels. Research Interests: Nonverbal social influence in consumer contexts Haptics and sensory marketing Textual paralanguage and consumer linguistics Psychological ownership Virtual reality and digital experiences Her recent research explores how digital cues mimic physical sensations, how language conveys nonverbal emotion, and how consumers develop feelings of ownership. Her work has been published in premier journals including the Journal of Marketing Research , Journal of Consumer Research , and Journal of Consumer Psychology . She has received numerous awards, including the C.W. Park Young Contributor Award (2017), the Early Career Faculty Research Award (2021), and the Mid-Career Faculty Scholar Award (2025–2028). She is also an MSI Young Scholar (2023). Mid-Career Faculty Scholar Award - University of Iowa (2025–2028) MSI Young Scholar, Marketing Science Institute (2023) Early Career Faculty Research Award - Tippie College of Business (2021) Cannon Faculty Scholarship for Teaching Excellence (2020) Highly Cited Paper Award - Journal of Consumer Psychology (2017) C.W. Park Young Contributor Award (2017) Park Outstanding Contribution to JCP Award (2016) She has secured research funding through the Tippie Research Excellence Grant (2019) and served as Director of Graduate Studies in Marketing from 2022 to 2025. She is actively involved in the academic community as an Editorial Board Member for the Journal of Marketing Research (from 2025) and Journal of Consumer Psychology (from 2022). Her lab focuses on behavioral experimentation in consumer psychology, leveraging both virtual environments and textual analysis tools to study nonverbal influence.

Markus ListView profile

Professor

• Systems Biology
• Data Science
• Bioinformatics
• +3 more

Prof. Dr. Markus List is a Professor of Data Science in Systems Biology at the Technical University of Munich (TUM), affiliated with the TUM School of Life Sciences. His research focuses on integrating data science with systems biology to understand gene regulatory mechanisms across genomic levels. He leads the Big Data in Biomedicine group and has held roles including Group Leader at the Chair of Experimental Bioinformatics (2018–2023) and PostDoc at the Max Planck Institute for Informatics (2015–2018). Educational Background: BSc and MSc in Bioinformatics from Eberhard Karls University of Tübingen (2005–2011) PhD in Molecular Oncology from University of Southern Denmark (2011–2015) Research Interests: Prof. List’s work bridges biology, medicine, and informatics using machine learning and data integration. Key areas include: Systems Biology of gene regulation in cancer Epigenetic data analysis Computational methods for biomedical big data Awards & Recognition: Research Prize of the Hamburg Cancer Society (2023) TUM Teaching Award (2023) TUM School of Life Sciences Supervisory Award (2022) Labs & Teams: Leads the DaisyBio group, focusing on experimental and computational bioinformatics. Collaborates with interdisciplinary teams in bioinformatics and systems medicine.

Zhenzhou WangView profile

Research Fellow

• Composite Materials
• Cryogenic Material Testing
• Multi-objective Design Optimization
• +7 more

Dr. Zhenzhou Wang is a Research Fellow at the University of Southampton, affiliated with the CERN-STFC HL-LHC Project. His research focuses on lightweight materials for liquid hydrogen storage systems in aircraft and ships, composite material modeling, and AI-driven multi-objective optimization. He is a member of the Energy Technology Group and has held roles such as Guest Editor for Polymers (2021-2023). Notable achievements include receiving the Dean's Award (2024) twice. His work integrates analytical and numerical methods to address challenges in aerospace materials, cryogenic testing, and structural optimization. Recent studies include evaluating thermoplastic polymers for cryogenic sealing, thermal fatigue effects on composites, and deployable composite boom design frameworks. Collaborations involve researchers from institutions like CERN and industry partners. Affiliations: University of Southampton (CERN-STFC HL-LHC Project), Energy Technology Group Key Projects: Liquid hydrogen fuel storage systems, spacecraft lightweight materials, AI optimization algorithms Awards: Dean's Award (2024)

Shengwu LiView profile

Professor

• Behavioral Economics
• Oncology
• Molecular Biology
• +3 more

Shengwu Li is a Professor of Economics at Harvard University’s Department of Economics, affiliated with the Faculty of Arts and Sciences (FAS). He previously served as a Junior Fellow of the Society of Fellows. His research spans behavioral economics theory and molecular oncology, focusing on mechanisms of cancer drug resistance, targeted therapies, and epigenetic regulation in tumors. He has contributed to understanding KRAS inhibition resistance, HER2 exon 20 insertion mutations, and synergistic immunotherapies combining epigenetic modifiers with immune checkpoint blockade. Education details not explicitly listed in the text. Research interests include behavioral economic models of decision-making under uncertainty, coupled with experimental studies in cancer biology. His work bridges theoretical economics and translational oncology, addressing challenges in precision medicine and drug development. Recent studies explore therapeutic efficacy of CDK7 inhibitors in pancreatic cancer and mechanisms of adeno-to-squamous transition in lung tumors. Notable achievements include the Junior Fellow distinction, highlighting early-career excellence in interdisciplinary research. Collaborative projects involve preclinical models of tumor organoids and ex vivo patient-derived spheroids to identify combination therapies for HER2-mutant lung cancers.

• Biofluid Dynamics
• Biomedical Engineering
• Biomechanics
• +7 more

Joseph van Batenburg-Sherwood is a Lecturer in Biofluid Mechanics at Imperial College London's Department of Bioengineering (Faculty of Engineering). He leads the vBS Lab and holds a Royal Academy of Engineering Research Fellowship (2017–2022). His research focuses on biofluid dynamics, particularly in microvascular diseases, intraocular pressure regulation, and ventilator design for resource-limited settings. Education: MEng in Mechanical Engineering, King’s College London (2005–2009) PhD in Biofluid Dynamics, University College London (2009–2013) Research interests include experimental techniques for microscale biological flow analysis, with specializations in: Red blood cell dynamics in microvascular diseases Aqueous humor flow mechanics in glaucoma Ventilator design optimization Benchtop perfusion systems (e.g., iPerfusion) Publications emphasize translational research in ocular fluid dynamics and medical device innovation. Notable contributions include consensus guidelines for outflow facility measurement protocols and MMP-3-based glaucoma therapies. Advising: No listed advisees. Grants: Unspecified in provided text. Labs: vBS Lab at Imperial College London's White City Campus.

Bahador BahramiView profile

Assistant Professor

• social neuroscience
• collective decision-making
• decision-making
• +7 more

Dr. Bahador Bahrami serves as an ERC Group Leader and junior faculty member at the Graduate School of Systemic Neurosciences (GSN), affiliated with the Chair of General and Experimental Psychology within the Faculty of Psychology and Educational Sciences at Ludwig Maximilian University of Munich. Previously associated with the Munich Center for Neurosciences (MCN), his current research integrates psychological, neurobiological, and computational approaches to investigate human interactive behavior. His primary research interests center on the cognitive and neurobiological mechanisms of social decision-making, with emphasis on collective intelligence, confidence calibration, influence dynamics, and consensus formation. Utilizing behavioral experiments, fMRI neuroimaging, and psychopharmacology, his work examines how humans share information and negotiate during joint decisions, particularly investigating biases like equality distortion and vulnerability to disinformation in group contexts. The lab actively explores neural substrates of social influence and human-AI collaborative decision-making. Analysis of his 2015-2021 publications reveals a consistent trajectory examining social influence mechanisms across behavioral, neural, and computational domains. Key themes include the neural basis of strategic advice-giving, cultural universality of decision biases, exploitation vulnerabilities in human-AI systems, and disinformation's impact on social influence competition. His work demonstrates interdisciplinary integration of psychology, neuroscience, and game theory to model collective cognition. Scientific recognition includes: ERC Group Leader award supporting his independent research program Dr. Bahrami supervises graduate researchers including Jamal Esmaily, with his ERC-funded laboratory enabling comprehensive investigation of interactive decision-making. His research program combines theoretical modeling with multimodal empirical approaches, securing significant European funding for exploring the biological foundations of social cognition. Current projects examine neural correlates of influence reciprocity and algorithmic exploitation in human-machine teams. He leads an active research group at LMU Munich investigating crowd cognition dynamics, with laboratory facilities supporting behavioral testing, fMRI studies, and computational modeling of social interactions. The team maintains international collaborations across neuroscience and decision science domains, focusing on translating fundamental research into understanding real-world collective behavior in digital and social environments.

Neil LeonardView profile

Professor

• Sound Art
• Experimental Music
• Multimedia Performance
• +7 more

Neil Leonard is a Professor at Berklee College of Music and the founding Artistic Director of the Berklee Interdisciplinary Arts Institute. He is affiliated with the Department of Electronic Production and Design (EPD) within the College of Arts and Sciences. His artistic and academic work bridges music, technology, and interdisciplinary collaboration. Ph.D. or equivalent terminal degree in composition or sound art (inferred from academic rank and output) Extensive international residency and fellowship experience Leonard's research and artistic practice centers on sound art, electroacoustic composition, and multimedia performance . He explores immersive multichannel audio, live electronics, and collaborations with visual artists, dancers, and filmmakers. His work investigates the resonance of cultural memory, urban soundscapes, and historical acoustics. He integrates technology and philosophy, often drawing from astronomy, Plato, and intercultural exchange. His recent works, including Matanzas Sound Map (Tate Modern, 2025), Sonance for the Precession , and For Kounellis , reflect a trend toward site-specific, durational sound installations that merge scientific concepts with poetic expression. These pieces utilize field recordings, algorithmic processing, and spatial audio to create immersive environments. His scientific and artistic honors include: Fulbright Specialist Award (2016) Distinguished Faculty Award, Berklee (2011) International CubaDisco Award (2015) Rauschenberg Residency (2016) Sacatar Institute Fellow (2023) MIT Art, Culture, and Technology affiliate U.S. State Department Fulbright Specialist Roster (2013–present) Leonard is deeply committed to mentoring students, particularly in refining portfolios and developing lifelong learning strategies. He emphasizes time management as a compositional skill and encourages adaptability in the evolving music industry. He has led major collaborative projects such as The Berklee Sessions with Robin Rimbaud (Scanner) and has performed with renowned artists including Vijay Iyer, Rudresh Mahanthappa, and Los Muñequitos de Matanzas. He co-founded and leads the Berklee Interdisciplinary Arts Institute , fostering cross-departmental collaborations and innovative performance practices. His work continues to be exhibited globally, from Documenta and Venice Biennale to Mass MoCA and the Peabody Essex Museum.

Vassilis ChristophidesView profile

Professor

• Databases
• Web Information Systems
• Big Data Processing
• +9 more

Vassilis Christophides is a Professor of Computer Science at the University of Crete and holds an advanced research position at Inria Paris, where he leads work in the MiMove team. His research spans databases, web information systems, big data processing, and IoT analytics, with a strong emphasis on entity resolution, data integration, and scalable data mining. He has supervised numerous research projects funded by the European Union and the Greek State, and has published over 130 articles in top-tier conferences and journals. Research Interests: His primary research areas include Databases, Web Information Systems, Big Data Processing and Analytics, and Information Systems for the Internet of Things. He also focuses on entity resolution, knowledge graphs, streaming data, and explainable AI, particularly in the context of anomaly detection and fairness-aware data systems. His recent work explores hybrid attention models for entity alignment and causal analysis in time series classification. Recent Research Trends: Analysis of his recent publications (2021–2025) reveals a strong focus on entity resolution with fairness constraints, explainable anomaly detection, and adaptive scheduling in IoT edge analytics. He also investigates deepfake detection, crop type mapping using satellite data, and structural bias in knowledge graphs, demonstrating a broad and impactful research portfolio at the intersection of data management and machine learning. Scientific Awards: 2004 SIGMOD Test of Time Award Best Paper Award, ISWC 2003 Best Paper Award, ISWC 2007 Advising and Grants: While specific student names are not listed in the provided texts, Christophides has co-authored numerous papers with researchers such as Vasilis Efthymiou, Ioannis Tsamardinos, and Nikolaos Myrtakis, suggesting active mentorship. He has been the scientific coordinator of multiple EU and national research projects, indicating substantial grant leadership and project management experience. Labs and Teams: He is affiliated with the MiMove team at Inria Paris, a research group focused on mobility and data-intensive systems. His work bridges academic and applied research, leveraging Inria’s infrastructure for large-scale data experimentation and innovation in IoT and edge computing environments.

Xifan WuView profile

Professor

• Computational Physics
• Materials Science
• Condensed Matter Physics
• +3 more

Xifan Wu is a Professor of Physics at Temple University, specializing in computational methods and materials science. His research focuses on first-principles computational approaches, particularly exploring the locality of Wannier orbitals to address physical problems in solids and liquids. Key interests include superlattice design and applications of order-N exact exchange functionals like PBE0 and GW quasi-particle approximations. He has authored numerous high-impact publications in journals such as Physical Review Letters and Physical Review B , covering topics like ferroelectric superlattices, X-ray absorption spectroscopy, and the dielectric properties of electrolyte solutions. His work bridges quantum mechanical models with machine learning potentials, advancing large-scale simulations of complex materials. Education/Background: Not explicitly detailed in the provided text. Grants/Awards: No specific awards listed, but his research is supported by Temple University’s Center for the Computational Design of Functional Layered Materials (CCDM). Labs/Teams: Collaborates with teams focused on computational design and materials modeling, possibly through Temple’s physics department and affiliated research centers. His recent work explores molecular-scale insights into electrical double layers at oxide-electrolyte interfaces and the impact of ions on X-ray spectra, demonstrating expertise in linking theoretical models with experimental phenomena.

Kandler SmithView profile

Researcher

• Battery lifespan
• Battery microstructures
• Battery second use
• +5 more

Kandler Smith is a Researcher VI in Mechanical Engineering at the National Renewable Energy Laboratory (NREL), where he leads data science, modeling, and diagnostics efforts within the Electrochemical Energy Storage group. He has been with NREL since 2007, establishing himself as a key contributor to battery research and development. Smith holds a PhD in Mechanical Engineering from Pennsylvania State University, along with a Master's in Mechanical Engineering from the same institution, a Master's in Engineering Management from the University of Florida, and a Bachelor's in Mechanical Engineering from Virginia Tech. His educational background provides a strong foundation in both technical engineering principles and project management. His research focuses on advancing lithium-ion battery technology, with particular expertise in battery lifespan prediction, microstructure analysis, second-life applications, and multi-scale modeling approaches. Smith applies machine learning techniques to model identification, fast charging algorithms, and computational design of electrochemical/thermal/mechanical phenomena in batteries. His work spans energy storage systems and transportation/mobility applications, contributing significantly to the field of electrochemical energy storage. Smith maintains a robust publication record with over 200 research outputs, showing consistent growth in productivity with notable peaks in 2015 (19 publications), 2020 (21 publications), and 2022 (20 publications). His recent work demonstrates sophisticated approaches to battery technology challenges, including advanced modeling techniques and innovative material solutions. Invited to Finland by U.S. Ambassador Bruce Oreck to represent NREL and the U.S. Department of Energy in seminars and interviews (2009) NREL Distinguished Member of Research Staff Recipients (2022) NREL Outstanding Mentor Award (2014) NREL President's Award (2009) NREL Staff Award (2012) As recognized by his Outstanding Mentor Award, Smith plays an important role in developing the next generation of energy researchers. His work bridges fundamental battery science with practical applications in electric transportation and renewable energy integration, contributing to more sustainable energy solutions. His research fingerprint shows strong focus on lithium-ion batteries (100%), lithium ion battery material science (86%), and related areas including state of charge engineering and electric vehicle technology.

Julian F. HenriquesView profile

Researcher

• Sound Studies
• Cultural Studies
• Caribbean Studies
• +4 more

Dr. Julian F. Henriques is a Senior Research Fellow at Goldsmiths, University of London, and a leading scholar in sound studies, cultural studies, and Caribbean research. With a PhD thesis (2008) on Reggae Sound System Crews, his work bridges music, technology, and embodiment through practice-based research. He has authored the book Sonic Bodies (2011) and co-edited Rhythm, Movement, Embodiment (2014). Currently, he explores fetal auditory environments through the Sonic Womb Exhibition (2026) and contributes to obstetric research on noise exposure. Research Interests: His scholarship focuses on the Jamaican sound system as a cultural technology, analyzing rhythm, affect, and sonic embodiment. He investigates intersections between popular culture, Caribbean diasporic practices, and the materiality of sound through theoretical frameworks like Afrofuturism (2015) and cosmopolitan theory (2020). Recent work combines computational acoustic modeling with ethnographic insights into prenatal soundscapes. Key Publications: Includes articles on fetal noise exposure (2025), Jamaican knowledge systems (2023), and rhythm analysis (2014). His edited works span Stuart Hall's legacy (2018) and sound studies companions. Collaborations with acoustic engineers (2025) demonstrate interdisciplinary reach. Collaborations: Works with institutions like University College London (2025), Tate Modern (2011), and the University of Munich (2014). Leads the Sonic Womb project with Pierre Gélat and Atau Tanaka.

Rianne ConijnView profile

Assistant Professor

• Learning Analytics
• Human-Technology Interaction
• Artificial Intelligence
• +6 more

Rianne Conijn is an assistant professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), Netherlands. Her research bridges data-driven methodologies (machine learning, statistical modeling) with human-centered design to enhance learning analytics, explainable AI, and writing process analysis. She holds a joint PhD (cum laude) from Antwerp University and Tilburg University, and an MSc (cum laude) in Human-Technology Interaction from TU/e. Academic Background: MSc (2015, TU/e, cum laude), PhD (2020, Antwerp University & Tilburg University, cum laude). Research Focus: Learning analytics, keystroke logging, explainable AI for education, data dashboards, and self-regulated learning dynamics. Teaching: Courses in Advanced Research Methods, Human-AI Interaction, Behavioral Research Methods, and AI ethics in education. Her recent publications explore parallel language planning in writing, longitudinal self-regulated learning strategies, and generalizability of academic performance prediction models. She leads an NWO Veni project on Human-Centered AI in education, emphasizing tailored explanations for student-AI collaboration. Scientific awards include cum laude distinctions for her MSc and PhD, and the NWO Veni grant. Collaborative work spans institutions in the Netherlands, Norway, and the U.S., with applications in intelligent tutoring systems and ethical AI deployment in exams. Key trends across her work: integration of machine learning with educational theory, leveraging keystroke data for cognitive process insights, and prioritizing actionable, explainable AI systems for student support. Publications span journals like the Journal of Experimental Psychology: General , Computers and Education , and IEEE Transactions on Learning Technologies . Scientific Awards: NWO Veni grant for Human-Centered AI in education Cum laude for MSc and PhD Grants & Collaborations: National Science Foundation grants (2016868, 2302644) for biometric feedback in writing UK Research and Innovation grant (ES/W011832/1) for real-time AI scaffolding TU/e Boost! Program grant for self-regulated learning analysis Labs & Teams: EAISI Foundational (Eindhoven AI Systems Institute) Human Technology Interaction group at TU/e Collaboration with Norwegian Reading National Center (University of Stavanger) Project teams for Waterproof ITS and ProWrite grants

Rayid GhaniView profile

Professor

• Machine Learning
• Artificial Intelligence
• Data Science
• +5 more

Rayid Ghani is a Professor at Carnegie Mellon University (CMU), affiliated with both the Machine Learning Department (School of Computer Science) and the Heinz College of Information Systems and Public Policy. He co-leads CMU’s Responsible AI Initiative and leads the Data Science and Public Policy Group and the Data Science for Social Good Program. His work focuses on applying machine learning, AI, and data science to address social and policy challenges in health, criminal justice, education, public safety, workforce development, and sustainability, with an emphasis on fairness, equity, and transparency in AI systems. Education: PhD in Software Engineering PhD in Societal Computing Rayid’s research spans three pillars: (1) building AI systems for human collaboration to improve decision-making, (2) embedding fairness and equity in AI design, and (3) ensuring reliability and resilience of AI systems in dynamic environments. He emphasizes application-grounded experimental design and stakeholder engagement. His recent publications include frameworks for fair ML experimentation, analyses of fairness-accuracy trade-offs, and AI applications in child welfare, public health, and housing policy. He has also contributed to policy discussions, including congressional testimonies on responsible AI procurement. Advising & Grants: Rayid collaborates with governments, NGOs, and academic institutions on projects like eviction prevention, HIV care retention, and bias mitigation in public policy. He advises non-profits and startups on data science strategy and ethics. Labs & Teams: He leads the Data Science and Public Policy Group and the Data Science for Social Good Program at CMU, fostering interdisciplinary collaborations between computer scientists, social scientists, and policymakers.