Find Academic Supervisors

• Digitisation
• Document Analysis
• Digital Transformation
• +7 more

Prof Apostolos Antonacopoulos is a Professor of Pattern Recognition at the University of Salford, leading the PRImA research Lab (Pattern Recognition and Image Analysis). He holds a PhD from UMIST (1995) and has held academic roles at the University of Liverpool and Salford. His expertise spans Document Analysis, Computer Vision, and AI applications in Cultural Heritage. Education: PhD in Computer Science, University of Manchester Institute of Science and Technology (UMIST), UK (1995) Research Interests: Digitisation of historical documents and large-scale data Image Analysis and Pattern Recognition AI-driven solutions for cultural heritage preservation Performance evaluation frameworks for OCR systems Recent Projects: Leading a £750K ONS-funded project (2020–2025) digitising UK census reports Europeana Newspapers (€4M EU project, 2012–2015) for European Digital Library SUCCEED (€1.8M EU project, 2013–2015) for digitisation competencies Awards and Roles: IAPR/ICDAR Young Investigator Award (2005) Former President of International Association for Pattern Recognition (IAPR) Editorial roles in IJDAR and IEEE Transactions on Multimedia Labs/Teams: Director of PRImA Lab, collaborating with institutions like British Library and Wellcome Library. Active in industry partnerships for digitisation solutions.

Vikram DeshpandeView profile

Professor

• Mechanobiology
• Solid mechanics
• Data-driven mechanics
• +4 more

Vikram Deshpande is a Professor in the Department of Engineering at the University of Cambridge, UK, where he has been employed since 2010. He also maintains significant international connections, having served as a Visiting Professor at the Technical University of Eindhoven (2009-2017) and previously holding positions at the University of California, Santa Barbara and Brown University. His research spans multiple disciplines within solid mechanics and materials science, focusing on fundamental mechanisms that govern material behavior across different scales. His research interests encompass Mechanobiology , where he explores cellular organization mechanisms; Solid mechanics with applications to impact and failure; Data-driven mechanics approaches; Microarchitectured solids including mechanical metamaterials; Fluid-structure interaction in impact scenarios; Chemo-mechanics of battery materials; and Dislocation mechanics for understanding material deformation. His work uniquely bridges fundamental physics with practical engineering applications, particularly in developing materials with tailored mechanical properties. The analysis of his recent publications reveals a strong focus on mechanical metamaterials, cellular mechanics, and electro-chemo-mechanical phenomena in energy storage systems. His research demonstrates a consistent pattern of addressing fundamental scientific questions while maintaining strong connections to practical engineering applications, particularly in materials design, protective systems, and energy technologies. His publications frequently combine experimental approaches with sophisticated modeling techniques across multiple scales. 2024 Zdeněk P. Bažant Medal for Failure and Damage Prevention 2023 Fellow, Royal Academy of Engineering and International Member US National Academy of Engineering 2022 Warner T. Koiter Medal and William Prager Medal 2022 European Research Council (ERC) Advanced Grant 2021 Gili Agostinelli Prize and IIT Bombay Distinguished Alumnus Award 2020 Fellow, Royal Society of London and Rodney Hill Prize Professor Deshpande has served on numerous editorial boards including the Journal of the Mechanics and Physics of Solids (current Associate Editor), Modelling and Simulation in Materials Science and Engineering, and Proceedings of the Royal Society A. He chairs the Royal Society Sectional Committee 4 and serves on the Advisory Board of the European Mechanics Society EUROMECH. His leadership extends to directing the International Conference on Fracture and chairing the EUROMECH Mechanics of Materials Conference committee. His research group at Cambridge, accessible through cambridgesolidmechanics.co.uk, focuses on developing fundamental understanding of material behavior to enable the design of next-generation engineering materials.

• Social Media Analysis
• Sentiment Analysis
• Computational Journalism
• +6 more

Fabrício Benevenuto is an Associate Professor in the Computer Science Department at Federal University of Minas Gerais (UFMG), where he conducts interdisciplinary research at the intersection of social media analysis, data science, and computational journalism. His work spans complex networks, machine learning, and natural language processing with strong societal impact. His research focuses on social media dynamics, particularly in Brazilian contexts, with major contributions to hate speech detection, fake news analysis, and political discourse monitoring. He leads large-scale projects against misinformation, including development of systems like WhatsApp Monitor, Media Bias Monitor, and Purple Feed. His work combines technical innovation with real-world applications for election transparency and public discourse integrity. Benevenuto's recent publications demonstrate strong trends in multilingual NLP for social media analysis, with emphasis on Brazilian Portuguese contexts. His team produces both theoretical contributions and practical systems addressing hate speech, misinformation, and media bias. Notable methodological approaches include combining network analysis with linguistic features, developing culturally-aware detection systems, and creating large annotated datasets for understudied languages. CAPES award for best Brazilian computer science thesis (2010) Humboldt Foundation scholarship recipient (2017-2018) Member of TikTok Safety Advisory Council WWW'20 Best Paper Nominee & CNIL-INRIA Privacy Protection Prize winner Multiple best paper awards at CEAS, WBC, and ICWSM conferences Test-of-Time Award at ICWSM'20 Benevenuto actively mentors PhD and MSc students, with numerous advisees securing academic positions at Brazilian universities and research roles at institutions like Max Planck Institute. His projects often receive funding supporting interdisciplinary collaborations across computer science and social sciences. Current work includes large-scale analysis of Telegram political groups, real-time election monitoring systems, and developing culturally-aware NLP tools for Portuguese. He leads research teams working on social media analysis systems with societal impact, particularly focused on Brazilian digital ecosystems. Projects involve cross-institutional collaborations with researchers from MPI-SWS, Max Planck Institute, and various Brazilian universities, emphasizing practical applications for public discourse integrity.

Enkelejda MihoView profile

Professor

• Digital Life Sciences
• Medical Informatics
• Artificial Intelligence in Healthcare
• +4 more

Prof. Enkelejda Miho is a Professor of Digital Life Sciences at the School of Life Sciences, FHNW, leading the aiHealthLab. Her work bridges computer science/AI with life sciences, focusing on drug discovery, personalized medicine, and immunology. She holds roles as Team Leader at aiHealthLab and Group Leader at the Swiss Bioinformatics Institute. Research Interests : She applies machine learning to analyze immune repertoires, antibody engineering, and autoimmunity diagnostics. Her lab develops computational tools like the RWD-Cockpit for real-world data analysis and synthetic antibody-antigen models (Absolut!) to advance biotherapeutics. Her work on dengue immunity and monoclonal gammopathies highlights translational applications. Key Projects : The aiHealthLab focuses on AI-driven diagnostics and therapeutics. Her contributions include AI frameworks for antibody specificity prediction, age-related immune repertoire changes, and large-scale network analysis of antibody repertoires. Labs/Teams : Leads aiHealthLab and collaborates with the Swiss Bioinformatics Institute, integrating computational and experimental immunology.

Yuntian DengView profile

Assistant Professor

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +3 more

Yuntian Deng is an Assistant Professor at the University of Waterloo and a Visiting Professor at NVIDIA. He holds affiliations with Harvard SEAS as an Associate and the Vector Institute as a Faculty Affiliate. He completed his PhD in Computer Science at Harvard under Professors Alexander Rush and Stuart Shieber, followed by a postdoc under Yejin Choi. His research focuses on Natural Language Processing and Machine Learning, with notable contributions in chatbot interaction analysis (WildChat), implicit reasoning models, and markup-to-image generation. He has developed influential tools like OpenNMT and WildVis, and his work has been featured in outlets like the Washington Post and used by OpenAI and Anthropic. Education: PhD in CS (Harvard), Postdoctoral Research (University of Washington). Key achievements include the ACM Gordon Bell Prize for GenSLMs, Best Demo Runner-up at ACL 2017, and Best Paper at DAC 2020. His research emphasizes scalable datasets, efficient reasoning techniques, and real-world applications of AI models. Research interests span NLP, machine learning algorithms, and their applications in areas like dialogue systems, generative models, and ethical AI evaluation. Notable projects include WildChat (1M ChatGPT interactions), implicit chain-of-thought reasoning, and neural steganography for text-based information hiding. His articles explore topics ranging from knowledge distillation to diffusion models, with a focus on bridging theoretical advancements and practical implementations. He actively collaborates with industry partners like NVIDIA and maintains open-source tools to advance AI research accessibility.

John LehrterView profile

Professor

• Coastal Biogeochemistry
• Eutrophication Dynamics
• Hypoxia Modeling
• +7 more

Dr. John Lehrter is a Professor of Marine Sciences and Associate Director of the Stokes School of Marine & Environmental Sciences at the University of South Alabama, as well as a Senior Marine Scientist at the Dauphin Island Sea Lab. He holds a Ph.D. in Marine Sciences from the University of Alabama (2003). His research focuses on coastal biogeochemistry, ecosystem modeling, and satellite ocean color remote sensing, with an emphasis on understanding eutrophication, hypoxia, and multiple stressor impacts on coastal ecosystems. Dr. Lehrter has advised numerous graduate and undergraduate students and leads a lab engaged in field studies, numerical modeling, and satellite data analysis. His work addresses societal challenges in coastal management and climate change adaptation. Research Interests: Multiple Stressor Impacts to Coastal Ecosystems, Marine Biogeochemistry, Ecosystem Modeling, Satellite Remote Sensing, and Hypoxia Dynamics. His lab develops tools to quantify nutrient pollution effects and predict ecosystem responses to management actions. Advising and Grants: Dr. Lehrter oversees a dynamic lab with graduate students, postdocs, and technicians. Current projects include modeling nutrient dynamics, satellite data applications for water quality, and experimental studies on multiple stressors (e.g., temperature, pH) impacting marine organisms. His lab collaborates with agencies like the EPA and NOAA, contributing to coastal policy and restoration efforts. Labs/Teams: Dauphin Island Sea Lab (DISL) and the University of South Alabama’s Stokes School of Marine & Environmental Sciences. The lab recently established a state-of-the-art facility for multiple stressor experiments on marine species.

Olga VitekView profile

Professor

• Statistical Science
• Machine Learning
• Mass Spectrometry
• +5 more

Olga Vitek is a Professor at Northeastern University's Khoury College of Computer Sciences, with affiliated faculty status in the Department of Chemistry and Chemical Biology. Her research bridges statistical science and machine learning with mass spectrometry-based proteomics and systems biology, focusing on developing open-source software tools like MSstats and Cardinal for quantitative proteomic analyses and imaging. Education: PhD in Statistics (Purdue University), Postdoc at the Ruedi Aebersold Lab (Institute for Systems Biology) Leadership: Director of the Barnett Institute for Chemical and Biological Analysis Her work emphasizes: Statistical experimental design Signal detection in complex mass spectrometry data Causal inference in biomolecular networks Reproducible computational infrastructure Recent publications highlight advancements in quantitative proteomics , mass spectrometry imaging , and causal modeling , with applications spanning cancer research, immunology, and clinical diagnostics. Notable trends include deep learning integration for image analysis and open-source tool development for scalable, transparent workflows. Scientific accolades: Elected Fellow of the American Statistical Association 2021 Gilbert S. Omenn Computational Proteomics Award NSF CAREER award Chan-Zuckerberg Essential Open-source Software award Senior Member, International Society for Computational Biology

Pia FrickerView profile

Associate Professor

• Computational Methodologies
• Urban Design
• Landscape Architecture
• +8 more

Prof. Pia Fricker is an Associate Professor and Vice Head of the Department of Architecture at Aalto University's School of Arts, Design and Architecture in Finland. She holds the Professorship of Computational Methodologies in Landscape Architecture and Urbanism, directing the Urban Studies and Planning Programme. Her research integrates urban design, landscape architecture, and digital design culture, focusing on data-driven methods, immersive environments, and adaptive urban development. Collaborations include ETH Zurich, Singapore University of Technology and Design, and Hafencity University Hamburg. Key projects include the Metaversity and Future Smart Cities initiatives. Fricker has led over 80 publications and exhibitions globally, including at the Venice Biennale and National Design Centre Singapore. She is an editorial board member for the Journal of Digital Landscape Architecture and peer reviewer for multiple journals. Awards include the Digital Landscape Architecture Award (2018) and DLA Scientific Merit Award (2021). Her teaching emphasizes computational pedagogy and digital innovation in design education. Education: PhD in Architecture (ETH Zurich, 2021) Postgraduate in Didactics (ETH Zurich, 2011) MAS in Computer Aided Architectural Design (ETH Zurich, 2003) MSc Arch in Urban Design & Landscape Architecture (Technical University of Karlsruhe, 2001) Research Interests: Computational design, parametric modeling, mixed reality, climate-adaptive ecosystems, generative AI, and sustainable urban development. Her work bridges emerging technologies with ecological and urban challenges, emphasizing interdisciplinary collaboration. Grants & Projects: Metaversity (2023–2025, Principal Investigator) Future Smart Cities Sasakawa (2023–2024, Principal Investigator) ABRA (2020–2023, Project Member) Awards: DLA Awards (2018, 2021) DLA Review Committee Awards (2020–2022) Exhibition Recognitions (Venice Biennale, National Design Centre Singapore) Labs/Teams: Leads the Urban Studies and Planning Programme and collaborates with interdisciplinary teams on projects like the RAILCORRIDOR Singapore initiative. Active in digital twin development and AI-driven design tools.

Jonathan HugginsView profile

Assistant Professor

• Machine Learning
• Bayesian Computation
• Statistical Genetics
• +3 more

Jonathan Huggins is an Assistant Professor at Boston University, affiliated with the Department of Mathematics & Statistics and the Faculty of Computing & Data Sciences. He holds a Ph.D. in Computer Science from MIT (2018) and a B.A. in Mathematics from Columbia University (2012). His research focuses on developing fast, trustworthy machine learning and Bayesian methods that balance computational efficiency and statistical optimality, with applications in ecological forecasting and genomic data analysis. Education: Ph.D. in Computer Science, Massachusetts Institute of Technology (2018) B.A. in Mathematics, Columbia University (2012) Research Interests: Large-scale machine learning and Bayesian computation Robust statistical inference Applications in genomics and ecological modeling Algorithmic development for scalable inference Key Projects: Stochastic Methods for Data Science: A book on stochastic processes and algorithms VIABEL: A Python package for variational inference and diagnostics ShorTeX: A LaTeX package for mathematical writing Recent Articles: Focus on scalable Bayesian methods, error bounds for iterative algorithms, and mutational signature discovery. His work emphasizes reproducibility and robustness in statistical inference. Awards: Blackwell–Rosenbluth Award (Outstanding Junior Bayesian Researcher) Grants & Funding: Supported by NIH, NSF, and the Department of Defense. Active in advising students across multiple BU programs. Labs/Teams: Affiliated with the BU URBAN Program, Program in Bioinformatics, and Department of Computer Science.

Laura Mersini-HoughtonView profile

Professor

• Cosmology
• Theoretical Physics
• Quantum Physics
• +6 more

Laura Mersini-Houghton is a Professor of Theoretical Physics and Cosmology at the University of North Carolina at Chapel Hill. She is affiliated with the Gravity, Cosmology, and HEP (GCHEP) theory group and the Institute of Field Physics , supported by the Bahnson Fund. Her research spans three main areas: origins of the universe, dark energy, and quantum black hole physics. Her work includes proposing a quantum landscape multiverse theory to explain the universe's origin, with predictions tested by PLANCK and LHC experiments. She has also demonstrated that Hawking radiation back-reaction prevents singularity formation in collapsing stars. Education : PhD in Physics (University of Wisconsin-Milwaukee, 2000), MSc (University of Maryland-College Park, 1997), Fulbright Scholar (University of Maryland, 1994). Key trends in her recent publications include cosmological tensions, quantum multiverse implications, and time crystal-based dark energy models. She co-authored works on inflationary cosmology and cosmic probes of fundamental physics. Scientific Awards : UWM Distinguished Alumni She has been featured in media coverage and public talks, exploring topics like the arrow of time and cosmic puzzles. Her research integrates theoretical physics, string theory, and observational cosmology, supported by the Bahnson Fund.

• Addictive Disorders
• Genetics
• Substance Use Disorders
• +3 more

Yaira Zoé Núñez is a Researcher in the Division of Human Genetics at the Yale School of Medicine. Her work focuses on genetic and epidemiological factors underlying substance use disorders, including cannabis, opioid, alcohol, and methamphetamine addictions. She collaborates extensively with the Gelernter Lab and other institutions on large-scale genomic studies. Research Interests: Genetic basis of addictive disorders Multi-ancestry genome-wide association studies (GWAS) Epidemiology of polysubstance use Clinical correlates of substance use disorders Key Collaborations: Works with Prof. Joel Gelernter, Renato Polimanti, and international teams. Recent studies include: Multicenter analysis of gambling disorder in methamphetamine users (2025) Multi-ancestry cannabis use disorder GWAS (2023) Genetic risk loci for opioid use disorder (2022) Labs/Teams: Core member of the Gelernter Lab, contributing to translational research bridging genetics and clinical addiction medicine. Active in collaborative networks analyzing large-scale biomedical data.

J. Christopher BrownView profile

Professor

• Human-Environment Geography
• Amazonian Sustainable Development
• Political Ecology
• +5 more

J. Christopher Brown is a Professor of Geography and Environmental Studies at the University of Kansas. He specializes in human-environment interactions, focusing on sustainable development in the Amazon Basin. His research integrates ecological, political, and socio-economic dimensions to address deforestation, agricultural expansion, and NGO-mediated rural development. Affiliations: Department of Geography, University of Kansas; Collaborator with Brazil's Embrapa Agricultural Research Agency Key Projects: Amazonian NGO dynamics and political impacts Soybean and sugarcane expansion impacts Spatial analysis of deforestation and land use Research interests include political ecology, biogeography, and the interplay between global and local scales. He employs remote sensing and interdisciplinary methods to study environmental governance and policy outcomes. His work on NGOs reveals how funding shapes political behavior in Brazil, with findings published in Comparative Political Studies and Political Geography . Recent studies highlight the edge effects of land-use changes and biodiversity impacts on pollinators like orchid bees. Awards: 2016 George and Eleanor Woodyard International Educator Award (University of Kansas) Brown's research bridges academic inquiry and policy, examining how development policies interact with ecological systems in Latin America. Current projects address soy moratorium efficacy, sugarcane expansion in the Cerrado, and the MST landless movement's political influence.

• Psychiatry
• Addiction Medicine
• Mental Health
• +3 more

Hüseyin ÜNÜBOL is an Associate Professor (part-time) at Uskudar University's Department of Psychiatry. He graduated from Ege University Faculty of Medicine in 2008 and completed his PhD in Psychiatry in 2010. He achieved the title of Associate Professor in 2020. His research focuses on behavioral addictions, psychiatric epidemiology, and mental health during crises. Notable areas include ADHD diagnostic methods, pandemic-related anxiety, and addiction patterns in Turkey. Education: Ege University Faculty of Medicine (MD 2008), PhD in Psychiatry (2010) Key Roles: Part-time academic contributor to Uskudar University's Psychiatry Department Research Interests: His work spans addiction medicine, public health surveillance, and the psychological impacts of modern technologies. He has pioneered studies on social media addiction, pandemic mental health dynamics, and the neurocognitive basis of ADHD diagnosis using eye-tracking technology. His recent projects include large-scale national surveys on problematic gaming, shopping addiction, and substance use patterns. Articles Trends: Over 50 peer-reviewed publications since 2012, with recent emphasis on behavioral addictions (sex/gaming/social media), pandemic-related mental health, and diagnostic innovations. His 2020-2024 work shows strong focus on epidemiological studies and technological applications in psychiatry. Awards: None explicitly listed. Grants/Advising: Active in large-scale national health surveys like TURBAHAR but no specific grants/advising details provided here. Collaborates on addiction mapping projects and public health initiatives. Labs/Teams: Involved in multidisciplinary teams studying behavioral addictions and psychiatric epidemiology, though specific lab affiliations not detailed.

Nicola McConkeyView profile

Lecturer

• Neutrino Physics
• Quantum Technology
• Detector Development
• +2 more

Nicola McConkey is an Ernest Rutherford Fellow and Lecturer in Particle Physics at the School of Physical and Chemical Sciences, Queen Mary University of London. She joined the Particle Physics Research Centre in 2024 and leads experimental work in neutrino interactions and detector development. Her affiliations include the Centre for Fundamental Physics and Centre for Experimental and Applied Physics. McConkey is an active member of international collaborations including SBND, DUNE, and MicroBooNE, where she contributed to the assembly of SBND and pioneered high-statistics measurements of electron-neutrino interactions using liquid argon detectors. Her research focuses on three primary domains: neutrino physics (particularly neutrino-argon scattering cross-sections), quantum technology applications for neutrino mass measurement, and liquid argon time projection chamber (LArTPC) detector development. McConkey's investigations aim to advance fundamental particle physics through precision measurements and technological innovation, with emphasis on improving detection capabilities for next-generation neutrino experiments. Publications predominantly explore neutrino interaction dynamics, cross-section measurements, and detector performance optimizations across MicroBooNE, SBND, and DUNE collaborations. Research trends demonstrate consistent focus on refining LArTPC technologies, developing machine learning applications for particle reconstruction, and probing beyond-Standard-Model physics through neutrino interactions. Scientific Awards: Ernest Rutherford Fellowship (2022) McConkey advises two PhD students (Oscar Chow, Yoshita Dabburi) and leads significant research funding including: STFC Grant: 'Piecing together the neutrino mass puzzle' (£431,666; 2024-2027) STFC Outreach Grant: 'Quantum Technologies for Neutrino Mass' (£99,999; 2024-2025) She coordinates research within the Particle Physics Research Centre laboratory and collaborates extensively within the SBND, DUNE, and MicroBooNE international teams, alongside leading the Quantum Technologies for Neutrino Mass collaboration developing novel measurement techniques.

Jedidiah CrandallView profile

Associate Professor

• Internet Security
• Censorship Resistance
• Network Security
• +3 more

Jedidiah Crandall is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence, with an affiliation to the Biodesign Center for Biocomputing, Security and Society. His research focuses on Internet censorship, network security, and privacy-preserving technologies. Crandall collaborates with journalists and activists to expose surveillance mechanisms, particularly in politically sensitive regions like Russia and China. His work includes analyzing VPN vulnerabilities , decentralized censorship systems , and cross-border data flows . He teaches advanced courses in computer network security and advises graduate students on thesis/dissertation research. Research trends in his publications emphasize measuring state-level information control , attack vectors in modern networks , and secure communication technologies . Notable work includes TSPU: Russia's censorship infrastructure and Hidden Links: Analyzing Secret Families of VPN Apps . Crandall's teaching spans courses like Advanced Computer Network Security and Applied Cryptography , reflecting his commitment to preparing the next generation of security professionals. His Censored Planet project tracks global Internet censorship patterns through large-scale measurements.