Find Academic Supervisors

• Artificial Intelligence in R&D
• Deep Tech Ventures
• Scientific Collaboration through Digital Infrastructures
• +3 more

Angelo Romasanta is an Assistant Professor at the Department of Operations, Innovation and Data Sciences, Esade Business School. He specializes in maximizing science impact through AI-driven R&D, deep tech commercialization, and digital collaboration infrastructures. His work involves collaborations with DeepMind, CERN, and leading European institutions like the European Molecular Biology Laboratory. Education: PhD in Innovation Management (cum laude) from Vrije Universiteit Amsterdam, Erasmus Mundus Master's in Chemical Innovation and Regulation (Universities of Bologna, Barcelona, and Algarve), and a BSc in Chemistry from Ateneo de Manila University. Research interests focus on AI's role in scientific breakthroughs (e.g., AlphaFold), translating discoveries into industry via deep tech ventures, and digital infrastructures like Science Mesh. He leads projects like ATTRACT (€50M tech commercialization initiative) and participates in CERN's Science Mesh to enhance European scientific collaboration. Recognized with a Marie Curie Fellowship for studying pharmaceutical innovation adoption. Active in grants from the European Commission and AGAUR (Spain), focusing on sustainability and innovation ecosystems. Participates in the Institute for Innovation and Knowledge Management, fostering cross-sector partnerships between academia, industry, and policymakers.

Roland Dunbrack, Jr.View profile

Professor

• Computational Structural Biology
• Bioinformatics
• Protein Structure Prediction
• +14 more

Roland Dunbrack, Jr. is a Professor and Co-Leader of the Cancer Signaling and Microenvironment Program at Fox Chase Cancer Center. He also serves as Director of both the Molecular Modeling Facility and the Organic Synthesis Facility. He holds adjunct professorships at the University of Pennsylvania School of Medicine and Drexel University College of Medicine, reflecting his broad academic engagement. His research lies at the core of computational structural biology and bioinformatics, focusing on protein structure prediction, statistical analysis of protein conformations, and the development of software tools such as SCWRL, MolIDE, and BioAssemblyModeler. His work integrates Bayesian statistics, machine learning, and computational geometry to improve the accuracy of protein modeling and to apply these methods to cancer biology, DNA repair, and antibody design. He maintains several widely used public databases, including the backbone-dependent rotamer library and ProtCID. The analysis of his recent publications reveals a sustained focus on protein structure and function, with significant contributions to understanding kinase conformations, biological assemblies, antibody CDR loops, and the structural basis of disease mutations. His work increasingly bridges computational methods with clinical applications in precision medicine, particularly in cancer. Health Equity & Social Justice Award (2024) Dr. Dunbrack leads a research group that includes graduate students and postdoctoral researchers, and he actively collaborates with experimentalists across Fox Chase and beyond. His lab has been involved in major community efforts such as CASP and CAGI, assessing the state of the art in protein and genome structure prediction. He has directed the NCI-supported Molecular Modeling Facility since 2003, providing critical resources to cancer researchers. His lab, the Dunbrack Lab, is dedicated to advancing structural bioinformatics through method development, software engineering, and collaborative science. The team works on large-scale analyses of the Protein Data Bank, develops user-friendly graphical interfaces for modeling, and applies computational insights to problems in cancer signaling and microenvironment.

Shu-Ching ChenView profile

Professor

• Data Science
• Multimedia Big Data
• Disaster Information Management
• +8 more

Shu-Ching Chen is a Professor and Executive Director of the Data Science and Analytics Innovation Center (dSAIC) at the University of Missouri-Kansas City (UMKC), School of Science and Engineering. He holds a Ph.D. in Electrical and Computer Engineering from Purdue University and has extensive experience in data science, multimedia big data, disaster information management, AI/ML, and AR/VR. He leads a multi-university research center focused on data analytics, AI, and societal impact. Research Interests: His research spans data science , multimedia big data , disaster informatics , AI/ML , and spatial computing . He has pioneered work in multimodal data fusion, multimedia retrieval, and intelligent systems for disaster response and climate modeling. His recent work emphasizes AI-driven solutions for public health, transportation, and environmental resilience. The 15 most recent publications reflect a strong trend in AI for societal challenges , including pandemic response, disaster management, climate modeling, and transportation analytics. His work integrates deep learning , graph neural networks , remote sensing , and multimodal data fusion , often applied to real-world problems in public safety, healthcare, and infrastructure. There is a clear emphasis on practical software systems (e.g., hurricane loss modeling) and interdisciplinary collaboration . Scientific Honors: IEEE Fellow (2016), AAAS Fellow (2016), AIMBE Fellow (2025), AAIA Fellow (2021), SIRI Fellow (2009) ACM Distinguished Scientist (2011) Best Paper Awards (2006, 2016, 2022) IEEE TCMC Impact Award (2024), Service Award (2019) FIU Top Scholar (2011, 2012), Eminent Scholar (2014–2019) Research Leadership and Grants: Dr. Chen has secured major funding from NSF, NIH, DHS, DOE, NOAA, DoD, and industry partners (Microsoft, IBM). He is PI of a U.S. Department of Education Center of Excellence in AI-Empowered Spatial Computing and leads the dSAIC. His grants focus on AI for disaster management, pandemic response, transportation, and secure computing. He actively mentors students and collaborates across institutions. Labs and Centers: He leads the Data Science and Analytics Innovation Center (dSAIC) , a University of Missouri System-wide center. He is also PI of the AI-Empowered Spatial Computing Center of Excellence funded by the U.S. Department of Education.

• Theoretical Chemistry
• Molecule-Surface Reaction Dynamics
• Density Functional Theory (DFT)
• +3 more

Geert-Jan Kroes is a Full Professor of Theoretical Chemistry at Leiden University’s Leiden Institute of Chemistry (LIC), part of the Faculty of Science. Born in 1961, he earned his PhD in Physical Chemistry from the University of Amsterdam in 1990. His research focuses on dissociative chemisorption on transition metal surfaces, emphasizing accurate modeling of molecule-surface interactions and reaction dynamics. Key contributions include advancing density functional theory (DFT) methods (e.g., SRP-DFT) and quantifying non-adiabatic effects like electron-hole pair excitation. Education & Career: PhD: University of Amsterdam (1990) Postdoctoral positions at the University of Cambridge (1992–1993) and Free University of Amsterdam (1993–1996) Joined Leiden University in 1998 as Assistant Professor, promoted to Full Professor in 2003 Research Interests: His work bridges theoretical chemistry and surface science, targeting chemically accurate descriptions of reactions at metal surfaces. Current projects address challenges in systems with (WF-EA) > 7 eV, requiring first-principles SRP-DFT and non-adiabatic dynamics modeling. Teaching & Supervision: Teaches Theoretical Chemistry (BSc) and advanced MSc courses like Quantum Reaction Dynamics Supervised 17 PhD students and 30 postdocs, many now in academic/industry roles globally Awards & Grants: ERC Advanced Grant (2013) NWO grants (multiple awards since 2010) Labs/Teams: Leads a theoretical chemistry group at LIC, collaborating with experimental groups on surface reaction dynamics. Active in editorial roles (e.g., Surface Science Reports ) and conference organization (e.g., Gordon Research Conferences).

Inge van de VenView profile

Associate Professor

• Digital Humanities
• Literary Theory
• Cultural Studies
• +2 more

Inge van de Ven is an Associate Professor at Tilburg University's School of Humanities and Digital Sciences, Department of Culture Studies. She is currently a Marie Curie fellow at UC Santa Barbara, focusing on intersections between digital culture and literary traditions. Her research explores how digital media reshape reading practices and narrative forms. Academic affiliation: Tilburg University Current fellowship: UC Santa Barbara (Marie Curie) Key research areas: Digital Humanities, Attention Economies, Literary Theory Active in: 2016-present Van de Ven's research examines the evolving relationship between readers and texts in digital environments. Her work addresses: Attentional modulation in literary reading Database-like narrative structures in contemporary novels Trust mechanisms in digital reading environments Impact of platformed attention economies on cultural production Epistemic vigilance in reading practices Digital transformation of literary forms Her recent publications analyze how digital culture influences narrative techniques, particularly through concepts like 'Big Data' and 'Attention Economy' in works by authors such as Karl Ove Knausgård and Roberto Bolaño. She investigates how monumental novels adapt to digital information overload and how narrative structures reflect digital culture. Her research fingerprint includes strong connections to: Close and Distant Reading methodologies Narrative theory in digital contexts Attention economy analysis Age of Information studies Media-specific narrative adaptations

• Computer Science
• Databases
• Distributed Systems
• +4 more

Shahram Ghandeharizadeh is a Professor at the University of Southern California , specializing in Computer Science with a focus on databases, distributed systems, and multimedia. His research spans caching middleware, flying light specks for 3D displays, and swarm robotics. Recent work includes CAMP (cache eviction policies), Disaggregated Database Management Systems , and Flight Patterns for Swarms of Drones , reflecting his expertise in data management and swarm-based technologies. He has collaborated extensively with researchers like Hamed Alimohammadzadeh and Hieu Nguyen . His scientific awards include the ACM Software System Award (2008) , recognizing long-term contributions to software systems. Publications since 2021 highlight advancements in cache management, graph databases, and swarm robotics, with a strong emphasis on non-volatile memory and decentralized frameworks.

• Biomechanics
• Ecophysiology
• Functional morphology
• +1 more

Dr. Cristian L. Klunk is an active researcher at the Department of Biology, Technical University of Darmstadt , focusing on the biomechanics and functional morphology of ant mandibles. His work bridges ecology, evolutionary biology, and insect physiology, with a particular emphasis on how morphological traits influence mechanical performance.

Roger HunterView profile

Professor

• Synthetic Organic Chemistry
• Medicinal Chemistry
• Total Synthesis
• +4 more

Professor Roger Hunter holds the Mally Chair of Organic Chemistry in the Chemistry Department at the University of Cape Town, South Africa, a position he has occupied since 2004 after serving as Associate Professor from 1989-2003. His research program bridges synthetic organic chemistry with medicinal applications through cutting-edge methodology development and drug discovery initiatives. His academic journey began with BSc Hons (1975) and PhD, DIC (1978) from Imperial College London, followed by EPSRC Post-Doctoral Research at University College London (1980-1982) and Royal Society Fellowship in Barcelona (1978-1980). He was awarded a US Fulbright Fellowship to Yale University in 2007. Hunter's research integrates synthetic organic chemistry across three major domains: total synthesis of bioactive alkaloids (Castanospermine, Tacamonine, Lepadiformine) using novel asymmetric catalysis techniques; medicinal chemistry targeting HIV through bifunctional reverse-transcriptase inhibitors developed with Yale collaborators; antimalarial agents active against chloroquine-resistant strains; and stable garlic-derived mimics with antimicrobial/anticancer properties. His group also pioneered practical methods for unsymmetrical disulfide synthesis using 1-chlorobenzotriazole. Publication analysis reveals consistent focus on therapeutic applications (HIV, malaria, cancer) coupled with innovative synthetic methodologies, demonstrating interdisciplinary collaboration with virologists, parasitologists, and oncologists to validate compound efficacy. The HIV bifunctional inhibitor project exemplifies his rational drug design approach. His scientific recognition includes: US Fulbright Fellow (2007) at Yale University Hunter leads multiple grant-funded projects through strategic collaborations with Professor Karen Anderson (Yale, HIV inhibitors), Professor Tim Egan (antimalarials), and Dr Catherine Kaschula/Professor Iqbal Parker (anticancer agents). His laboratory trains researchers in advanced organic synthesis while maintaining active partnerships with the Institute of Infectious Disease and Molecular Medicine (IDM) at UCT. The Hunter laboratory operates at the chemistry-biology interface, utilizing specialized instrumentation for complex molecule synthesis and mechanism-of-action studies. Current efforts focus on optimizing azaquaternary center formation for alkaloid synthesis, developing next-generation HIV therapeutics, and expanding the structure-activity database for garlic-derived anticancer compounds.

Aaron GoldmanView profile

Associate Professor

• Molecular Evolution
• Origin of Life
• Astrobiology
• +3 more

Aaron Goldman is an Associate Professor in the Department of Biology at Oberlin College's College of Arts and Sciences, where he leads computational research on molecular evolution and the origins of cellular life. His work bridges genomics, biochemistry, and astrobiology to reconstruct ancient biological systems. His academic training includes a BA in Biology from Swarthmore College (2003), a PhD from the University of Washington (2010), and postdoctoral research at Princeton University (2010-2013). BA: Swarthmore College, 2003 PhD: University of Washington, 2010 Postdoc: Princeton University, 2010-2013 Goldman's research focuses on deciphering molecular signatures of the Last Universal Common Ancestor (LUCA) through computational analysis of genomic and proteomic data. His lab investigates how early life evolved cellular organization, metabolic pathways, and protein machinery over 3.5 billion years ago. Key themes include the coevolution of cellularity and metabolism, electron transport chain origins, and the role of cofactors as molecular fossils. The work combines phylogenetic reconstruction with biophysical modeling to test hypotheses about life's earliest stages. Analysis of his recent publications reveals a concentrated effort to integrate evolutionary biology with systems-level understanding of early cellular processes. The research consistently targets the interface between prebiotic chemistry and biological complexity, using computational tools to simulate ancient molecular environments and evolutionary trajectories across diverse disciplines including astrobiology and bioenergetics. Scientific recognition includes: Zuckerkandl Prize for top research article in Journal of Molecular Evolution (2023) Goldman actively mentors undergraduate researchers, with Oberlin students co-authoring 11+ publications since 2020. His lab receives support for computational infrastructure and genomic databases, enabling large-scale evolutionary analyses. Current projects include the LUCApedia Database and development of ancestral sequence reconstruction algorithms. The lab maintains active GitHub repositories for open-science collaboration. The Goldman Lab operates as a computational research hub within Oberlin's biology department, maintaining specialized resources including the LUCApedia Database and Simmerpop GitHub repository. The team collaborates with international researchers on NASA Astrobiology Institute-related projects and contributes to open-source tools for evolutionary analysis, with recent work featured in the Oberlin Research Review and covered by 27 news outlets including Popular Mechanics.

Akhil AroraView profile

Researcher

• Data Mining
• Graph Data Management
• Information Retrieval
• +4 more

Akhil Arora is a researcher at Aarhus University, Denmark, specializing in data mining, graph analytics, and information retrieval. His work focuses on scalable systems for network data analysis, Wikipedia navigation patterns, and influence propagation models. Current affiliations: Aarhus University (2025) Previous affiliations: EPFL (Switzerland), Xerox Research Centre India, IIT Kanpur Research Interests : Arora's research bridges graph data management, machine learning applications, and web-scale analytics. His recent projects include large-scale Wikipedia usage analysis and neural methods evaluation for entity alignment. Publication Trends : His work spans from 2014-2025 with consistent output in ACM SIGMOD/PODS conferences and affiliated venues, covering graph algorithms, influence maximization, and web interface design. Technical Contributions : Developed scalable systems for graph querying (RAQ), benchmarked influence maximization methods, and created synthetic data frameworks for Wikipedia navigation studies.

• Semantic Web
• Ontology-Based Data Access
• Knowledge Graphs
• +3 more

Martin Giese is affiliated with the University of Oslo (Department of Informatics) and the University Clinic Tübingen (Department of Cognitive Neurology). He is a researcher with a focus on semantic technologies, ontology-based data access, and visual query systems. Research Themes : Semantic Web, Ontology Engineering, Knowledge Graphs, Geological Informatics, Probabilistic Logic, Automated Reasoning Key Collaborations : Siemens, Statoil, Norwegian Petroleum Directorate, and various European research institutions Technical Contributions : Developed visual query systems (OptiqueVQS), ontology-driven geological modeling (GeoFault), and semantic data integration frameworks for industrial applications. His work spans both theoretical logic and practical implementations in big data environments. Publications : Recent articles focus on fault ontologies, process representation, and semantic embeddings. Earlier work includes foundational research in automated theorem proving and UML formalization.

• Database Systems
• Big Data Management
• XQuery Processing
• +3 more

Vinayak R. Borkar is a researcher and software engineer affiliated with the University of California, Irvine, where he completed his PhD in 2016. His work focuses on big data platforms, database systems, and scalable query processing frameworks. PhD in Big Data Processing (UC Irvine, 2016) Contributions to Apache AsterixDB, Hyracks, and Pregelix Industry experience at BEA Systems (2000s) Research interests include database systems , big data management , XQuery optimization , and dataflow engines . His publications analyze scalable similarity queries, memory management, and declarative approaches to machine learning. Recent articles explore Apache AsterixDB , dataflow compilation , and graph analytics . Collaborators include Michael J. Carey and Alexander Behm.

• Distributed Computing
• Database Systems
• Big Data
• +7 more

YongChul Kwon is a researcher affiliated with the University of Washington , focusing on distributed computing, database systems, and big data optimization. His work addresses critical challenges in MapReduce frameworks, including skew management, fault tolerance, and performance efficiency. Key research contributions include SkewTune for dynamic skew mitigation in MapReduce, SnipSuggest for SQL autocompletion, and comparative analyses of Hadoop's scalability. He has published in venues like VLDB , SIGMOD , and IEEE Data Engineering Bulletin , often collaborating with Magdalena Balazinska and Bill Howe. Recent work (2013–2016) explores iterative MapReduce frameworks, Hadoop's workload evolution, and parallel processing of scientific user-defined functions. Earlier contributions (2008–2010) include fault-tolerant stream processing, clustering algorithms for astrophysics, and collaborative query management systems. His research bridges distributed systems, database engineering, and scientific computing, with implications for cloud infrastructure and large-scale data analytics.

Elizabeth R. ThomasView profile

Researcher

• Paleoclimatology
• Ice Core Analysis
• Antarctic Climate Variability
• +3 more

Dr. Elizabeth R. Thomas is a leading paleoclimatologist at the British Antarctic Survey , head of the Ice Core Research team and the National Capability for Ice Core Acquisition and Analysis . She has led groundbreaking expeditions to drill the first sub-Antarctic ice cores (Balleny Islands, Peter 1st Island, Bouvet Island) and Antarctic deep ice cores. Principal Investigator for multiple NERC and Leverhulme grants (2018-2027) International collaborations with universities in Leeds, UCL, Cambridge, and St Andrews Contributor to IPCC AR6 climate projections Research Focus : Polar climate variability through ice core proxies (temperature, sea ice, westerly winds) over 2000 years. Key contributions include documenting 20th century snow accumulation that offset sea-level rise by ~10mm, and sea ice proxy reconstructions exceeding internal climate variability. Publications span Antarctic climate dynamics, including regional snow accumulation analysis and Holocene ice loss studies . Recent work integrates ice core chemistry with satellite firn observations. 2025 Science Bulletin : Antarctic oldest ice core analysis 2024 PNAS : Biomass burning reconstruction 2023 Earth System Science Data : Antarctic sodium/sulfate database Awards include the 2014 BAS Laws Prize , 2018 SCAR Weyprecht Lecture , and 2019 National Geographic Explorer recognition. Outreach : TED talks, BBC documentaries ( Ice Age: The Apocalypse ), and educational programs for Key Stage 2 children. She co-led the Sub-ICE expedition to preserve climate archives from remote islands.

Shani RossView profile

Associate Professor

• Neural Engineering
• Neuromodulation
• Biomedical Engineering
• +3 more

Shani Ross is an Associate Professor and Associate Chair for Undergraduate Programs in the Department of Bioengineering at George Mason University. She focuses on bladder neurophysiology and closed-loop neuroprosthetics. BSc Electrical Engineering, Howard University (2004) MS & PhD in Biomedical Engineering with bioelectrical concentration, University of Michigan (2006, 2013) Her research spans neural engineering, neuromodulation, and biomedical device development. Key areas include peripheral nerve stimulation, deep brain stimulation, and neuroprosthetics for restoring physiological function. Recent publications highlight work on graphene-based neural electrodes, decoding algorithms for bladder pressure estimation, pudendal neuromodulation effects on blood flow, and trigeminal nerve stimulation in equine models. Her work integrates computational methods with biomedical applications.