Find Academic Supervisors

• Enumerative Combinatorics
• Graph Theory
• Random Graphs
• +4 more

Juanjo Rué Perna is an Associate Professor at the Universitat Politècnica de Catalunya (UPC), holding a position in the Department of Mathematics . He also serves as Director of the CFIS (Centre de Formació Interdisciplinària Superior). Previously, he was a Juniorprofessor (Assistant Professor) at Freie Universität Berlin (2013-2016), affiliated with the Combinatorics and Graph Theory group. His academic journey includes postdoctoral positions at ICMAT (Madrid, 2010-2013) and École Polytechnique (France, 2009-2010). Rué obtained his PhD in Discrete Mathematics from UPC in 2009 under Marc Noy, focusing on the enumeration of topological graphs. His research interests span Enumerative Combinatorics , Graph Theory , Random Graphs , and Additive Combinatorics , with notable contributions to planar maps and asymptotic analysis. He has supervised four PhD students, including Clément Requilé and Christoph Spiegel. He has organized major conferences like EUROCOMB 2021 and authored books such as El arte de contar: Combinatoria y enumeración and academic works on transcendental numbers. Rué's work bridges theoretical mathematics with applications in quantum gravity and statistical physics, emphasizing interdisciplinary approaches.

Steve WolfmanView profile

Teaching Professor

• Computer Science Education
• Teaching Methodologies
• Educational Technology
• +3 more

Steve Wolfman is a Teaching Professor in the Department of Computer Science at the University of British Columbia (UBC), within the Faculty of Science. He specializes in computer science education, focusing on innovative teaching methods, curriculum development, and assessment tools. His work emphasizes pedagogical techniques such as autograding systems, adaptive learning platforms, and inclusive curricular design. Wolfman has received numerous awards for teaching excellence, including the Killam Teaching Prize and multiple UBC Department of Computer Science Teaching Awards. Wolfman has taught a wide range of courses, including introductory programming (CPSC 103, CPSC 110), data structures and algorithms (CPSC 221, CPSC 320), and operating systems (CPSC 313). He has also led the Interactive Digital Media Practicum (CPSC 491) and contributed to courses like Functional and Logic Programming (CPSC 312). His courses often incorporate modern educational technologies and active learning strategies. His research explores topics such as student assessment through autograding systems, leveraging tools like PrairieLearn, and improving educational outcomes through concept inventories and strength-based approaches. He has published extensively on pedagogical innovations, including inverted exams, kinesthetic learning, and the use of tablet PCs in classrooms. Wolfman is also involved in academic service, contributing to symposia like SIGCSE and fostering engagement through creative methods like the CS Parody Songs Filk Circle. Wolfman’s contributions extend to open-source educational platforms and collaborative projects, such as the Presenter System for tablet-based lectures and the Dictionary Wars project for teaching data structures. He advocates for inclusive education practices and has conducted action research to refine lab instruction and classroom dynamics.

Souyoung JinView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Cognitive Science
• +3 more

Souyoung Jin is an Assistant Professor in the Department of Computer Science at Dartmouth College. Her research focuses on Computer Vision, Machine Learning, and Cognitive Science with expertise in video understanding. She earned her B.S. from Dongguk University, M.S. from KAIST, Ph.D. from UMass Amherst, and completed a postdoc at MIT's CSAIL under Aude Oliva. She teaches courses like Machine Learning and Deep Learning, and leads research on AI systems mimicking human perception. Her lab explores multimodal tasks and synthetic data applications. She is an Area Chair for WACV 2025 and actively recruits motivated students for her lab. Education: B.S., Dongguk University M.S., Korea Advanced Institute of Science and Technology Ph.D., University of Massachusetts Amherst Postdoc, MIT Research Interests: Dr. Jin develops AI systems to understand human experiences through video analysis. Her work spans video understanding, synthetic data applications, and cognitive-inspired models. She emphasizes temporal context in low-resource regimes and cross-modal learning. Recent projects include BOLD Moments (fMRI-video datasets) and LangNav (language-based navigation). Grants & Labs: Her research is supported by grants focusing on synthetic video representations and multimodal fusion. She leads Dartmouth's Video Understanding Lab, fostering interdisciplinary collaborations between computer vision and cognitive science.

• Coding Theory
• Combinatorics
• Error-Correcting Codes
• +2 more

Anina Gruica is a Research Fellow in the Algebra group at the Technical University of Denmark (DTU), specializing in coding theory with emphases on density questions, combinatorial structures of error-correcting codes, and DNA-based data storage systems. Her work bridges theoretical mathematics and practical applications in next-generation storage technologies. Her research program centers on Coding Theory and Combinatorics, investigating the geometric and probabilistic properties of codes in metric spaces. Key interests include rank-metric codes, MRD codes, and combinatorial optimization for DNA storage efficiency, where she develops novel approaches to random access and coverage depth challenges through algebraic and geometric frameworks. Dr. Gruica's publication portfolio reveals a strong interdisciplinary trajectory, with increasing focus on DNA storage applications since 2022. Her work combines deep theoretical insights in combinatorial geometry with practical storage system design, resulting in high-impact publications across SIAM journals, IEEE conferences, and arXiv preprints that address both classical coding problems and emerging biological storage constraints. She has received competitive recognition including: ALCOCRYPT conference travel award (February 2023) DIAMANT PhD travel grant (2000 EUR, January 2023) DIAMANT visitor grant (1900 EUR, October 2021) SIAM Travel Award (August 2021) As co-organizer of the Postgraduate International Coding theory Seminar (PICS), Dr. Gruica actively mentors junior researchers while maintaining extensive collaborations with A. Ravagnani, J. Sheekey, and E. Yaakobi. Her conference presentations at venues like ISIT and SIAM AG23 demonstrate her leadership in translating theoretical advances to storage applications. She contributes to DTU's Algebra group research ecosystem, focusing on algebraic structures for coding theory and cryptography. Her current projects, evident from 2024-2025 preprints, explore combinatorial geometry for DNA storage efficiency and advanced rank-metric code constructions, positioning her at the forefront of coding theory's application to biological data systems.

Henk van der WorpView profile

Assistant Professor

• Urinary Incontinence
• Primary Health Care
• Overactive Bladder
• +6 more

Dr. Henk van der Worp is an Assistant Professor at the University of Groningen's Faculty of Medical Sciences, specifically within the Medicine, General & Internal discipline. He is affiliated with the University Medical Center Groningen (UMCG) and works within the Cure and Care in the Community Context (FOUR-C) research group. His academic profile demonstrates active engagement in clinical research with a focus on primary care medicine and evidence-based practice. Dr. van der Worp's research primarily centers on urinary incontinence, particularly in women, with significant contributions to understanding app-based treatments, cost-effectiveness analyses, and clinical pathways in primary care settings. His work also extends to sports medicine, specifically tendinopathy and injury prevention in athletes. He has developed expertise in systematic reviews, meta-analyses, and mixed-methods research approaches. His fingerprint analysis shows strong engagement with topics including Urine Incontinence (80%), Primary Health Care (48%), Tendinitis (100%), and Injury research (57%). Analysis of his recent publications reveals a clear trend toward digital health interventions for urinary incontinence, with numerous studies examining app-based treatments and their effectiveness compared to standard care. His work increasingly focuses on implementation science, examining how to integrate evidence-based practices into real-world primary care settings. He also maintains an active interest in sports medicine, particularly tendinopathy in athletes, showing the breadth of his research interests across different patient populations. Dr. van der Worp has supervised multiple students as indicated by the 'Supervised Work (3)' notation in his profile. His research has been supported by various grants, particularly for studies examining app-based interventions for urinary incontinence and tendinopathy management in athletes. He has collaborated extensively with researchers across the University Medical Center Groningen and with primary care practitioners throughout the Netherlands. He is actively involved with the FOUR-C (Cure and Care in the Community Context) research group at UMCG, which focuses on developing and evaluating interventions for common health problems in primary care settings. His work on the URinControl app demonstrates his commitment to translating research findings into practical tools for patients and healthcare providers. His recent involvement in systematic reviews and meta-analyses of overactive bladder treatments indicates expanding research interests into related urological conditions.

• Cryptography
• Wireless Communications
• Information Theory
• +3 more

Henri Hentilä serves as a Postdoctoral Researcher (Tutkijatohtori) within the Department of Information and Communications Engineering at Aalto University, actively contributing to the Visa Koivunen Research Group. His work bridges theoretical information theory with practical wireless security applications. His research expertise spans Information Theory , Cryptography , and Wireless Communications , with concentrated efforts on secret key generation for resource-constrained environments. Key methodologies include polar coding and finite blocklength analysis applied to physical layer security, particularly for Internet of Things (IoT) networks where computational limitations demand innovative cryptographic solutions. Publication analysis (2016-2024) reveals a consistent trajectory toward optimizing secure communication in wireless channels, evolving from cognitive radio scheduling to cutting-edge second-order bounds for key generation. His work demonstrates increasing specialization in information-theoretic security protocols for IoT, with polar coding emerging as a unifying technical thread across eight recent publications. Scientific awards: No awards were documented in the source material. Regarding academic mentorship and funding, the provided text contains no references to student supervision, research grants, or collaborative projects beyond his core affiliation with the Visa Koivunen Group. He operates within the Visa Koivunen Research Group, which maintains a strong focus on signal processing innovations for next-generation wireless communication systems, particularly emphasizing information-theoretic approaches to security and network optimization.

• Global Mental Health
• Depression Treatment
• Public Health Interventions
• +5 more

Ricardo Araya is a Professor in the Department of Population Health at the London School of Hygiene & Tropical Medicine (LSHTM), Faculty of Epidemiology and Population Health. His research spans multiple continents with significant contributions to global mental health, particularly in low- and middle-income countries including Chile, Zimbabwe, Nigeria, and India. London School of Hygiene & Tropical Medicine (2012-present) Extensive collaborative work with institutions in Chile, Africa, and South Asia Principal investigator on multiple international mental health trials Araya's research focuses on innovative approaches to mental health service delivery in resource-limited settings, with particular emphasis on depression treatment. His work explores task-shifting models where non-specialists deliver evidence-based psychological interventions, school-based mental health programs, and digital mental health solutions. He has made significant contributions to understanding the implementation challenges and effectiveness of mental health interventions across diverse cultural contexts, with a strong commitment to generating evidence that can inform policy and practice in global mental health. His publication record shows a consistent focus on depression treatment and prevention across different populations and settings. The research demonstrates methodological rigor with numerous randomized controlled trials, meta-analyses, and implementation studies. His work often addresses the intersection of mental health with other social determinants and health conditions, including HIV, substance use, and adolescent development. Araya has received recognition through substantial research funding and extensive international collaboration. His work has influenced mental health policy and practice in multiple countries, particularly through the development and testing of scalable interventions that can be implemented in primary care and community settings. As a mentor and collaborator, he has worked with numerous early-career researchers across multiple continents, contributing to capacity building in global mental health research. His leadership in initiatives like LATIN-MH demonstrates commitment to strengthening research infrastructure in low- and middle-income countries.

Douglas RizzoloView profile

Associate Professor

• Probability Theory
• Combinatorics
• Stochastic Processes
• +3 more

Douglas Rizzolo is an Associate Professor in the Department of Mathematical Sciences at the University of Delaware, part of the College of Arts & Sciences. His research focuses on the large-scale structure of random combinatorial objects, including diffusions on combinatorially structured spaces and the behavior of pattern-avoiding permutations. He has contributed to interdisciplinary areas such as probability theory, stochastic processes, and mathematics education. Research Interests: Rizzolo’s work explores random combinatorial structures , diffusions on discrete spaces , and pattern-avoiding permutations . He investigates how these structures behave at macroscopic scales, often employing techniques from probability theory and combinatorics. His recent projects include studies on Aldous diffusions, Galton-Watson trees, and interval partition evolutions. Publications: His articles span topics like measure-valued diffusions, stochastic sandpile models, and educational practices in calculus instruction. Key themes include scaling limits , stationary distributions , and combinatorial dynamics . A common thread is the interplay between discrete structures and continuous stochastic processes. Awards: No scientific awards are explicitly listed in the provided texts. Grants/Advising: No specific grants or advisee names are mentioned, though his research likely involves collaborative projects given the interdisciplinary nature of his work. Labs/Teams: While no lab affiliations are specified, his involvement with the Department of Mathematical Sciences suggests participation in university research groups focused on probability and combinatorics.

• Computational Complexity
• Cryptography
• Theoretical Computer Science
• +3 more

Manuel Blum is the Bruce Nelson Professor of Computer Science at Carnegie Mellon University's School of Computer Science, Department of Computer Science. He is renowned for foundational contributions to computational complexity, cryptography, and theoretical computer science. His work includes pioneering research on CAPTCHAs, human computation, and self-testing programs. Blum has collaborated extensively with figures like Luis von Ahn, contributing to projects like Peekaboom and Verbosity. His research also extends to philosophical inquiries into consciousness, blending computer science with neuroscience and philosophy. Blum's teaching includes courses on theoretical cryptography (15-503) and undergraduate complexity theory (15-455). He has advised students such as Brendan Juba and Matt Humphrey, whose work explores computational complexity and related fields. His research spans grants on machine learning, game theory, and computational complexity, including an NSF proposal on understanding concept understanding. Blum's contributions to security, randomness, and algorithm design have had lasting impacts on computer science.

Connor Wilson ColeyView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Cheminformatics
• +4 more

Connor W. Coley is the Class of 1957 Career Development Professor and Associate Professor at MIT, with joint appointments in the Department of Chemical Engineering and the Department of Electrical Engineering and Computer Science. He is also affiliated with the Schwarzman College of Computing. He holds a B.S. in Chemical Engineering from Caltech, a Ph.D. from MIT, and completed postdoctoral training at the Broad Institute. His research integrates AI, chemistry, and automation to accelerate molecular design and reaction discovery. Key focus areas include: AI-driven synthesis planning and reaction prediction Machine learning for molecular property optimization Laboratory automation and high-throughput experimentation Therapeutic discovery and bioisosteric drug design His work bridges computational models with experimental validation. His publications emphasize machine learning in chemistry, with recent trends in generative models for molecular design, reaction mechanism prediction, and autonomous experimentation. Key themes include improving model generalizability, addressing data biases, and enhancing synthesizability predictions. Scientific Awards & Honors: NSF CAREER Award (2021) Forbes 30 Under 30: Healthcare (2019) Camille Dreyfus Teacher-Scholar (2025) MIT Common Ground Award for Excellence in Teaching (2023) James W. Swan Outstanding Faculty Award (2024, 2025) He leads the Coley Research Group, advising 18+ graduate students and postdocs. His team develops open-source tools like ASKCOS for synthesis planning and collaborates with industry partners (e.g., Sanofi). The group leverages robotic platforms for high-throughput experimentation and maintains active projects in retrosynthesis, metabolomics, and polymer design.

Ron DoView profile

Professor

• Computational Biology
• Genomics
• Human Genetics
• +5 more

Dr. Ron Do is a full Professor with Tenure in the Department of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai, serving as the founding Director of the Center for Genomic Data Analytics within The Charles Bronfman Institute for Personalized Medicine. He holds the endowed Charles Bronfman Professorship in Personalized Medicine. His research focuses on computational genetics and large-scale genomic data analysis to elucidate disease mechanisms, with expertise in human genetics, statistical genetics, and omics integration. Education includes: B.Sc. in Cell Biology and Genetics (University of British Columbia) M.Sc. in Experimental Medicine (University of British Columbia) Ph.D. in Human Genetics (McGill University) Postdoctoral Fellowship (Banting CIHR) and Instructorship in Medicine at Harvard Medical School/Massachusetts General Hospital Research interests span computational biology, cardiovascular genomics, epigenetics, and systems biology, with a focus on leveraging genomic and clinical data to advance precision medicine. Key projects include genome-wide association studies, polygenic risk scoring, and machine learning-driven disease prediction. Notable awards include the Dr. Harold and Golden Lamport Clinical Research Award for junior faculty excellence and the Canadian Institutes of Health Research Banting Postdoctoral Fellowship. His lab (Do Lab) develops innovative methods for genomic data analysis and integrates electronic health records with genomic datasets to improve disease understanding and clinical outcomes. Grants and collaborations involve large-scale genomic initiatives such as the Trans-Omics for Precision Medicine (TOPMed) Program and multi-ancestry studies. He leads teams in translational research, bridging computational methods with clinical applications in cardiovascular, metabolic, and ophthalmic disorders.

• Causal Inference
• Machine Learning
• Social Media Analysis
• +3 more

Prof. Drew Dimmery is the Professor of Data Science for the Common Good at the Hertie School's Data Science Lab. He holds a PhD in Politics from New York University (2016), with a focus on causal inference and machine learning. Prior to joining Hertie, he served as Scientific Coordinator at the University of Vienna’s Data Science Research Network (2021–2023) and worked on Facebook’s Core Data Science team (2016–2020), developing experimentation tools and methods. His research emphasizes methodological innovation in causal inference and machine learning, particularly applied to social media and internet studies. Key areas include experimental design, algorithmic transparency, and policy applications of data science. He has published in top-tier journals like ICML, KDD, and Science, and his work bridges computational methods with societal challenges such as electoral integrity, digital governance, and public welfare provision. Recent publications analyze the impact of social media platforms on elections, user behavior, and mental health, leveraging large-scale experimentation and causal analysis. His endowed professorship, supported by the Dieter Schwarz Foundation, includes scholarships for the Master of Data Science for Public Policy program, reflecting his commitment to applying data science for societal benefit.

• Networking
• Communications
• Cybersecurity
• +5 more

Martin Reisslein is a Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His research focuses on advanced networking technologies, cybersecurity, and edge computing, with a specialization in Time-Sensitive Networking (TSN), 5G, and network coding. He collaborates closely with institutions like the National Research Data Infrastructure (NFDI) and has published extensively in top-tier journals and conferences. His work spans theoretical and applied domains, including hardware-software co-design for low-latency systems, cybersecurity for satellite and IoT networks, and AI-driven resource management in transportation networks. Recent projects highlight contributions to TSN testbeds, molecular communication simulations, and unified threat management systems for home networks. Reisslein has co-authored over 270 publications, with notable contributions in IEEE Transactions on Networking, Communications Surveys & Tutorials, and the Journal of Signal Processing Systems. His research emphasizes practical implementations, such as hardware-aligned TSN simulations and flexible measurement frameworks for edge computing.

Niek MoonenView profile

Assistant Professor

• Electromagnetic Interference
• Power Electronics
• Renewable Energy
• +4 more

Niek Moonen is an Assistant Professor at both the Digital Society Institute and Radio Systems. His research focuses on electromagnetic compatibility (EMC), power electronics, renewable energy systems, and microgrid technology. He has contributed extensively to understanding conducted electromagnetic interference (EMI), power quality, and energy access solutions in remote and off-grid systems. His work addresses challenges such as EMI mitigation in power electronic converters, optimizing microgrid performance under rapid load changes, and improving energy meter robustness against EMI. Moonen has been recognized with awards including the Richard B. Shultz Best Transaction Paper Award (2023) and multiple Distinguished Reviewer accolades from IEEE Transactions on Electromagnetic Compatibility (2020–2025). Research interests include the interplay between supply and demand quality in off-grid systems, EMC in marine and aerospace applications, and the development of cost-effective monitoring tools for energy access initiatives. His contributions span theoretical analysis, experimental validation, and practical solutions for sustainable energy systems.

Sebastian SpäthView profile

Professor

• Technology and Innovation Management
• Digital Platforms
• Open Innovation
• +5 more

Prof. Dr. Sebastian Späth is the Chair of Business Administration/Digital Markets at the University of Hamburg , affiliated with the Faculty of Economics and Social Sciences and Department of Social Economics . He teaches general business administration, strategy, knowledge management , and innovation management . Since 2013, he has led research on collaborative innovation, digitalization of society , and technology platforms . He served as Program Director for the Bachelor's program in Social Economics from 2021–2025. Education : Karlsruhe Institute of Technology (Industrial Engineering) Linköping University of Technology (Master of Science) University of St. Gallen (Doctor in Business Administration) Research Interests : Technology and innovation management, focusing on cross-company collaboration Digital platforms and network effects in smart home ecosystems Open innovation in peer production systems (e.g., Open Source Software/Hardware) Privacy challenges in digital economies Publications : His work appears in Research Policy , Management Science , and Strategic Management Journal , with recent trends exploring AI-driven finance, platform interoperability, and 3D printing's impact on manufacturing. Team & Lab : He leads the Management & Digital Markets team, including researchers like Karsten Wenzlaff , Tobias Werner , and Dr. Ufuk Pala , with administrative support from Alexandra Christiansen .