Find Academic Supervisors

• Medical Image Reconstruction
• Computed Tomography
• Positron Emission Tomography
• +6 more

Professor Jerome Liang is a distinguished faculty member at Stony Brook University's Renaissance School of Medicine, holding professorships in Radiology, Biomedical Engineering, Electrical and Computer Engineering, and Computer Science. He serves as Co-Director of Radiology Research and has established himself as a leading expert in medical imaging reconstruction techniques. Dr. Liang's educational background includes a Ph.D. in Physics from City University of New York, postdoctoral training at Duke University, and fellowship at Albert Einstein College of Medicine. His undergraduate degree in Modern Physics was obtained from Lanzhou University in China. His primary research interests focus on advanced medical imaging techniques, particularly low-dose computed tomography image reconstruction, quantitative SPECT reconstruction, high-resolution PET imaging, tissue segmentation from multi-spectral images, computer-aided diagnosis systems, and virtual colonoscopy development. His work bridges engineering principles with clinical applications to improve diagnostic imaging capabilities while reducing radiation exposure. Analysis of his recent publications reveals a strong focus on machine learning applications in medical imaging, particularly in polyp classification, dual-energy CT spectral analysis, and virtual endoscopy. His research consistently aims to enhance diagnostic accuracy while optimizing radiation dose and improving visualization techniques for various medical conditions. 1981 China-US Physics Examination and Application Program (CUSPEA) Winner (Top 25 among 250,000 candidates) 1990 NIH First Investigator Award 1996 American Heart Association Established Investigator Award 1996 Radiological Society of North America Certificate of Merit Award 2002 SUNY Chancellor's Entrepreneur Award 2007 IEEE Society Fellow 2011-2013 SBU, BNL and CSHL Certificates of Excellence in Research and Invention 2013 Stony Brook School of Medicine Award for Excellence in Translational Research Dr. Liang has secured significant research funding including NIH/NCI R01 grants for "Advanced Virtual Colonoscopy for Early Cancer Screening" and "Radiogenomics of Colorectal Polyps." He currently leads active protocols including IRB 93995-MODCR005 focused on integrating virtual and optical colonoscopies with pathological analysis. His laboratory (IRIS - Imaging Research and Informatics) continues to advance medical imaging technology while mentoring the next generation of researchers in this critical field.

Chin Hoong ChorView profile

Professor

• Transportation Systems Modelling
• Transportation Safety
• Congestion Management
• +6 more

Professor Chin Hoong Chor is a Professor in the Department of Civil Engineering at the National University of Singapore (NUS), affiliated with the Faculty of Engineering. He specializes in transportation systems modeling, safety assessment, and congestion management. As a registered professional engineer and road safety auditor, he has contributed to numerous projects with Singapore’s land authorities and private companies. He holds leadership roles including Vice Chairman of the Chartered Institute of Logistics and Transport and Editorial Board membership for the International Journal of Transport Management. Qualifications include a BEng and MEng from NUS and a PhD in Transportation Engineering from the University of Southampton. His research interests span vehicle detection using image processing, traffic conflict analysis, and public transport optimization. Notable awards include the NUS Faculty Innovative Teaching (Gold) Award (2001/2002) and the UK Institution of Civil Engineers Webb Prize (2003). Education: BEng in Civil Engineering, National University of Singapore MEng in Civil Engineering, National University of Singapore PhD in Transportation Engineering, University of Southampton His research focuses on quantitative safety analysis, traffic flow modeling, and smart city initiatives. Recent work explores maritime collision risk modeling and sentiment analysis for transportation planning. He actively contributes to government committees and has authored over 40 peer-reviewed papers on traffic management and safety. Awards: Faculty Innovative Teaching (Gold) Award, 2001/2002 UK Institution of Civil Engineers Webb Prize 2003 Prof Chin has undertaken traffic impact studies and road safety reviews in Singapore, collaborating with public and private sectors. His work bridges academic research and practical policy implementation, emphasizing sustainable urban mobility solutions.

Zakir DurumericView profile

Assistant Professor

• Internet Security
• Cybersecurity
• Network Measurement
• +7 more

Zakir Durumeric is an Assistant Professor of Computer Science at Stanford University, leading the Stanford Empirical Security Research Group. His research focuses on Internet security, trust, and safety, emphasizing large-scale network measurement and open-source tool development. He founded Censys, a platform providing global Internet device data, and maintains tools like ZMap, ZGrab, and Retina. Research interests include cybercrime prevention, censorship analysis, disinformation tracking, and platform governance for online harassment. Notable contributions include studies on the Mirai botnet, TLS certificate ecosystems, and vulnerabilities like Heartbleed and Logjam. Awards include the IRTF Applied Networking Research Prize (2015) and a Test of Time Award (2022). Teaches courses: CS155 (Computer & Network Security), CS356 (Systems & Network Security), and CS249i (Modern Internet). Advises over 20 students, including Catherine Han, Kimberly Ruth, and Liz Izhikevich. Develops open-source software such as ZMap Toolkit and ASdb, and maintains datasets like CrUX Top Million Websites. Recent work explores toxic online behavior, misinformation ecosystems, and regional censorship mechanisms in China. His lab’s tools are widely adopted in academia and industry for security research and policy guidance.

Reuben BinnsView profile

Associate Professor

• Data Protection
• Machine Learning
• AI Ethics
• +5 more

Dr. Reuben Binns is an Associate Professor of Human Centred Computing at the University of Oxford , where he investigates intersections between computer science, law, and philosophy. His research focuses on data protection , machine learning ethics , and regulation of technology .

Tengfei MaView profile

Assistant Professor

• Machine Learning
• Natural Language Processing
• Biomedical Informatics
• +6 more

Tengfei Ma is an Assistant Professor in the Department of Biomedical Informatics at Stony Brook University, with affiliations to Computer Science and Applied Mathematics & Statistics. He holds a Ph.D. from The University of Tokyo, M.S. from Peking University, and B.E. from Tsinghua University. Previously, he was a Research Scientist at IBM T.J. Watson Research Center. His research focuses on machine learning, natural language processing (NLP), and biomedical informatics, particularly deep graph learning, scalable graph methods, and healthcare applications. He has contributed to frameworks like EvolveGCN for dynamic graphs and IGB datasets for graph benchmarks. Key awards include ISWC 2021 Best Paper (Research Track) and IBM Outstanding Research Accomplishments (2019, 2022). His work bridges theory and practice, addressing challenges like over-dilution in GNNs and interpretable time series analysis. Collaborations span interdisciplinary areas, such as AI for wound monitoring and code summarization. He teaches BMI530: Software Development for Biomedical Informatics and is open to graduate students from CS, BMI, and AMS departments. Research highlights include: Deep Graph Learning: Scalability (FastGCN, IGB), dynamic graphs (EvolveGCN), and topology-enhanced GNNs. Healthcare: Models for EHR analysis, medication recommendation (GAMENet), and wearable wound monitoring. NLP: Document summarization, code summarization (CP-BCS), and commonsense generation via knowledge graph compression. Recent projects include AI tools like Influencer for promotional content creation and neural-symbolic models for interpretable time series analysis. His lab explores foundational AI for healthcare, code analysis, and graph systems.

• Computational Sociology
• Gender Studies
• Social Movements
• +4 more

Laura K. Nelson is an Associate Professor of Sociology at the University of British Columbia , where she also directs the Centre for Computational Social Science . Her work bridges computational methods with sociological inquiry, focusing on gender inequality, social movements, and organizational dynamics. She previously held faculty roles at Northeastern University and affiliated with institutions like the NULab for Texts, Maps, and Networks and the Network Science Institute . Education: PhD in Sociology (2014), University of California, Berkeley MA in Sociology (2009), University of California, Berkeley BA in Sociology (2006), University of Wisconsin-Madison (Phi Beta Kappa) Research Interests span computational sociology, social movement strategy, intersectionality, and STEM equity. She pioneered frameworks like computational grounded theory and radical objectivity , integrating machine learning with qualitative paradigms. Recent publications analyze gender dynamics in emergency medicine, feminist movement histories, and the NSF ADVANCE program’s impact on equity. Her 2024 Social Science Quarterly paper quantifies ADVANCE’s interdisciplinary reach. Awards include the 2020 Best Meta-Reviewer at SocInfo20 and Outstanding Faculty of the Year at Northeastern University. She serves on editorial boards for American Journal of Sociology , Poetics , and Acta Sociologica . She co-PIs a National Science Foundation grant studying gender-equity dissemination in higher education networks and supervises graduate student Jinyang Yu . Her lab, Centre for Computational Social Science , drives open-source methodological innovation.

Mattias GassmanView profile

Assistant Professor

• Late Antique Studies
• History of Christianity
• Roman Religion
• +3 more

Mattias Gassman is an Assistant Professor of Humanities at the University of Florida's Hamilton School for Classical and Civic Education. His research focuses on the transformation of Roman religious ideas by Christianity, particularly in late antiquity. Previously, he held postdoctoral fellowships at the University of St. Andrews and the University of Oxford. He earned a PhD in Classics from the University of Cambridge (2017), and prior degrees from Oxford, Minnesota, and Iowa State University. His research emphasizes critical analysis of modern concepts like 'paganism' and 'secularity' through ancient lenses. His first monograph, Worshippers of the Gods (Oxford, 2020), examined fourth-century Roman religious debates. His current book project, Citizens of the Earth , analyzes Augustine's engagement with Roman religion across his works. He also co-authored a general-audience textbook on fourth- and fifth-century theological controversies. His articles explore topics such as Augustine's anti-pagan rhetoric, late antique preacher techniques, and the reception of classical texts. Recent publications appear in Journal of Early Christian Studies , Historia: Zeitschrift für Alte Geschichte , and Augustinian Studies . He teaches courses on ancient texts and religious history, including Immortality (Quest 1) and Great Books of the Ancient World .

• Artificial Intelligence in Healthcare
• Biomedical Engineering
• Traditional Chinese Medicine Informatics
• +3 more

Dr. Jing Wang is a Professor in the Department of Bioinformatics at Southern Medical University's School of Medicine, with extensive research at the intersection of artificial intelligence and biomedical applications. Her work demonstrates strong cross-disciplinary collaboration across medical institutions, engineering departments, and computer science research groups. Her primary research interests include Artificial Intelligence in Healthcare , Biomedical Engineering , and Traditional Chinese Medicine Informatics , with recent publications showing particular expertise in medical imaging analysis, diagnostic assistance systems, and clinical decision support. Her work spans both theoretical algorithm development and practical clinical implementations. Analysis of her 15 most recent publications (2025-2026) reveals a strong trend toward clinically applicable AI systems, with approximately 60% of publications focused on medical diagnostics and treatment support systems. The remaining publications demonstrate expertise in industrial applications of computer vision and fundamental AI research. Her work shows consistent collaboration with both domestic Chinese institutions and international research groups. Notable scientific contributions include: Development of 'Tianyi', a traditional Chinese medicine language model for clinical practice Innovations in bionic soft robotics for rehabilitation assistance Novel approaches to medical image analysis for cancer diagnostics Her research program appears well-funded with consistent publication output across high-impact journals in biomedical engineering, AI, and medical informatics. Current work suggests strong emphasis on translating AI research into clinical practice, particularly in diagnostic support systems and rehabilitation technology.

Pengfei WangView profile

Assistant Professor

• Geotechnical Engineering
• Engineering Seismology
• Applied Statistics
• +4 more

Pengfei Wang is an Assistant Professor in the Department of Civil & Environmental Engineering at Old Dominion University (ODU). He holds a Ph.D. in Geotechnical Engineering and an M.S. in Statistics from UCLA, alongside a B.S. in Transportation Engineering from Tongji University. Prior to ODU, he conducted postdoctoral research at UCLA. His expertise focuses on Geotechnical Engineering , Engineering Seismology , and Applied Statistics , with emphasis on regional geo-hazard modeling, multi-hazards risk assessment, and statistical learning applications. Key research interests include seismic site response analysis, liquefaction susceptibility, and probabilistic risk frameworks for infrastructure resilience. Dr. Wang’s work integrates geospatial analysis and statistical methodologies to address challenges in earthquake engineering. He has developed frameworks for regional landslide and liquefaction risk assessments, particularly in vulnerable regions like California’s Sacramento-San Joaquin Delta. His contributions include advancing HVSR (Horizontal-to-Vertical Spectral Ratio) methodologies and ergodic site response modeling. He maintains active collaborations with institutions globally and contributes to open-source databases for seismic data, promoting transparency and reproducibility in geotechnical research. His educational background in transportation engineering enriches interdisciplinary approaches to civil infrastructure resilience.

Gert-Martin GreuelView profile

Professor

• Singularity Theory
• Computer Algebra
• Algebraic Geometry
• +3 more

Prof. Gert-Martin Greuel is a distinguished mathematician and Emeritus Professor at RPTU Kaiserslautern, where he previously held a Professorship in the Department of Mathematics. His career includes roles as Director of the Mathematisches Forschungsinstitut Oberwolfach (2002-2013) and as editor of major journals like Zentralblatt MATH. He co-founded the Singular computer algebra system and led the Center for Computer Algebra at Kaiserslautern. Research Interests: His work focuses on singularity theory, algebraic geometry, and computational algebra. Key contributions include foundational studies on hypersurface singularities, equisingularity, and the development of mathematical software tools like Singular and swMATH. Awards: Greuel received the Richard D. Jenks Prize (2004) for Singular, an honorary doctorate from Leibniz University Hannover (2009), and the German Mathematical Society's Media Prize (2013). He pioneered public math exhibitions through the IMAGINARY project. Leadership & Outreach: He served as Chair of European Research Centres on Mathematics (2010-2013) and championed open-access initiatives for mathematical software and publications. His editorial roles span Oberwolfach Reports, Revista Matemática Complutense, and Ergebnisse series. Education: PhD (1973) and Habilitation (1980) from University of Göttingen and Bonn, respectively. His academic journey includes professorships in Osnabrück and Kaiserslautern, and supervision of over 20 PhD students in algebraic geometry and computational mathematics.

Rikky MullerView profile

Associate Professor

• Neural Engineering
• Medical Devices
• Low-Power Electronics
• +6 more

Rikky Muller is an Associate Professor of Electrical Engineering and Computer Sciences at UC Berkeley, holding the S. Shankar Sastry Professorship in Emerging Technologies. She is Co-director of the Berkeley Wireless Research Center (BWRC), a Core Member of the Center for Neural Engineering and Prostheses (CNEP), and an Investigator at the Chan-Zuckerberg Biohub. Her research focuses on implantable/wearable medical devices, low-power wireless systems, and neurotechnology for neurological applications. Education: PhD (2013), UC Berkeley; BS and M.Eng. (2004), MIT, all in EECS. Prior roles include IC designer at Analog Devices and co-founder of Cortera Neurotechnologies (acquired). Research interests include neural interfaces, closed-loop neuromodulation, and biomedical microelectronics. Notable contributions include Neural Dust (ultrasonic implants), wireless EEG systems, and seizure prediction hardware. Awards: MIT TR35 Innovator, NAE Gilbreth Lectureship, NSF CAREER Award, IEEE SSCS New Frontier Award Grants: Bakar Fellows, Hellman Fellowship, NSF CAREER Labs: Muller Lab (UC Berkeley EECS), Chan-Zuckerberg Biohub collaborations

Michael AlfaroView profile

Professor

• Evolutionary Biology
• Marine Fishes
• Phylogenetics
• +3 more

Dr. Michael Alfaro is a Professor in the Department of Ecology and Evolutionary Biology at UCLA, where he leads the UCLA Alfaro Lab. His research focuses on understanding evolutionary dynamics of organismal diversification, particularly in marine fishes. He employs interdisciplinary approaches combining evolutionary morphology, molecular phylogenetics, and theoretical evolution to explore patterns and mechanisms of morphological and functional diversity. Education: Ph.D. in Evolutionary Biology, University of Chicago (2000) M.A. in Biology, Humboldt State University (1995) B.A. in Dramatic Arts, University of California, Davis (1989) Research interests emphasize the interplay between morphological diversity and ecological/functional dynamics. Notable themes include the drivers of diversification in marine lineages, the role of physiological traits in lineage success, and the integration of computational tools for large-scale phenotypic analysis. Alfaro has contributed to advancements in phylogenetic methodology and genomic resources for studying fish evolution. His work bridges macroevolutionary theory with empirical data, often leveraging crowdsourced phenotypic data and bioinformatics tools like Sashimi and Charisma for high-throughput analysis. The lab actively engages in collaborative projects addressing biodiversity patterns and evolutionary mechanisms across marine and terrestrial systems. Grants and advising activities are central to his academic contributions, though specific details are not detailed in the provided text. The UCLA Alfaro Lab collaborates internationally, emphasizing both basic research and applied conservation contexts.

Claude DELPHAView profile

Professor

• Signal Processing
• Fault Diagnosis and Prognosis
• Electrical Engineering Systems
• +4 more

Claude DELPHA is a Full Professor at Université Paris Saclay, affiliated with CentraleSupélec’s Laboratoire des Signaux et Systèmes (L2S). He holds an IEEE Senior Member status and has been with L2S since 2001. His expertise spans signal processing, fault diagnosis, electrical engineering systems, and machine learning. He leads the Modelling and Estimation team (GME) at L2S and oversees engineering admissions at Polytech Paris Saclay. Education: PhD in Instrumentation & Measurements and Signal Processing from Université de Metz, with a focus on intelligent sensor systems. Graduate degree in Electrical and Signal Processing Engineering. Research Interests: Multidimensional/statistical signal processing, fault diagnosis/prognosis (modeling, detection, estimation), electrical systems (drives, converters, PV), data hiding (watermarking), and pattern recognition (machine/deep learning). Active in energy systems, industry 4.0, and health/biology applications. Professional Roles: Director of GME research team, Polytech admissions lead, member of Polytech’s executive and academic boards, and IUT department council member. Engaged in labs like SYCOMORE and ILOCOS. Publications: Over 200 works since 2015, focusing on fault diagnosis in electrical systems, photovoltaic modules, bearings, and tidal turbines. Key methods include Kullback-Leibler divergence, Jensen-Shannon divergence, Mahalanobis distance, and PCA-based approaches. Awards: Not explicitly listed in provided texts.

Heather TaylorView profile

Assistant Professor

• Health services research
• Mental health
• Oral health disparities
• +2 more

Dr. Heather Taylor is an Assistant Professor in the Department of Health Policy and Management at Indiana University Fort Wayne, within the School of Public Health. She holds a PhD in Health Policy and Management from the Fairbanks School of Public Health and an MPH and RDH (Registered Dental Hygienist). Her career spans clinical practice as a dental hygienist, teaching at the Indiana University School of Dentistry, and community outreach through programs like SEAL Indiana, which provides preventive dental care to underserved children. Currently, her research focuses on oral health disparities, mental health, and the oral-systemic relationship, with a particular interest in improving access to dental care for low-income populations. Dr. Taylor’s educational background includes a PhD and MPH from Indiana University, complemented by a dental hygiene license and teaching experience in dental radiology. She has held a National Library of Medicine Fellowship in Population and Public Health Informatics (2017–2021). Her research portfolio includes over 14 peer-reviewed publications, addressing topics such as healthcare costs, social determinants of health, and the economic burden of untreated mental illness in Indiana. Her courses include PBHL-H325: Health Information Technology Management and Policy. She collaborates on projects exploring dental informatics, such as health information exchange during dental visits and the role of natural language processing in social work interventions. Her work bridges clinical practice, public health policy, and health informatics to address systemic inequities in healthcare access. Awards: National Library of Medicine Fellow (2017–2021) Grants/Projects: Ongoing work on economic burdens of mental illness in Indiana Her affiliations include Indiana University Fort Wayne and collaborations with state public health initiatives. She contributes to community outreach and policy advocacy for oral health equity.

Oliver GasserView profile

Researcher

• Internet Measurement
• IPv6
• BGP
• +9 more

Oliver Gasser is a researcher at the Max Planck Institute for Informatics (MPI-INF) and the Technical University of Munich (TUM), where he has co-lectured courses such as Advanced Computer Networking and Master Course Computer Networks. His research focuses on Internet measurement, security, and privacy, with a strong emphasis on IPv6, DNS, BGP, and web tracking technologies. His research interests include Internet measurement, IPv6 deployment, BGP security, DNS infrastructure, web tracking, privacy technologies, and network resilience. He has made significant contributions to understanding IPv6 hitlists, router fingerprinting, hypergiant content delivery networks, and consent banner manipulation on the web. His work combines large-scale active measurements with data analysis to uncover systemic issues in Internet infrastructure and privacy practices. The recent publications highlight a consistent focus on measurement-driven research across networking, security, and privacy. Trends include analyzing IPv6 adoption patterns, detecting covert tracking mechanisms in web cookies, evaluating security of Internet protocols like DNS and BGP, and improving measurement methodologies for large-scale network studies. His work often involves developing open tools and datasets that advance reproducibility in networking research. PAM 2023 Best Paper Award TMA 2023 Best Paper Award TMA 2023 Fast Track Award PAM 2018 Best Paper Award IRTF Applied Networking Research Prize 2018 IMC 2017 Community Contribution Award TMA 2017 Best Dataset Award CoNEXT 2023 Community Contribution Award Oliver Gasser has advised or co-advised over 40 master’s and bachelor’s theses at MPI-INF and TUM, demonstrating strong mentorship in academic research. He has led several measurement projects that have received external funding, including development of the IPv6 Hitlist Service and tools for analyzing web tracking. His community service includes extensive participation in program committees for major networking conferences such as IMC, CoNEXT, PAM, and TMA. He leads and contributes to several open research initiatives including the IPv6 Hitlist Service, SNMPv3 Measurement Service, MPTCP Measurement Service, DNS Observatory, and the BannerClick tool for automated cookie banner interaction. These platforms provide valuable resources for the global networking research community and support reproducible science.