Find Academic Supervisors

• Applied Statistics
• Geology
• Materials Science
• +3 more

Dr. Eleanor Stillman is a Senior Lecturer in Probability & Statistics at the School of Mathematical and Physical Sciences, University of Sheffield, where she has been a faculty member since 1987 after completing both her BSc and PhD at the institution. Her career exemplifies deep institutional commitment and interdisciplinary impact across scientific domains. Her educational foundation at Sheffield enabled her specialization in applied statistics, with research focusing on geological and archaeological applications (particle size modeling for sediment transport and cereal landrace analysis) and materials science (composite strength, glaze design, manufacturing process control). She also pioneers statistical education through computer-assisted learning tools and studies on school-university transitions. Analysis of her 2016-2024 publications reveals three dominant threads: archaeological morphometrics (geometric analysis of ancient grains), industrial quality control (multivariate monitoring of tool wear and manufacturing), and biological/educational applications (zebrafish breeding statistics, school outreach programs). This demonstrates remarkable versatility in solving real-world problems from prehistoric agriculture to modern industry. Her professional recognition includes: Chartered Statistician designation from the Royal Statistical Society Dr. Stillman has secured significant research funding as Coinvestigator on EPSRC grants including Simulation Tools for Automated and Robust Manufacturing and Quantitative characterisation of particle clustering in MMCS . She actively shapes statistical practice through service on the University's MASH steering committee and as an Associate Consultant to the Statistical Services Unit for training and ethical review. Within the School, she contributes to the Mathematical and Statistical Modelling research group, which drives collaborative projects bridging theoretical statistics with geological, archaeological, and industrial challenges.

Dongkuan XuView profile

Assistant Professor

• Machine Learning
• Natural Language Processing
• Computer Vision
• +7 more

Dongkuan Xu is an Assistant Professor in the Department of Computer Science at North Carolina State University, leading the Generative Intelligent Computing (GIC) Lab. His research spans Artificial Intelligence , focusing on scalable, efficient, and reliable AI systems for large language models, diffusion models, and generative frameworks. Education Ph.D. in Computer Science, Pennsylvania State University (2022) M.S. in Optimization and Data Mining, University of Chinese Academy of Sciences (2017) B.E. in Information Management and System, Renmin University of China (2014) His research explores test-time adaptation, computational efficiency, and trustworthy AI through uncertainty-aware learning and robust generalization. Applications include Education , Robotics , Agriculture , Networking , and Healthcare . Recent work emphasizes hardware-algorithm co-design and domain-specific AI platforms like Synthora and Gentopia. His publications from 2024–2025 highlight advancements in Vision Transformers , Diffusion Models , Edge Computing , and Trustworthy AI , with grants from NVIDIA , Microsoft , and the National Science Foundation . Awards include the AAAI Best Demonstration Award (2025), NVIDIA Academic Grant (2025), and the Carla Savage Award (2024). He actively mentors undergraduate researchers and co-chairs workshops at top venues like DAC , CVPR , and KDD , aiming to democratize AI access and enhance its reliability across real-world domains.

Jens OpitzView profile

Professor

• Transportation Systems
• Railway Timetabling
• Optimization Algorithms
• +3 more

Jens Opitz is a Professor at the Faculty of Transportation Science at Technical University of Dresden, where he is based at Hettnerstraße 1, 01069 Dresden (Room POT 105). He teaches courses including Theory of Transportation Systems and Statistics, Reliability Theory, Advanced Theory of Transportation Systems, Surface Transport Aviation and Simulations, and Actual Aspects in Optimization of Processes in Transportation and Logistics. His research focuses on transportation systems optimization, particularly in railway operations. Dr. Opitz has developed significant methods for generating synchronized timetables, integrating freight traffic into passenger timetables, and optimizing rail network operations. His work bridges theoretical optimization approaches with practical railway operations challenges, with applications in both passenger and freight rail transport. Dr. Opitz's publication record shows a strong focus on railway timetable optimization, with recurring themes in periodic scheduling, conflict resolution, and capacity utilization. His research has evolved from foundational work on modulo network simplex methods to more recent applications in complex railway station track allocation and integrated freight-passenger timetable planning. The publications demonstrate expertise in both theoretical algorithm development and practical implementation of railway optimization systems. His key research projects include Timetabling, Enhancement of existing methods for the generation of synchronized timetables, Integration of freight traffic into the generation of synchronized timetables, and Algorithms for synchronized timetable in railway traffic. These projects reflect his dedication to improving railway operations through advanced optimization techniques and software implementations like the TAKT program system for automatic routing in railway networks.

• Wireless Communications
• Digital Signal Processing
• MIMO Systems
• +5 more

Risto Wichman is a Professor in the Department of Information and Communications Engineering at Aalto University's School of Electrical Engineering. His research focuses on signal processing techniques for wireless communication systems, spanning physical layer design and MAC layer innovations with applications in next-generation networks. His research interests center on in-band full-duplex communications, multiple antenna systems (including massive MIMO), RF non-ideality compensation, spectrum sharing, cooperative communications, and network topology optimization. He employs advanced methodologies from communication theory, detection and estimation theory, stochastic geometry, random matrix theory, and large system analysis to solve complex wireless challenges. Recent publications (2024-2025) reveal strong emphasis on satellite-terrestrial integration, optical wireless networks, and machine learning-driven resource allocation. Key themes include line-of-sight optimization for positioning/sensing, Doppler effect characterization in LEO networks, full-duplex protocol design, and information harvesting for wireless power transfer. His work bridges theoretical foundations with practical implementations for 5G/6G systems. No scientific awards are documented in the provided materials. Information regarding student advising and research grants is not specified in the available sources. His leadership of the Risto Wichman Research Group drives collaborative work in wireless signal processing. The Risto Wichman Research Group focuses on cutting-edge wireless communication systems, with active projects spanning satellite networks, optical wireless integration, full-duplex technologies, and machine learning applications for network optimization. The group maintains strong industry and academic collaborations while developing solutions for real-world deployment challenges.

Henry BurtonView profile

Associate Professor

• Structural Engineering
• Earthquake Engineering
• Structural Reliability
• +3 more

Henry Burton is an Associate Professor and Presidential Endowed Chair in Structural Engineering within the Department of Civil and Environmental Engineering at the University of California, Los Angeles (UCLA), where he conducts research on structural safety and disaster resilience. His academic credentials include: Ph.D. in Civil Engineering, Stanford University (2014) M.S. in Civil Engineering, Stanford University (2004) B.S. in Civil Engineering, Morgan State University (2002) Professor Burton's research specializes in earthquake engineering and structural reliability, developing advanced methodologies for seismic performance assessment, enhanced building systems, and community-wide resilience planning. His work integrates computational modeling with practical engineering solutions to mitigate earthquake risks in urban infrastructure. His major recognitions include: NSF CAREER Award (2016) National Science Foundation Next Generation Fellowship (2014) International Conference on Building Resilience Best Paper Award (2014) Stanford University DARE Fellowship (2012) NSF-funded International Conference on Earthquake Engineering Travel Award (2011) Environmental Protection Agency Undergraduate Research Fellowship (2000) He teaches core structural engineering courses including Structural Design and Testing Laboratory (C&EE 135L), Advanced Structural Analysis (C&EE 235A), and Structural Reliability (C&EE 244), while leading a dedicated research group focused on seismic safety innovations as evidenced by his project website and media features in LAist, NSF Science Nation, and UCLA Newsroom.

• Earthquake Engineering
• Seismic Design
• Steel Structures
• +2 more

Lydell Andree Wiebe is a Professor in the Department of Civil Engineering at McMaster University's Faculty of Engineering. He specializes in earthquake engineering, seismic design of steel structures, and resilient infrastructure systems. His academic credentials include a BASc (2005) and PhD (2013) in Civil Engineering from the University of Toronto, and an MSc in Earthquake Engineering (2008) from the ROSE School in Pavia, Italy. His research focuses on developing innovative structural systems such as controlled rocking braced frames and masonry walls to enhance seismic resilience. Key areas include performance-based design, structural dynamics, and risk assessment of infrastructure under seismic loads. He actively contributes to professional committees, including the CSA S16 Technical Committee (Steel Structures) and the Canadian Association for Earthquake Engineering. Dr. Wiebe's recent publications (2020–2025) emphasize seismic loss mitigation, optimization of controlled rocking systems, and machine learning applications in structural engineering. His work integrates experimental testing with advanced computational models to improve design methodologies for earthquake-resistant structures. Awards & Honors: GJ Jackson Fellowship Award (2005) HA Krentz Research Award (2015) McMaster Faculty of Engineering Teaching Excellence Award (2017) McMaster Students Union Teaching Award (2014, 2017) He teaches courses including Steel Structures , Seismic Design and Analysis , and Introduction to Civil Engineering , reflecting his commitment to education and mentorship.

• Human-Computer Interaction
• User Experience
• Player Experience
• +6 more

Prof. Dr. Maximilian Altmeyer serves as Professor of Web Development and Mobile Applications Engineering at Saarland University of Applied Sciences within the School of Engineering. He leads the interaction experience group and holds key administrative roles including Member of the Faculty Council, Member of the University Library Advisory Board, and Deputy Head of Production Informatics. His work bridges academic research with practical application in digital systems. Altmeyer's research centers on Human-Computer Interaction with specialized focus on User Experience (UX), Player Experience (PX), Gamification, and Persuasive Technology. His investigations span Digital Health applications, gameful design principles, and interactive system development. Recent work examines voice interfaces, music effects in gaming, and sustainable behavior change through gamified eco-feedback systems. He employs rigorous empirical methods including instrument validation, comparative studies, and large-scale literature reviews. His publication trajectory reveals consistent contributions to top venues like CHI and CHI PLAY, with growing emphasis on user typology validation (Hexad scale), multimodal feedback systems, and cross-cultural adaptation of research instruments. The work demonstrates strong methodological diversity spanning controlled experiments, content analysis of 280+ papers, and longitudinal behavior change studies. Altmeyer actively shapes the research community through leadership roles including Work In Progress Co-Chair for CHI Play 2024/2023, Associate Chair for CHI 2026-2024, and extensive reviewing for premier HCI conferences. He teaches across bachelor's and master's programs covering Web Development, Gamification, Theoretical Computer Science, and Empirical Evaluation of Interactive Systems. The interaction experience group under his direction focuses on designing, implementing, and evaluating interactive systems with particular attention to user-centered gamification techniques and persuasive health technologies. Current projects include voice experience measurement tools, office wellness interventions, and game-based learning frameworks.

• Software Testing
• Mutation Testing
• Distributed Real-Time Systems
• +5 more

Birgitta Lindström is an Associate Professor of Informatics at the University of Skövde, Sweden, where she has been employed since 2000. She serves as Director of PhD education in Informatics since 2019 and leads the Distributed Real-Time Systems (DRTS) research group. Her academic home is within the School of Informatics, specifically the Department of Information Technology, where she teaches courses in software testing, concurrent programming, distributed systems, and software engineering experimentation. Lindström's research focuses on software testing methodologies, particularly mutation testing, testability analysis, and testing approaches for distributed real-time systems. Her work bridges theoretical foundations with practical applications in critical infrastructure protection, cybersecurity, and model-based testing. She has made significant contributions to understanding strong mutation theory, mutant subsumption, and efficient test set generation. Her recent publications reveal a growing emphasis on applying software testing principles to critical infrastructure systems, particularly smart grids and cyber-physical systems. The DOMINO project (2017-2025) represents her current focus on reducing the number of mutants needed for effective testing, while her earlier work in the ELVIRA (2017-2020) and TOCSYC (2013-2018) projects addressed testing of critical system characteristics including performance efficiency, robustness, and testability in complex embedded systems. Guldäpplet (Best Teacher Award) 2012 Lindström has supervised numerous BSc and MSc final year projects and served as examiner for various courses. Her research has been supported by substantial funding from sources including EU/ISF, KKS (30 MSEK for TOCSYC), and Vinnova (multiple projects totaling over 6.5 MSEK with matching from Saab Aeronautics). She has been instrumental in developing curriculum for computer science programs and establishing software testing education initiatives, including founding the TestEd workshop series focused on software testing education. As research leader of the DRTS group since 2015, she has fostered collaboration across institutions including Mälardalen University, Swedish Institute of Computer Science, Blekinge Institute of Technology, and Karlstad University. Her current DOMINO project continues this tradition of collaborative research addressing fundamental challenges in mutation testing efficiency.

Enrique Ruiz ZunigaView profile

Associate Professor

• Production Engineering
• Logistics Systems
• Robotics
• +7 more

Enrique Ruiz Zuniga serves as Associate Professor in Production Engineering at the University of Skövde's School of Engineering Science in Sweden, while simultaneously holding a JSPS research fellowship at Kyoto University's Systems Design Laboratory and collaborating with Japan Manned Space Systems Corporation (JAMSS). His career bridges academic research and industrial applications across Europe and Asia, focusing on optimizing complex manufacturing and logistics systems through advanced computational methods. University of Skövde, School of Engineering Science JSPS Research Fellow, Kyoto University Japan Manned Space Systems Corporation (JAMSS) collaborator Dr. Ruiz Zuniga's educational background includes a B.Eng. in industrial engineering from the University of Malaga, Spain, a BSc in automation engineering from the University of Skövde, Sweden, followed by an MSc in industrial informatics and a 2020 PhD in informatics from the University of Skövde, completed in partnership with Xylem Water Solutions Manufacturing. His doctoral research focused on facility layout design using simulation-based optimization methodologies. His primary research interests encompass the design, verification, and improvement of logistics, robotics, and complex production systems, with methodological expertise in Lean Production, Discrete-Event Simulation, System Dynamics, Simulation-Based Optimization, and the Functional Resonance Analysis Method. Dr. Ruiz Zuniga's work demonstrates a consistent focus on international collaboration and practical implementation of theoretical models in real-world industrial settings across healthcare and manufacturing sectors. Analysis of his publication record reveals an evolution from foundational work in facility layout design toward more recent explorations of AI integration, human-centered design, and resilient production systems. His research shows increasing sophistication in combining simulation approaches with functional analysis methods, with a growing emphasis on human factors and system resilience in complex production environments. REFUSE (2023-2026): Resource efficient use of reconfigurable machining systems Dynamic SALSA (2023-2024): AI scheduling for assembly and logistics systems Envisioned world problems (2021-2023): Functional approaches for system design Emergency Department Modeling (2012-2016): Healthcare production systems Dr. Ruiz Zuniga has coordinated international engineering programs in Industrial Engineering, Product Design Engineering, and Mechanical Engineering (all 60 credits), while teaching courses including Introduction to Lean Philosophy, Methods Engineering, Mechatronics/Electronics, and Production and Logistic Simulation. His work demonstrates a strong commitment to bridging theoretical research with practical industrial applications in production engineering through international collaboration and methodological innovation.

• Formal Methods
• Model Checking
• Bisimulation
• +9 more

Jeroen Keiren is an Assistant Professor in the Department of Computer Science at Eindhoven University of Technology (TU/e) , where he leads research in Formal Methods with a focus on Model Checking , Bisimulation , and Timed Systems . He is actively involved in the Formal System Analysis group , contributing to the development of techniques for verifying correctness in software and hardware systems. Education: Master's (2009) and PhD (2013) in Computer Science from TU/e Previous Roles: Postdoc at Vrije Universiteit Amsterdam (2013–2015), Assistant Professor at Open Universiteit (2015–2019) and University of Maryland (2016), Visiting Researcher at Radboud University (2015–2019), and Visiting Lecturer at TU Delft (2015–2019) His research emphasizes reducing model-checking complexity through bisimulation and parity games, with applications to industrial critical systems like UML state machines and medical devices. He is the principal investigator (PI) for projects in the Cordis SUITE framework. His work spans concurrent systems , parameterized models , and software/hardware verification . Recent publications highlight advancements in model-checking algorithms , timed modal logics , and industrial case studies (mechanical ventilators, packet networks). He contributes to the mCRL2 toolset and participates in industry-focused formal-methods initiatives. Committees: Chair of TU/e Computer Science Program Committee (2022–present), Secretary of Formal Methods Europe (FME) Industry Committee (2022–present), and roles in academic program and examination committees

• Abstract interpretation
• Termination analysis
• Formal languages
• +13 more

James Emil Avery is an Associate Professor at the Department of Computer Science, Faculty of Science, University of Copenhagen. His research spans abstract interpretation, termination analysis, and quantum chemistry applications using Coulomb Sturmians. He actively contributes to program analysis, computational methods in physics, and discrete mathematics. Research areas: Formal languages, operator algebra, quantum theory, and computational nanoscience Academic activities: VILLUM Young Investigator Program (2017), Editor for IET Nanobiotechnology (2017-2021) Technical publications: 15+ works on quantum chemistry methods, graph theory, and parallel computing His recent work includes simulating fullerene formation, solving wave equations on non-Euclidean surfaces, and developing symmetry-adapted basis sets. He has presented at international conferences on topics ranging from wave equation modeling to carbon nanostructure analysis. Scientific Awards: VILLUM Young Investigator Program grant recipient As an active researcher, Avery has participated in collaborative projects like the ERC Starting Grant evaluation and contributed to programming language development through the Bohrium framework. His editorial work at IET Nanobiotechnology demonstrates commitment to scientific peer review.

Heather ClarkView profile

Assistant Professor

• Program Evaluation
• Community Collaboration and Partnerships
• Rural Community Health
• +3 more

Dr. Heather Clark serves as Assistant Professor of the Practice and Director of Public Health Practice at Texas A&M University School of Public Health, specializing in community capacity building and program evaluation within rural and underserved populations. With two decades of field experience, she leads the Office of Public Health Practice to create student experiential learning opportunities through internships, service-learning, and workforce development initiatives funded by the Texas Department of State Health Services. Her educational credentials include a DrPH in Health Promotion & Community Health Sciences (2014), MSPH in Social and Behavioral Health (2005), and BS in Health (1995), all from Texas A&M University. These foundational qualifications underpin her expertise in translating academic theory into community practice. Dr. Clark's research centers on utilization-focused program evaluation, interorganizational network analysis, and rural community health capacity building. She employs collaborative methodologies to ensure data directly informs quality improvement and decision-making, with particular emphasis on social determinants of health in geographically isolated regions. Her work consistently bridges academic research and practical community health interventions. Recent publications reveal a concentrated focus on rural health infrastructure, telehealth-enabled sexual assault forensic services, and community-based evaluation frameworks. She frequently applies social network analysis to map referral systems and partnership dynamics, demonstrating how methodological rigor can address health disparities in resource-limited settings while advancing evidence-based public health practice. As an active mentor, Dr. Clark integrates students into federally and state-funded projects including the Texas Tele-forensic Remote Access Center and Collaborative Approaches to Well-being in Rural Communities. Her leadership in the Public Health Workforce Development Initiative directly addresses rural staffing shortages through structured training pipelines and applied practice experiences. She directs the Office of Public Health Practice in strategic collaborations with the Texas A&M School of Nursing, Hogg Foundation, CDC, and Texas Department of State Health Services. These partnerships drive community health assessments across the Brazos Valley and statewide initiatives that strengthen public health infrastructure through intersectoral coordination and capacity-building frameworks.

• Machine Learning
• Computational Biology
• Protein Structure Prediction
• +3 more

Wouter Boomsma is a Professor in the Machine Learning section of the Department of Computer Science at the University of Copenhagen. He leads the BioML research group, which focuses on developing machine learning techniques to address fundamental challenges in biology, particularly in the realm of protein science. His research interests center around understanding the relationship between protein sequence, structure, and function through advanced machine learning approaches. Key research areas include representation learning of protein sequences and structures, 3D structure prediction, and systematic protein optimization using techniques like Bayesian optimization. His work has significant applications in protein engineering, basic biological research on mutation effects in protein interaction networks, and health-related studies on human disease mutations. Boomsma's research program recently received substantial funding from the Novo Nordisk Foundation to establish the Center for Basic Machine Learning Research in Life Science (MLLS), a collaborative effort involving six machine learning research groups in the Copenhagen area. This initiative underscores the significance and potential impact of his work at the intersection of machine learning and life sciences. His publication record demonstrates a consistent focus on applying machine learning to protein science challenges, with recent work emphasizing protein structure prediction, variant effect analysis, and Bayesian optimization for protein engineering. The research output shows strong interdisciplinary connections between computer science, biology, and medicine. Boomsma maintains active collaborations with industry partners and research institutions, with his work gaining recognition through citations and media coverage. His group's research has been featured in high-impact journals including Nature Methods, Nature Communications, and PLOS Computational Biology. The BioML group operates within the Department of Computer Science's Machine Learning section at the University of Copenhagen, with physical location at Universitetsparken 1, Copenhagen Ø. The group maintains an active presence through their website (https://ku-bioml.github.io) and continues to expand its research portfolio in machine learning for biological applications.

Dana LokeView profile

Assistant Professor

• Medical Education
• Clinical Teaching Skills
• Simulation-Based Mastery Learning
• +3 more

Dana Loke, MD, MS serves as Assistant Professor (CHS) in the Department of Emergency Medicine at the University of Wisconsin School of Medicine and Public Health. She holds key leadership roles including Assistant Director of Medical Student Education, Quality Lead at the Veterans Hospital Emergency Department, and Quality Lead for Resident Education. Additionally, she is Partner Longitudinal Teacher Coach and Chief Quality Officer for Foundations of Emergency Medicine, a nonprofit advancing global emergency medicine education through open-access curricula. Her educational background includes: Undergraduate: University of Wisconsin–Madison Graduate: Northwestern University (MS in Healthcare Quality and Patient Safety) Medical School: Medical College of Wisconsin Residency: Northwestern University Feinberg School of Medicine (Chief Resident) Fellowship: Northwestern University Feinberg School of Medicine (Medical Education Clinical Scholars Program) Dr. Loke's research centers on medical education innovation with emphasis on simulation-based mastery learning and healthcare quality improvement. Her work integrates clinical teaching skills development with patient safety initiatives, particularly addressing resident education in quality and safety frameworks. She actively explores physician wellness impacts on clinical performance and develops open-access educational resources for emergency medicine practitioners worldwide. Her scholarship bridges theoretical educational models with practical emergency department quality improvement. Analysis of her 2022-2025 publications reveals three dominant themes: (1) Development and validation of simulation-based mastery learning tools for emergency procedures; (2) Systemic analysis of emergency department operations including boarding impacts and gender disparities; (3) Integration of patient safety principles into medical education curricula. Her work consistently connects educational innovation with frontline clinical quality improvement. Her scientific recognition includes: Dr. David Salzman Junior Faculty Award Dr. Morris Kharasch Award for Excellence in Teaching Best Faculty Innovator in Education Award Cornerstone Award for Foundations of Emergency Medicine leadership As Quality Lead for Resident Education and Medical Student Education Director, Dr. Loke mentors trainees through the residency quality improvement curriculum and longitudinal coaching programs. Her leadership in the Undergraduate Medical Education Leadership Team and VA Emergency Department Leadership Team drives institutional quality initiatives. She serves as Editor-in-Chief for Foundations of Emergency Medicine's F1 Course, impacting medical education globally. She leads the Foundations of Emergency Medicine nonprofit as Chief Quality Officer, developing standardized curricula adopted internationally. Within UW Health, she directs quality improvement efforts across University Hospital and East Madison Hospital emergency departments, focusing on procedural competency and patient safety systems.

Benjamin SchnappView profile

Associate Professor

• Medical Education
• Emergency Medicine
• Resident Training
• +4 more

Benjamin Schnapp, MD, MEd serves as Associate Professor in the Department of Emergency Medicine at the University of Wisconsin-Madison School of Medicine and Public Health, where he directs both the Emergency Medicine Residency Program and the Graduate Medical Education Scholarship Fellowship. His clinical expertise spans trauma care, musculoskeletal emergencies, and central nervous system infections within the BerbeeWalsh Emergency Department and affiliated clinical sites. His educational journey includes undergraduate training at Brown University, medical degree from The Warren Alpert Medical School of Brown University, emergency medicine residency at The Mount Sinai Hospital (serving as Chief Resident), medical education fellowship at Northwestern University, and ongoing Master of Education in Health Professions at the University of Cincinnati. This foundation supports his dual focus on clinical excellence and educational innovation. Dr. Schnapp's research centers on medical education transformation, particularly clinical teaching methodologies, resident-as-teacher development, wellness initiatives, and decision-making systems. His work pioneers competency-based frameworks like Entrustable Professional Activities (EPAs) and predictive learning analytics to enhance resident assessment. Current projects include an American Medical Association-funded initiative developing unified assessment systems across emergency medicine residencies. His publication portfolio reveals three dominant research trajectories: 1) Evolution of standardized evaluation systems (SLOEs) with AI integration potential, 2) Precision education through clinical dashboards and learning analytics, and 3) Implementation science for coaching models in graduate medical education. These threads converge on optimizing educational quality while addressing resident workload and case-mix variability. As Residency Program Director, he oversees comprehensive training for emergency medicine residents while mentoring faculty through national committees including SAEM's Graduate Medical Education and Fellowship Approval panels. His research portfolio includes significant funding from the American Medical Association for developing predictive analytics systems using EPAs, reflecting his commitment to data-driven educational improvement. Dr. Schnapp leads institutional efforts in educational innovation through the residency program's curriculum development and the fellowship program for medical education scholars, creating structured pathways for faculty development in academic emergency medicine.