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Kristiina BrunilaView profile

Professor

• Sociology of education
• Educational policy studies
• Cultural studies
• +7 more

Kristiina Brunila is Professor of Educational Sciences at the University of Helsinki , Finland. She is affiliated with the Department of Educational Sciences , the AGORA Research Center for Social Justice and Equality in Education , the Institute of Sustainability Science (HELSUS) , and the Teachers' Academy . She also serves as a supervisor in the Doctoral Programs in Gender, Culture, and Society Studies and in School, Education, Society, and Culture. Her research critically examines the intersections of education, power, and governance , with a particular focus on neoliberal policy regimes , therapeutic governance , youth subjectification , and educational inequality . She employs feminist , deconstructive , and discursive methodologies to explore how education systems produce and regulate subjectivities under market-driven and psychologized paradigms. Brunila has led and co-led multiple externally funded research projects, including AGORAEd , FuturEd , CoSupport , and TASOVA , addressing themes such as social justice in education, youth vulnerability, and future-oriented governance. Her work has been recognized with awards such as the Maikki Friberg Equality Award and the Adult Educator of the Year . Scientific Awards: Adult Educator of the Year (2011) Faculty Student Union Merit Badge with Golden Merit (2012) Candidate for Bonus Magister – Excellent Teacher Award (2016) Honourable Mention, Nordic Journal of Migration Research Best Article Award (2024) Maikki Friberg Equality Award (2021) Doctoral Supervision and Mentoring: Supervisor or co-supervisor of 14+ doctoral theses Supervisor in Doctoral Program in Gender, Culture and Society Studies Supervisor in Doctoral Program in School, Education, Society and Culture Research Projects: AGORAEd : AGORA for the study of social justice and equality (Project Director) FuturEd : Interrupting Future Trajectories of the Precision Education Governance (Project Director) CoSupport : Interrupting Youth Support Systems in the Ethos of Vulnerability (Project Director) TASOVA : Equality in Regional Development (Project Director)

• Transport Engineering
• Sustainable Transportation
• Traffic Management
• +6 more

Dr. Ioannis Kaparias is an Associate Professor in Transport Engineering at the University of Southampton, affiliated with the Transportation Research Group (TRG). He holds a Master of Engineering from Imperial College London and a PhD from the same institution. His academic career includes roles at City, University of London, and postdoctoral research at Imperial College. He is a Fellow of Advance HE, a member of the Chartered Institute of Highways and Transportation (CIHT), and serves as Deputy Editor-in-Chief of the IET Intelligent Transport Systems journal. Education: MEng in Civil Engineering, Imperial College London (2004) PhD in Transport Engineering, Imperial College London (2008) Postdoctoral Researcher, Imperial College London (2008–2012) Research Interests: Efficient, safe, and sustainable land transport systems Highway and traffic management, including real-time routing and network reliability Active travel modes (cycling/pedestrian infrastructure) Public transport operations and optimization New transport technologies (CAVs, MaaS, EVs) Land use-transport interaction models Teaching: Highway & Traffic Engineering modules at Southampton Doctoral Programme Director (Training) in the School of Engineering Past roles include teaching at Imperial College London, City University London, and the University of East London External Roles: Member of US Transportation Research Board committees (Pedestrians/ACH10 and Human Factors/ACH40) Independent expert for the European Commission Speaker at international conferences (e.g., 'To share or not to share space? A very British tale', 2023)

• Natural Language Processing
• Large Language Models
• Soft Robotics
• +4 more

Peiyi Wang is an Assistant Professor at Peking University's School of Electronics Engineering and Computer Science, Institute for Artificial Intelligence. With strong research output spanning both natural language processing and robotics, Wang maintains significant collaborations with Southern University of Science and Technology and National University of Singapore, particularly in soft robotics research with Professor Cecilia Laschi. Additionally, Wang is actively involved with DeepSeek-AI, contributing to several major language model initiatives including DeepSeek-R1 and DeepSeek-V2. Peking University, School of EECS, Institute for Artificial Intelligence (Primary) Southern University of Science and Technology (Collaborative) National University of Singapore (Collaborative) DeepSeek-AI Research Organization Dr. Wang's research spans two primary domains with significant intersection points. In natural language processing, Wang focuses on large language model reasoning capabilities, mathematical verification, uncertainty estimation, and preference alignment. The robotics work centers on soft robotics, particularly origami-inspired designs, strain-based modeling, and control systems for continuum manipulators. These domains converge in Wang's work on vision-language models, embodied AI, and multimodal reasoning systems. Recent work demonstrates particular innovation in mathematical reasoning verification (Math-Shepherd), soft robotic control systems, and red teaming frameworks for language model safety. Wang's publication record shows remarkable productivity, with over 40 publications between 2021-2025 across top-tier venues including ACL, EMNLP, CVPR, and IEEE Transactions on Robotics. The work demonstrates consistent progression from foundational NLP tasks to increasingly sophisticated multimodal and reasoning systems. The most recent publications (2024-2025) show particular emphasis on mathematical reasoning verification, soft robotics control, and language model safety evaluation. While specific awards aren't documented in the provided materials, Wang's work has clearly gained significant recognition through acceptance at top-tier conferences and collaborations with leading researchers in both NLP and robotics fields. Wang's research demonstrates strong interdisciplinary connections, bridging theoretical NLP work with practical robotics applications. The work with DeepSeek-AI suggests active industry collaboration while maintaining strong academic research output. Current research directions appear focused on improving language model reasoning reliability while developing novel soft robotic systems that can interact safely and effectively with complex environments.

Uwe GrünefeldView profile

Visiting Professor

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Dr. Uwe Grünefeld is a Visiting Professor at the Faculty of Computer Science , Institute for Computer Science and Business Information Systems (ICB) of the University of Duisburg-Essen. He has been actively contributing to Human-Computer Interaction research through multiple publications in 2025-2022 focusing on Virtual Reality , Augmented Reality , and Robotics . Research Interests span across immersive technology applications for health behavior change (situated artifacts, weight visualization mirrors), haptic feedback systems (EMS for weight perception, vibrotactile directional cues), and behavioral biometrics (hand tracking identification, gaze-based user recognition). His work addresses cross-reality system design , collaborative robotics , and human-in-the-loop simulation methodologies . Key Publications demonstrate significant contributions to VR/AR user engagement, with particular focus on Physical activity promotion through situated artifacts Advanced haptic feedback techniques for immersive environments Behavioral biometric identification systems Robot motion intent communication Cross-reality transition visualization His research often employs mixed-method approaches combining technical implementations with user studies involving quantitative and qualitative data collection.

Andrea GarulliView profile

Professor

• Control Systems
• Aerospace Engineering
• Robotics
• +5 more

Andrea Garulli is a Professor in Control Systems at the Department of Information Engineering and Mathematics (DIISM), University of Siena. He served as Dean of the Faculty of Engineering (2011-2012) and Director of DIISM (2015-2021). His research focuses on control systems, including system identification, state estimation, robust control, multi-agent systems, and aerospace applications. He co-authored the book *Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems* and developed the LFR_RAI toolbox for robustness analysis of uncertain models. Garulli has led projects like ACANTO (social robot navigation) and DALi (autonomous navigation for elderly care). His teaching includes courses on system dynamics, state estimation, and filtering. He is an Associate Editor for *Automatica* and has contributed to initiatives like the Automatic Control Telelab for remote experiments with mobile robots.

• Data Science
• Data Management
• Big Data Analytics
• +3 more

Ioannis Theodoridis is a Professor at the Department of Informatics, University of Piraeus, and Director of the Data Science Laboratory under the School of Information and Communication Technologies. His research focuses on data science, particularly large-scale data management and analysis, with applications in maritime informatics, spatiotemporal data, and mobility patterns. He holds editorial roles at ACM Computing Surveys and has contributed to numerous international conferences and journals. As a project leader in Horizon 2020 initiatives, he has coordinated research on data-driven solutions for maritime safety and urban mobility. He earned his Diploma (1990) and PhD (1996) in Electrical and Computer Engineering from the National Technical University of Athens (NTUA). His work includes developing scalable systems for maritime route forecasting (e.g., GMSA), frameworks for vessel trajectory prediction (e.g., VesselVision), and platforms like i4sea for fisheries monitoring. Contact: ytheod@unipi.gr .

Jingbang ChenView profile

Academic

• Algorithms
• Graph Theory
• Data Structures
• +3 more

Jingbang Chen is a Research Assistant Professor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen) and holds a joint faculty position at Shenzhen Loop Area Institute (SLAI) starting September 2025. His academic journey includes a Ph.D. from the University of Waterloo, an M.S. from Georgia Institute of Technology, and a B.Eng (Honors) from Zhejiang University under the supervision of Can Wang. Education: Ph.D., Computer Science, University of Waterloo (2023-2025) M.S., Computer Science, Georgia Institute of Technology (2020-2022) B.Eng. (Honors), Pursuit Science Class, Chu Kochen Honors College (Joint Program with College of Computer Science and Technology), Zhejiang University (2016-2020) High School, Guangzhou No.2 High School (2010-2016) Dr. Chen's research focuses on the design, analysis, and implementation of provably efficient algorithms and data structures, with a particular emphasis on graph theory. He is also exploring intersections between traditional algorithm design and artificial intelligence. His work bridges theoretical computer science with practical applications in network analysis, temporal data processing, and optimization. The publication record shows a strong trajectory with papers in top venues including ICML, VLDB, KDD, and theoretical computer science conferences. Scientific Contributions: Published in premier venues including ICML 2025, VLDB 2025, KDD 2024, and multiple theoretical conferences Research spans graph algorithms, optimization techniques, network analysis, and the emerging field of learning-augmented algorithms Active contributor to the competitive programming community as both researcher and practitioner Dr. Chen is deeply involved in Competitive Programming activities, having competed in ICPC World Finals 2018 (Beijing) and 2022 (Egypt), winning regional champion titles and several gold medals. He serves as chief judge for multiple ICPC Asia regionals and coaches training camps including the North American Programming Camp (NAPC). He is also the founder and co-president of the Universal Cup, an international competitive programming contest platform. Currently, he is recruiting highly motivated PhD students with strong backgrounds in competitive programming and interest in research, collaborating with Prof. Chenhao Ma on algorithm design projects.

Hanan SametView profile

Professor

• Spatial Databases
• Data Structures
• Geographic Information Systems (GIS)
• +5 more

Hanan Samet is a Distinguished University Professor at the University of Maryland's Computer Science Department, affiliated with the Institute for Advanced Computer Studies (UMIACS) and the Center for Automation Research. He holds a Ph.D. from Stanford University (1975) and specializes in spatial databases, data structures, and geographic information systems. His research bridges computer science and geospatial analytics, with applications in image databases, computer vision, and spatio-temporal data management. Education: Ph.D., Computer Science, Stanford University, 1975 Research Interests: Focuses on spatial data structures, GIS, spatio-textual systems like NewsStand and CoronaViz, trajectory analysis, and metric indexing. His work emphasizes scalable algorithms for spatial networks and multimedia databases. Notable Projects: CoronaViz : Tracks disease spread via spatio-temporal data visualization NewsStand : Maps news articles geospatially SAND: Spatial browser for digital government Awards: ACM Paris Kanellakis Award (2014), IEEE McDowell Award (2015), UCGIS Research Award, and Fellowships in ACM/IEEE/AAAS. Recognized for advancing spatial database theory and practice. Grants/Advising: Leads NSF-funded projects on spatio-textual extraction and similarity search. Advises graduate students (e.g., Nicole Schneider, Montana Hoover) and undergraduate researchers. Labs/Teams: Active in UMIACS and the Center for Automation Research, collaborating on projects like VASCO (spatial visualization tools) and MARCO (image database systems).

• Explainable Artificial Intelligence
• Industrial Machine Learning
• Business Process Management
• +6 more

Adeel AHMAD is an active Associate Professor (Maître de Conférences) conducting cutting-edge research at the intersection of artificial intelligence, industrial applications, and business process management. His academic work demonstrates strong interdisciplinary connections between computer science, industrial engineering, and business informatics. Dr. AHMAD's research interests span Explainable Artificial Intelligence (XAI), Industrial Machine Learning, Business Process Management, Ontology-Based Reasoning, and Logistics Optimization. His work focuses on developing practical AI solutions for industrial contexts, particularly in Industry 4.0 environments where human-AI collaboration is essential. He has made significant contributions to meta-learning approaches for automated algorithm selection and configuration, with particular emphasis on making these systems transparent and interpretable for domain experts. His publication record shows a clear trajectory toward integrating explainability into industrial AI systems, with recent work focusing on conversational recommendation systems for cyber-physical environments. The research demonstrates consistent evolution from foundational work in business process analysis toward sophisticated AI applications in industrial settings. Active research leadership in Explainable AI for industrial applications Significant contributions to meta-learning frameworks for automated machine learning Interdisciplinary approach bridging computer science, industrial engineering, and business processes Strong publication record in top-tier conferences and journals Dr. AHMAD demonstrates strong collaborative research patterns, frequently working with colleagues including Mourad Bouneffa, Moncef Garouani, and other researchers in the French academic community. His work shows particular relevance to manufacturing, logistics, and cyber-physical systems where AI must work alongside human domain experts.

• Distributed Systems
• Cryptography
• Electronic Voting
• +3 more

Michael J. Fischer is a Professor of Computer Science at Yale University, renowned for foundational contributions to distributed systems theory, cryptography, and parallel algorithms. His work includes the seminal impossibility result for distributed consensus with faulty processes and the development of the parallel prefix algorithm fundamental to modern parallel computing. His educational background: B.S. in Mathematics, University of Michigan (1963) M.A. in Applied Mathematics, Harvard University (1965) Ph.D. in Applied Mathematics, Harvard University (1968) Fischer's research spans theoretical and applied computer science with emphasis on distributed systems (consensus protocols, fault tolerance), cryptography (information-theoretic security, card-based protocols), and electronic voting systems . His work bridges abstract theory with practical security applications, particularly in trust modeling for e-commerce. Current investigations focus on algorithmic approaches to establishing trust relationships in distributed environments. His publication trajectory reveals evolving expertise from early parallel algorithms (1970-80s) to distributed consensus breakthroughs (mid-1980s), then cryptographic protocols and secure e-voting systems (1985-2000s), with recent work synthesizing these domains through trust frameworks. Key thematic threads include fault tolerance in unreliable networks and verifiable security mechanisms. Scientific recognition: ACM Fellow Fischer has held significant leadership roles including Editor-in-Chief of the Journal of the ACM , chair of the Max-Planck-Institute for Computer Science International Scientific Advisory Board, and founding member of the Computing Research Association's subcommittee on Women in Computer Science. His advisory work extends to the National Science Foundation and Wuhan University's State Key Laboratory on Software Engineering. Outside academia, he actively participates in the Yale Figure Skating Club, having served multiple terms as president. He maintains international collaborations as Guest Professor at Wuhan University and through editorial roles including Acta Informatica , while continuing to teach core computer science courses from data structures to cryptography at Yale.

• Topology
• Fuzzy Topology
• Soft Set Theory
• +3 more

Assoc. Prof. Dr. Adem YOLCU is an active faculty member at Kafkas University's Faculty of Arts and Sciences, Department of Mathematics, specializing in advanced topological structures with applications in decision-making systems. Holding a PhD in Mathematics from Kafkas University (2020), he has established himself as a leading researcher in fuzzy topology and soft set theory. PhD in Mathematics (2020), Kafkas University Master's in Mathematics (2016), Kafkas University Bachelor's in Mathematics (2014), Kafkas University His research focuses on the intersection of topology, fuzzy logic, and decision theory, particularly exploring neutrosophic soft sets, hypersoft topological spaces, and their applications in multi-criteria decision-making problems. His work bridges theoretical mathematics with practical computational applications in risk assessment and building safety analysis. Recent publications demonstrate a consistent trajectory in developing novel frameworks for fuzzy parameterized systems, with 15+ articles published between 2019-2024 in SCI/ESCI-indexed journals. His work shows particular strength in extending classical topological concepts to neutrosophic and Pythagorean fuzzy environments. As an academic advisor, he has supervised Master's research including Büşra Aka's thesis on neutrosophic soft multisets. His collaborative network spans international researchers including Taha Yasin Öztürk (60+ joint publications), Florentin Smarandache, and Sadık Bayramov. His research group focuses on computational topology applications, with particular emphasis on developing mathematical frameworks for uncertainty handling in decision support systems. Current projects include hypersoft set applications in sustainable security systems and Fermatean fuzzy topological structures.

Robert RisseView profile

Professor

• Tax Compliance
• Tax Risk Management
• Transfer Pricing
• +4 more

Prof. Dr. Robert Risse is an esteemed academic and practitioner in tax law, currently serving at the Institute for Austrian and International Tax Law at Vienna University of Economics and Business since 2020. Previously, he held the position of Corporate Vice President Tax & Trade at Henkel AG & Co KGaA from 2000 to 2020, where he was globally responsible for taxation and customs. He also holds the title of Honorary Professor for Tax Compliance and Applied Tax Planning at the Institute for Business Taxation, University of Leipzig. His extensive career bridges academic excellence with practical corporate tax leadership. Education 2017: Chairman of the Board of Directors for the Transfer Pricing Center of the Institute for International and Austrian Tax Law, Vienna University of Economics and Business 2014: Doctoral Thesis "Tax Compliance und Tax Risk Management: Eine rechtsvergleichende Analyse und Umsetzung in einem internationalen Konzern" at University of Freiburg 1986-1989: Second State Examination in Law, University of Bonn 1983-1986: First State Examination in Law, University of Bonn 1979-1982: Diplom Finanzwirt FH in Financial Sciences, University of Applied Sciences for Finances North Rhine-Westphalia Research Interests Prof. Risse's research focuses on the intersection of tax compliance, digitalization, and international tax systems. His work explores how digital technologies can transform tax compliance processes, particularly in multinational corporations. He has pioneered research on Tax Compliance Systems, Transfer Pricing in the digital age, and the integration of tax risk management with corporate governance frameworks. His expertise spans international tax law, corporate taxation, and the practical implementation of tax strategies in global business environments. His recent work emphasizes the practical implementation of digital tax systems, with particular attention to blockchain applications, AI in tax compliance, and the integration of tax processes with broader business systems. He has developed frameworks for assessing tax risk in multinational corporations and has contributed significantly to the understanding of transfer pricing in the context of digital business models. Publication Trends Prof. Risse's recent publications reveal a strong focus on digital transformation in tax systems, with increasing attention to practical implementation challenges. His work consistently bridges theoretical tax principles with real-world corporate applications, particularly in multinational contexts. The emergence of topics like AI in tax administration, blockchain applications, and digital compliance systems reflects his forward-looking approach. His research shows a clear trajectory from traditional tax compliance toward integrated digital tax ecosystems that address both regulatory requirements and business efficiency needs. Professional Engagement President of Gesprächskreis Rhein-Ruhr, Internationales Steuerecht e.V./International Fiscal Association (IFA) West Member of DIHK Finanz- und Steuerausschuss, Berlin Member of Düsseldorfer Vereinigung für Steuerrecht e.V Member of Fachinstitut der Steuerberater e.V., Düsseldorf Member of Institut Finanzen und Steuern, Berlin Teaching and Advisory Roles Prof. Risse has extensive teaching experience across multiple institutions including University of Leipzig, Vienna University of Economics and Business, University of Freiburg, University of Cologne, and WHU – Otto Beisheim School of Management. He has supervised doctoral students through the "Doktorandenseminar zur Betriebswirtschaftlichen Steuerlehre" at University of Leipzig. His teaching focuses on international taxation, corporate tax law, and the practical application of tax planning in multinational corporations.

• Environmental Economics
• Tourism Economics
• Gender Economics
• +2 more

Dr. Jesus Barreal Pernas serves as Assistant Professor in the Department of Quantitative Economics at the Faculty of Economic and Business Sciences, University of Santiago de Compostela. His research bridges environmental policy, tourism economics, and educational innovation with significant regional impact in Galicia and broader European relevance. His academic foundation includes a 2015 PhD from the University of Santiago de Compostela with thesis "Wildfires in Galicia: causality, forest policy and risk in forest management" supervised by Dra. Maria L. Loureiro. This environmental economics work established his expertise in spatial analysis of forest systems. Barreal Pernas' research program demonstrates three converging trajectories: First, environmental economics focusing on wildfire patterns and forest policy in Galicia using spatial econometrics. Second, tourism economics examining sustainable financing mechanisms (particularly green tax willingness), international tourist segmentation, and PDO region development. Third, educational innovation through gamification techniques for teaching statistics in economics and tourism degrees. His recent publications reveal increasing emphasis on gender perspectives in financial inclusion and pandemic-related economic impacts. Analysis of his 2023-2025 publications shows methodological sophistication in spatial modeling and survey-based behavioral research, with strong policy relevance for Galician regional authorities and European tourism sectors. Key thematic clusters include sustainable tourism financing (12% of recent output), educational technology applications (18%), wildfire management (8%), and gender economics (7%). No scientific awards are documented in the provided materials, though his collaborative network spans multiple European institutions as evidenced by co-authorship patterns. His advisory role appears focused on thesis supervision within USC's economics programs, with research projects frequently addressing practical challenges in Galician tourism and environmental management. Current initiatives suggest expansion into post-pandemic tourism recovery and advanced gamification frameworks for quantitative education.

• Control Systems
• Renewable Energy Systems
• Hydrogen Energy Storage
• +3 more

Dr. Fan Zhang serves as Associate Professor in Engineering (Engineering and Design) at the School of Engineering and Informatics, University of Sussex, where he leads research in control systems and sustainable energy technologies. His work bridges theoretical control engineering with practical renewable energy applications, particularly in hydrogen storage and conversion systems. His academic foundation includes: PhD in Control Systems from the University of Sheffield MSc in Control Systems from the University of Sheffield PgCLT (Distinction) from the University of South Wales BEng in Automation from Tianjin University of Technology and Education Research centers on control systems for renewable energy integration, with emphasis on hydrogen storage, wind/solar-hydrogen systems, and automation. His work demonstrates strong interdisciplinary connections between power electronics, energy conversion, and sustainable transportation solutions, particularly through advanced control strategies for complex energy systems. Publication analysis reveals consistent focus on hydrogen energy systems (70% of recent work), with growing emphasis on aviation applications and tidal energy integration. His research trajectory shows evolution from foundational photovoltaic control (2013-2015) toward multi-source renewable systems (2021-2025), reflecting industry shifts toward hydrogen economy solutions. Academic recognition includes: Senior Fellow of the Higher Education Academy He supervises research projects including tidal lagoon power and hydrogen energy storage optimization, with teaching responsibilities spanning Robotics and Electrical Engineering programs delivered in China. His curriculum development for Automation & Mechatronics and Systems Analysis modules demonstrates practical application of his research expertise. Current research activities involve supervisory control systems for renewable hydrogen infrastructure, with emerging work in neurolinguistics-based control interfaces indicating expanding interdisciplinary reach.

• Cognitive Neuroscience
• Neuropsychology
• Traumatic Brain Injury (TBI)
• +7 more

Michael J. Larson is a Professor of Psychology in the College of Family, Home, and Social Sciences at Brigham Young University (BYU), where he directs the Clinical Cognitive Neuroscience and Neuropsychology (CCNN) Lab. His research integrates neuropsychology and cognitive neuroscience methodologies to investigate cognitive control mechanisms in healthy individuals and cognitive dysfunction following traumatic brain injury (TBI). He employs advanced techniques including event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI) to examine neural correlates of cognitive processes. Dr. Larson's research program has four primary aims: (1) Investigating behavioral and neural reflections of cognitive control using ERP/fMRI; (2) Understanding lifespan developmental trajectories of cognitive control in neurologic insult or psychopathology (TBI, autism, depression); (3) Examining cognitive control's role in exercise and food-related behaviors including obesity; (4) Determining psychometric properties of biological measures for clinical application. His work spans traumatic brain injury recovery, exercise cognition, food inhibitory control, and psychopathology-neurocognition interactions. His publication trends reveal strong focus on methodological rigor in psychophysiology, with recent articles emphasizing ERP reliability across paradigms, preregistration practices, and multiverse analysis approaches. Key research domains include TBI rehabilitation (particularly via photobiomodulation and HRV biofeedback), sex differences in concussion mechanisms through the LIMBIC MATARS Consortium, and neural markers of food-related inhibitory control. Editor-in-Chief, International Journal of Psychophysiology (2016-Present) Top-Cited Scholar for Scientific Field (2019) Martin B. Hickman Innovation in Teaching Award (2018) University Young Scholar Award (2015) College Outstanding Young Alumnus, University of Florida (2014) Dr. Larson mentors students through the BYU Chapter of the Association of Neuropsychology Students and Trainees (ANST) and collaborates extensively with Dr. Tricia Merkely, Dr. Derin Cobia, and Dr. Shawn Gale on clinical neuropsychology training. His lab emphasizes rigorous methodology and psychometric validation, contributing significantly to standards in electrophysiological research through editorial leadership and methodological publications.