جست‌وجوی استاد و پژوهشگر

Abraham Silberschatzمشاهده پروفایل

استاد

• Database Systems
• Operating Systems
• Storage Systems
• +۳ مورد دیگر

Abraham Silberschatz is the Sidney J. Weinberg Professor of Computer Science at Yale University. He previously served as Vice President of the Information Sciences Research Center at Bell Laboratories and held a chaired professorship at the University of Texas at Austin. His research focuses on database systems, operating systems, and network management. Silberschatz has advised over a dozen PhD students, many now in academia and industry. Education: Ph.D., Computer Science, Stony Brook University (SUNY) Research Interests: His work spans database systems, operating systems, storage systems, and network management. Notable contributions include foundational textbooks like Operating System Concepts and Database System Concepts , which have become industry standards. He has also developed innovative systems like DataPlay and contributed to projects such as NetInventory. Publications: His 15+ years of research include influential papers on database architecture, network routing, and distributed systems. Recent work explores leveraging non-volatile memory technologies in systems design. Awards: ACM Karl V. Karlstrom Outstanding Educator Award (1998) IEEE Taylor L. Booth Education Award (2002) VLDB Test of Time Award (2019) Multiple Bell Laboratories President's Awards for innovation Grants & Patents: Recipient of over two dozen grants and over four dozen patents, including foundational IP in multimedia storage and distributed systems. His team's HadoopDB project merged MapReduce and DBMS technologies. Labs/Teams: Collaborates with Prof. Robert Soulé on projects in database systems and networking, focusing on next-gen memory technologies. Active in mentoring graduate students and postdocs in their research group.

Jerry Zeyu Gaoمشاهده پروفایل

استاد

• Cloud Computing and Services
• Software as a Service (SaaS)
• Testing as a Service (TaaS)
• +۷ مورد دیگر

Jerry Zeyu Gao is a Professor in the Department of Computer Engineering at San Jose State University, part of the Charles W. Davidson College of Engineering. He maintains active office hours and has a strong presence in both academic and industry domains, combining over 15 years of academic experience with more than 10 years in software engineering and IT development management. His research spans a wide range of cutting-edge areas in computing, including: Cloud Computing and Services Software as a Service (SaaS) and Testing as a Service (TaaS) Test Automation Mobile Computing and Mobile Cloud Technologies Software and Service Engineering Mobile Sensor Technologies Smart Cities infrastructure Dr. Gao has published over 180 papers in top-tier IEEE and ACM journals and conferences, and has co-authored three technical books while editing several others in software engineering and mobile computing. His scholarly output reflects a strong focus on practical, scalable solutions in cloud, mobile, and service-oriented systems. The publications show consistent themes in automation, service delivery, distributed architectures, and real-world software validation. He has played a leadership role in the international research community, having served as conference chair, program co-chair, and workshop co-chair for numerous prestigious events such as IEEE MobileCloud, IEEE SOSE, SEKE, and others between 2004 and 2015. These roles highlight his influence and recognition in the software engineering and cloud computing communities. Dr. Gao advises students and contributes to graduate and undergraduate education, although specific advisees are not listed. He is involved in research projects and likely secures external funding given his publication and conference leadership activities, though specific grants are not mentioned. He is associated with research initiatives related to mobile systems, cloud services, and smart city technologies.

Bonnie Bergerمشاهده پروفایل

استاد

• Compressive Genomics
• Network Inference
• Structural Bioinformatics
• +۴ مورد دیگر

Bonnie Berger is the Simons Professor of Mathematics at the Massachusetts Institute of Technology and head of the Computation and Biology group at MIT's Computer Science and AI Lab. She holds additional appointments as an Associate Member of the Broad Institute, Faculty member of Harvard/MIT Health Science & Technology, and Affiliated Faculty of Harvard Medical School. Her career has been dedicated to pioneering computational approaches in molecular biology, where she has been instrumental in defining the field. Professor Berger's research focuses on designing algorithms to extract biological insights from large-scale data sets. Her work spans Compressive Genomics, Network Inference, Structural Bioinformatics, Genomic Privacy, and Medical Genomics. She actively collaborates with experimental biologists to maximize the power of computation for biological discovery, developing methods that address the challenges of modern high-throughput biological data. Her recent publications demonstrate a strong trend toward integrating machine learning with structural biology and genomic privacy. The articles show increasing sophistication in using deep learning for protein structure prediction, developing privacy-preserving techniques for genomic data sharing, and creating efficient algorithms for massive biological data sets. Her work bridges theoretical computer science with practical biological applications. Professor Berger's scientific recognition includes: Election to the National Academy of Sciences (2021) ISCB Accomplishments by a Senior Scientist Award SIAM Sonya Kovalevsky Lecture Prize Fellowships in ACM, ISCB, AMS, and other prestigious societies Multiple RECOMB Test of Time Awards NIH Margaret Pittman Director's Award She has mentored numerous students who have gone on to make significant contributions in computational biology, including Ellen Zhong, Yun William Yu, and Hyunghoon Cho. Her lab receives substantial research funding supporting projects in genomic privacy, structural bioinformatics, and compressive algorithms for biological data. Professor Berger serves on the Executive Editorial Board of the Journal of Computational Biology and multiple other editorial boards. The Computation and Biology group at MIT CSAIL, which she leads, is at the forefront of developing computational methods for biological discovery. The group combines expertise in algorithms, machine learning, and biology to tackle fundamental challenges in genomics and structural biology. They are currently organizing the Machine Learning in Structural Biology workshop at NeurIPS 2025, highlighting their leadership in this rapidly evolving interdisciplinary field.

Avi Wigdersonمشاهده پروفایل

استاد

• Computational Complexity Theory
• Randomness and Computation
• Algorithms and Optimization
• +۱۰ مورد دیگر

Avi Wigderson is the Herbert H. Maass Professor in the School of Mathematics at the Institute for Advanced Study, Princeton. He is a leading authority in theoretical computer science, particularly computational complexity theory. Wigderson organizes the Computer Science and Discrete Mathematics (CSDM) program at the Institute, fostering interdisciplinary research at the intersection of mathematics and computer science. Wigderson earned his Ph.D. (1983), M.A. (1982), and M.S.E. (1981) from Princeton University. Prior to his current position, he held appointments at The Hebrew University of Jerusalem (1986-2003), Princeton University (1990-1992), Mathematical Sciences Research Institute, Berkeley (1985-1986), IBM Research (1984-1985), and University of California, Berkeley (1983-1984). Wigderson's research spans computational complexity theory, randomness and computation, algorithms and optimization, circuit complexity, proof complexity, quantum computation and communication, and cryptography. His work explores fundamental questions like whether mathematical creativity can be automated (P vs NP problem), the security of electronic commerce, the role of randomness in computation, and the potential of quantum mechanics to enhance computation. He has made significant contributions to understanding the power and limitations of efficient computation. Analysis of Wigderson's recent publications reveals a strong focus on optimization, complexity theory, and their mathematical foundations. His work connects diverse areas including non-commutative algebra, geometric complexity, graph theory, and quantum computing. A recurring theme is exploring whether fundamental computational problems like P vs NP can be addressed through optimization techniques such as gradient descent. His research shows increasing interdisciplinary connections between theoretical computer science, mathematics, and physics. ACM A.M. Turing Award (2023) Abel Prize (2021) Donald E. Knuth Prize (2019) Gödel Prize (2009) American Mathematical Society's Levi L. Conant Prize (2008) Rolf Nevanlinna Prize (1994) Yoram Ben-Porat Presidential Prize for Outstanding Researcher (1994) Bergman Fellowship (1989) Member, American Academy of Arts and Sciences Member, National Academy of Sciences While specific details about Wigderson's students are not provided in the source material, his extensive lecture series, workshops, and program organization suggest significant mentorship activities. His book "Mathematics and Computation" published by Princeton University Press serves as an educational resource for students and researchers. Wigderson has organized major programs at the Institute for Advanced Study including "Lower Bounds in Computational Complexity" (2018) and "Pseudorandomness" (2017), creating research opportunities for numerous scholars. Wigderson leads the Computer Science and Discrete Mathematics (CSDM) program at the Institute for Advanced Study, which brings together researchers from mathematics and computer science to explore fundamental questions in computation. His work with collaborators across multiple institutions has established connections between theoretical computer science and diverse fields including quantum information theory, algebraic geometry, and optimization. Recent projects focus on non-commutative optimization and its applications to computational complexity problems.

• Cybersecurity and privacy
• Privacy protection
• AI and machine learning
• +۴ مورد دیگر

Dr. Bo Liu is an Associate Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he serves as a core member and director of the AI Security and Privacy (AISP) Research Lab at the Australian Artificial Intelligence Institute (AAII). With expertise spanning cybersecurity, privacy protection, AI and machine learning, and wireless communications, Dr. Liu has established himself as a leading researcher in the field of AI security and privacy. Dr. Liu earned his PhD from the Department of Electronic Engineering at Shanghai Jiao Tong University in 2010. His academic journey at UTS has progressed from Senior Lecturer (November 2019-December 2022) to his current position as Associate Professor (January 2023-present). Dr. Liu's research focuses on the critical intersection of artificial intelligence and security, particularly addressing emerging threats in the age of advanced AI systems. His work spans multiple dimensions of security and privacy, including deepfake detection, privacy-preserving data synthesis, AI model security, and fair machine learning. He has pioneered approaches to detect AI-generated content, protect visual privacy through de-identification techniques, and address the complex relationship between algorithmic fairness and privacy preservation. His publication record demonstrates significant contributions across multiple cutting-edge research areas, with particular emphasis on detecting and mitigating threats from generative AI systems. His recent work reveals a strong focus on deepfake detection across multiple modalities (images, video, and audio), privacy-preserving techniques for sensitive data, and the security implications of emerging AI architectures like Retrieval-Augmented Generation systems. Dr. Liu has secured substantial research funding, including as Lead Chief Investigator on multiple ARC Discovery and Linkage Projects, totaling over $3.5 million AUD. His industry collaborations include partnerships with the NSW Department of Planning and the Reserve Bank of Australia, demonstrating the practical applicability of his research. As an academic leader, Dr. Liu serves as Associate Editor for IEEE Transactions on Broadcasting and actively contributes to the academic community through conference organization, peer review for top-tier venues, and assessment for ARC grant schemes. He also teaches courses including Penetration Testing, Ethical Hacking and Offensive Security, and supervises Masters and PhD students in cybersecurity and privacy research.

Lin Zhongمشاهده پروفایل

استاد

• Computer Science
• Quantum Computing
• Operating Systems
• +۳ مورد دیگر

Lin Zhong is the Joseph C. Tsai Professor of Computer Science at Yale University, leading the Efficient Computing Lab. He holds a Ph.D. from Princeton University and M.S./B.S. degrees from Tsinghua University. Previously, he served at Rice University from 2005 to 2019. His research focuses on optimizing computing efficiency, quantum error correction, operating systems, and mobile systems. Education: Ph.D., Princeton University M.S., Tsinghua University B.S., Tsinghua University Research Interests: His work spans quantum computing (e.g., decoding algorithms for surface codes), operating systems (safety, correctness, and lightweight kernels), and mobile/networking systems (massive MIMO, energy-efficient designs). Recent trends include integrating large language models (LLMs) into robotics and securing cloud-based AI workflows. Awards: NSF CAREER Award ACM SIGMOBILE RockStar (2014) and Test of Time (2022) Fellowships from IEEE and ACM Best Paper Awards at ACM MobileHCI, IEEE PerCom, ACM MobiSys, and more Lab & Teams: His Efficient Computing Lab explores systems for quantum error correction (e.g., FPGA-based decoders), secure embedded systems, and LLM-driven robotics. Projects include TimelyLLM (real-time LLM serving) and Blindfold (confidential memory management).

• Climate Change Adaptation in Agriculture
• Land Use Modeling
• Biodiversity Conservation
• +۳ مورد دیگر

Thomas Berger is a Professor at the University of Hohenheim , affiliated with the Faculty of Agricultural Sciences and leading the Department of Economics of Land Use . He also contributes to the Computational Science Hub and Hohenheim Tropics initiatives. Focus Areas: Climate change adaptation, land-use modeling, biodiversity-productivity trade-offs, agent-based simulation, and machine learning in agricultural systems. Key Projects: Simulation frameworks for smallholder resilience in Ethiopia, bioeconomic modeling in the Amazon, and hybrid intelligence applications in European agricultural policy. Recent Publications: 2025 study on climate change effects on insecticide reduction in Germany, 2024 work on reconciling biodiversity with productivity via hybrid models, and 2023 methodological contributions to surrogate modeling and seasonal forecast integration. Research Trends: Interdisciplinary integration of climate science, agricultural economics, and computational modeling, with increasing emphasis on AI-assisted decision support systems and sustainability policy validation. Teaching & Outreach: Offers Agricultural Economics seminars and Hohenheim Tropics discussions, requiring advance email registration for office hours.

Terese Johannessenمشاهده پروفایل

دانشیار

• Quality Improvement in Healthcare
• Nursing Education
• Healthcare Leadership
• +۶ مورد دیگر

Terese Johannessen serves as an Associate Professor in the Department of Health and Nursing Sciences at the University of Agder (UiA), Norway. Her academic work focuses on quality improvement, leadership development, and implementation science within healthcare settings, particularly in nursing homes and home care services. Dr. Johannessen's research primarily centers on understanding quality and safety in long-term care environments. Her work investigates contextual factors influencing healthcare quality, leadership interventions for improvement, and the conceptualization of 'quality' among healthcare providers. She employs qualitative methodologies to explore managers' experiences, implementation challenges, and the development of practical tools for frontline staff. Her research has significant implications for improving care delivery in nursing homes and home care services through evidence-based leadership approaches. Analysis of Dr. Johannessen's publication record reveals a strong thematic focus on the SAFE-LEAD project, a comprehensive research initiative examining leadership interventions for quality and safety in nursing homes and home care. Her work spans multiple dimensions including intervention design, implementation challenges, contextual mapping, and evaluation of leadership approaches across different healthcare settings. The research demonstrates a methodological preference for qualitative and mixed-methods approaches to capture the complex realities of healthcare improvement work. Dr. Johannessen collaborates extensively with researchers including Siri Wiig, Eline Ree, and Ingunn Aase, primarily through the SHARE Centre for Resilience in Healthcare at the University of Stavanger. Her work bridges academic research and practical application in healthcare settings, with significant contributions to understanding how quality improvement efforts can be effectively implemented in real-world contexts. Her research portfolio demonstrates consistent productivity with multiple publications annually, showing progression from foundational studies on contextual factors to the development and testing of specific leadership interventions. The SAFE-LEAD project represents a cohesive research program addressing critical challenges in long-term care quality and safety through systematic investigation and practical tool development.

Yavuz Yakutمشاهده پروفایل

استاد

• Rehabilitation Science
• Physiotherapy
• Biomechanics
• +۵ مورد دیگر

Prof. Dr. Yavuz Yakut serves as full-time Professor and Head of the Department of Physiotherapy and Rehabilitation at Hasan Kalyoncu University's Faculty of Health Sciences since 2016. Previously, he held academic positions at Hacettepe University from 1985 to 2016, progressing from Research Assistant to Professor, while concurrently serving on national committees including the Ministry of Health and Ministry of Finance Budget Implementation Commissions (1997-2003) and YÖK Physiotherapy Sub-Commission (2013-2016). His educational foundation includes a Bachelor's (1984), Master's (1987), and PhD (1990) in Physiotherapy and Rehabilitation, all completed at Hacettepe University. Yakut's research demonstrates exceptional breadth across rehabilitation science, with concentrated expertise in biomechanics and scoliosis rehabilitation . His work significantly advances neurological rehabilitation for conditions like multiple sclerosis and cerebral palsy, while pioneering applications in burn rehabilitation and orthotics/prosthetics . Recent publications reveal strategic integration of biopsychosocial models and telerehabilitation , particularly addressing pandemic-related challenges and chronic disease management across diverse populations. Analysis of his 2023-2025 publications shows consistent interdisciplinary innovation: validating cross-cultural assessment tools (e.g., Turkish translations of scoliosis and ADL questionnaires), developing novel exercise protocols (dance therapy, cognitive exercise therapy), and investigating rehabilitation responses in complex cases including HIV, rheumatic diseases, and post-earthquake trauma. His methodology frequently combines biomechanical analysis with patient-centered outcomes, demonstrating particular rigor in controlled trials for spinal deformities and burn recovery. His leadership extends beyond direct research through committee roles shaping national rehabilitation policy and educational standards, including his current departmental leadership and recent systematic review on physiotherapy distance education during pandemic disruptions.

Jinjin Haمشاهده پروفایل

استادیار

• Machine Learning in Materials Science
• Plasticity
• Ductile Fracture
• +۳ مورد دیگر

Jinjin Ha serves as an Assistant Professor in the Department of Mechanical Engineering at the University of New Hampshire, with her office located in Kingsbury Hall, Room W101a, Durham, NH. She teaches core mechanical engineering courses including Statics (ME 525), Materials Processing in Manufacturing (ME 742/842), Theory of Plasticity (ME 927), and Doctoral Research (ME 999), demonstrating active engagement in both undergraduate and graduate education. Her research program integrates computational mechanics with advanced manufacturing, focusing on: Machine learning applications for plasticity modeling and fracture prediction Deformation mechanics in incremental sheet forming processes Martensitic phase transformations in stainless steels Anisotropic material behavior and yield function development Ductile fracture characterization of titanium and aluminum alloys Analysis of her 2023-2024 publications reveals a decisive shift toward AI-driven mechanics, where neural networks solve complex constitutive modeling challenges in metal forming. This interdisciplinary approach bridges fundamental material science with industrial manufacturing optimization, particularly in toolpath design and phase transformation control. No scientific awards were documented in the provided profile information. While doctoral research supervision is indicated through ME 999 course listings, specific student names, grant funding details, laboratory facilities, or collaborative team structures were not disclosed in the available text.

Panteleimon Ekkekakisمشاهده پروفایل

استاد

• Exercise Psychology
• Affective Responses to Exercise
• Public Health
• +۵ مورد دیگر

Panteleimon Ekkekakis is a Professor and Chair of the Department of Kinesiology at Michigan State University’s College of Education. His research focuses on affective responses to exercise, including their psychobiological mechanisms and implications for exercise behavior. He holds a Ph.D. from the University of Illinois, Urbana-Champaign. Ekkekakis’ work explores the pleasure and displeasure associated with exercise, emphasizing their role in predicting long-term adherence. His research spans topics like high-intensity interval training (HIIT), obesity, mental health interventions, and physical education practices. Notably, he critiques methodological flaws in HIIT studies and advocates for evidence-based exercise guidelines. His recent articles highlight critical analyses of HIIT efficacy, the role of affective valence in exercise adherence, and the need for paradigm shifts in obesity treatment. He emphasizes the importance of personalized exercise programs that prioritize subjective enjoyment to enhance public health outcomes. While no specific awards are listed, his contributions to exercise psychology and policy advocacy are significant. His research has informed debates on fitness testing in schools and the integration of exercise into clinical depression treatment.

Emily Cookمشاهده پروفایل

استادیار

• Higher Education Policy
• Economics of Education
• STEM Education
• +۳ مورد دیگر

Emily Cook is an Assistant Professor at Texas A&M University, focusing on higher education economics, policy analysis, and institutional decision-making. Her research examines topics such as college pricing structures, STEM education funding, vaccine mandate impacts, and market dynamics in education and aviation sectors. She employs rigorous empirical methodologies to evaluate policy outcomes and institutional behaviors. Her work highlights how federal funding influences STEM curricula, how tuition policies affect student major choices, and the role of peer institutions in shaping reopening strategies during crises. Cook also investigates the equity implications of college pricing models and the structural evolution of industries such as airlines and higher education markets. Notable areas of focus include the interplay between public health policies and educational continuity, the competitive landscape of US universities, and the socioeconomic factors influencing student transitions from high school to college.

Dimitris Kolovosمشاهده پروفایل

استاد

• Automated and Model-Based Software Engineering
• Model-Driven Software Engineering
• GenAI for Software Engineering
• +۴ مورد دیگر

Roles and Affiliations : Dimitris Kolovos is a Professor of Software Engineering at the University of York's Department of Computer Science. He leads the Automated Software Engineering (ASE) research group and is an Eclipse Foundation committer, leading development of the Epsilon open-source platform. His roles include research leadership, teaching, and academic service. Education : PhD in Software Engineering - University of York MSc in Software Engineering with Distinction - University of York First Class Honours Degree in Informatics - Athens University of Economics and Business Research Interests : Kolovos focuses on advancing Model-Driven Engineering (MDE), GenAI integration in software development, low-code platforms, and data analytics. His work emphasizes scalable modeling tools, education technology (e.g., MDENet platform), and industry collaboration with organizations like NASA, BAE Systems, and Siemens. Labs and Projects : He leads the Epsilon project under the Eclipse Modelling initiative, developing tools for model transformation, validation, and code generation. His research group also explores AI-driven model transformations and hybrid graphical-textual editors.

Jasmine Begeskeمشاهده پروفایل

استادیار بالینی

• Inclusive Education
• Arts Education
• Assistive Technology
• +۵ مورد دیگر

Jasmine Begeske serves as Clinical Assistant Professor of Special Education in Purdue University's Department of Educational Studies within the College of Education. She co-founded and directs CREATE: Center for Research and Equipment for Assistive Technology in Education, an AT library and makerspace providing hands-on opportunities for pre-service teachers to develop individualized solutions for students with disabilities using 3D printers, Cricut, and Glowforge equipment. Her educational background includes: PhD in Special Education with Cognate in Art Education from Purdue University MFA in Photography and Related Media from Purdue University MS in Secondary Education (Special Education specialization) from Indiana University Northwest BFA in Photography with Art History minor from Indiana University Dr. Begeske's research program examines inclusive access to arts education through program evaluation and creative assistive technology development. Her experimental printmaking practice integrates individuals with disabilities as co-creators , while her scholarly work validates instruments measuring preschool arts accessibility and develops multisensory adaptations for students with visual impairments. She bridges art education and special education through evidence-based AT interventions . Analysis of her publication history reveals consistent focus on arts/special education intersections with increasing emphasis on empirical validation of accessibility instruments and multisensory adaptations. Her 2023 work on teacher education in art classrooms and multisensory adaptations demonstrates practical applications of her CREATE center's mission, while her 2022 instrument validation study establishes methodological rigor in measuring arts accessibility. Her scientific recognition includes: 2023 USSEA Outstanding Dissertation Award 2023 Purdue Focus Award for equity initiatives 2022 AEAI President's Award for EDI service Multiple Purdue University teaching and discovery awards (2020-2023) With 15+ years of teacher preparation experience spanning 100+ course sections, Dr. Begeske mentors doctoral students while securing grant funding including $100K from Purdue's Instructional Equipment Grant for CREATE. Her professional service encompasses state-level program reviews, academic standards committees, and leadership roles in Indiana Division of Early Childhood and CEC-DARTS. The CREATE center operates as a dual-space AT innovation hub with fixed location in Beering Hall and mobile carts supporting field experiences. It empowers pre-service teachers to prototype solutions addressing specific student needs while advancing Dr. Begeske's mission of making education universally accessible through technology and creativity.

Jonathan Littleمشاهده پروفایل

استاد

• Exercise Physiology
• Metabolism
• Inflammation
• +۳ مورد دیگر

Jonathan Little is a Professor at the University of British Columbia Okanagan , affiliated with the Faculty of Health and Social Development and School of Health and Exercise Sciences . He leads the Exercise Metabolism and Inflammation Laboratory (EMIL) , focusing on the intersection of exercise physiology, nutrition, and metabolic disorders. Hons B. Kin – McMaster University, 2005 M.Sc. – University of Saskatchewan, 2007 Ph.D. – McMaster University, 2010 Postdoctoral Fellowship – UBC, 2010-2012 His research investigates how metabolic disruptions in type 2 diabetes affect cellular inflammation and how exercise/nutritional strategies can mitigate these effects. Key areas include high-intensity interval training (HIIT) , nutritional ketosis , and immunometabolic responses . EMIL combines human clinical trials with cellular/molecular experiments, utilizing advanced tools like flow cytometry and metabolic carts. His recent publications emphasize exercise snacks (short, frequent workouts), ketone supplements , and fasting protocols for managing diabetes and obesity. He has received prestigious awards like the Killam Accelerator Fellowship and CIHR New Investigator Award . Killam Accelerator Research Fellowship (2021-2023) Canadian Society for Exercise Physiology Young Investigator Award (2020) UBC Killam Research Fellowship (2018) Michael Smith Foundation for Health Research Scholar (2018-2023) American College of Sports Medicine New Investigator Award (2016) CIHR New Investigator Salary Award (2015-2020) He supervises graduate students in HMKN 313 – Exercise Metabolism and mentors through the HMKN 499 Research Practicum . His lab (EMIL) collaborates with institutions like the BC Diabetes Research Network and serves as an Associate Editor for Applied Physiology, Nutrition and Metabolism .