Dorothy Worden-Chambers is an Associate Professor in the Department of English at the University of Alabama, serving as Coordinator of the Applied Linguistics/TESOL Program. Her expertise spans multilingual writing pedagogy, second language teacher cognition, and genre-based instruction. She holds a PhD in Applied Linguistics from Pennsylvania State University (2015) and an MA in Rhetoric and Composition from Washington State University (2008). Her research focuses on L2 writing teacher development, with particular attention to pedagogical content knowledge, curriculum design, and the impact of teacher beliefs on instructional practices. Her work bridges theoretical frameworks in applied linguistics and writing studies, emphasizing practical applications in multilingual education. Recent publications explore themes such as teacher learning through tutoring, conceptual metaphors in curricular knowledge, and the role of genre projects in teacher education. Her contributions span journals like Teacher Development , Composition Forum , and Journal of Second Language Writing . Worden-Chambers actively contributes to professional development through workshops and collaborative initiatives, such as graduate student-led faculty training programs on multilingual writing pedagogy. Her work underscores the interplay between teacher identity, pedagogical practices, and multilingual learner outcomes.
Peter Newman, Ph.D., serves as Dean of the Rubenstein School of Environment and Natural Resources at the University of Vermont since July 1, 2024, and holds the Suzie and Allen Martin Professor title. With a career spanning decades, he has conducted extensive research on visitor management in protected areas, soundscape management, and transportation planning, partnering with the National Park Service's Natural Sounds and Night Sky Division since 2012. Education Ph.D. in Natural Resources, University of Vermont M.S. in Forest Resource Management, SUNY College of Environmental Science and Forestry B.A. in Political Science, University of Rochester His research focuses on social carrying capacity decision-making in protected area management, with fieldwork across major U.S. parks including Denali, Grand Canyon, and Great Smokies. He has developed frameworks for acoustic management and Leave No Trace efficacy, contributing to sustainable outdoor recreation practices. Scientific Awards: Cooperative Ecosystem Studies Unit National Award (2012) George Wright Society National Award for Achievement in Social Sciences (2013) Throughout his career, Newman has led high-quality teaching at Penn State's Graduate Degree Program in Acoustics and mentored numerous students through research projects on wildlife approach norms, pandemic recreation shifts, and waste management strategies in national parks. He previously served as a Park Ranger in Yosemite and Backcountry Patrol member in Idaho.
Evita Papazikou serves as a Lecturer in Transport Engineering at the School of Engineering, University of the West of England (UWE Bristol), where she contributes to the Centre for Transport and Society and collaborates with the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre. Her academic qualifications include: Civil Engineering (BEng and MEng) from Aristotle University of Thessaloniki MSc in Planning, Organisation, and Management of Transport Systems, Aristotle University of Thessaloniki PhD in Automated Systems and Driver Behaviour (Road Safety) from Loughborough University, sponsored by the Insurance Institute for Highway Safety with access to SHRP2 NDS data Dr. Papazikou's research focuses on road safety, connected and automated vehicles, driver behaviour analysis, and smart infrastructure. She investigates accident causation through statistical modeling, develops driver monitoring systems, and explores human factors in transportation. Her work integrates traffic simulation with mobility data fusion from vehicles, sensors, and infrastructure to enhance safety in future mobility systems, particularly in cooperative, connected, and automated environments. Her recent publications (2023-2025) reveal a concentrated research trajectory examining safety impacts of dedicated lanes for autonomous vehicles, parking policy implications in automated eras, and driver fatigue management. She consistently employs naturalistic driving data and traffic microsimulation to analyze driver-vehicle-environment interactions, with increasing emphasis on real-world intervention effectiveness and environmental sustainability in mobility systems. Scientific Awards: No specific awards were mentioned in the provided information. Dr. Papazikou has secured significant research funding through competitive programs including Horizon 2020, Innovate UK, and the Department for Transport. Her project portfolio demonstrates substantial industry collaboration, particularly with Ford, and includes: LEVITATE: Assessing societal impacts of Connected and Automated Vehicles SafetyCube: Developing an innovative road safety decision support tool i-DREAMS: Creating a smart driver and road environment assessment system DDRST: Building a data-driven road safety tool for hotspot identification TRIP: Developing a driver culpability assignment tool for road injury prevention She actively contributes to interdisciplinary research through her affiliations with the Centre for Transport and Society and the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre, where she bridges engineering, human factors, and policy development for next-generation transportation systems.
Nakul Gopalan serves as an Assistant Professor at Arizona State University's School of Computing and Augmented Intelligence (SCAI) in Tempe, where he founded and leads the Logos Robotics Lab since joining in August 2022. His academic foundation was established through a PhD in Computer Science from Brown University completed in 2019. Education: PhD in Computer Science, Brown University (2019) Research Focus: Dr. Gopalan pioneers work at the critical intersection of language grounding and robot learning, developing algorithms that enable robots to interpret natural language instructions and learn from human demonstrations. His research directly addresses real-world usability challenges by focusing on hierarchical reinforcement learning, task planning, and human-robot collaboration frameworks that empower non-expert users to train robots for home and office environments. Key innovations include plannable representations for natural language instruction following and transfer learning techniques for robotic task execution. Publication Evolution: Recent publications (2023-2025) demonstrate accelerating specialization in language-conditioned robot learning, with 80% of his latest work exploring compositional instruction following, novice-user teaching interfaces, and explainable AI for robotics. His research trajectory shows a deliberate shift from foundational language grounding (2017-2020) toward practical human-robot collaboration systems, evidenced by increased focus on hardware-software co-design, cross-embodiment transfer, and clinical applications of explainable AI in neurology support systems. Scientific Recognition: Best Paper Award at RoboNLP workshop (Association for Computational Linguistics) 2017 RSS 2023 Best Student Paper Finalist Mentorship & Service: As lab director, Dr. Gopalan actively mentors graduate researchers while teaching core courses including Data Structures and Algorithms (CSE 310) and specialized seminars on robot learning. His significant service contributions include organizing the RSS 2021 "Robotics for People" workshop, serving as Action Editor for ICRA 2023/2024, and extensive reviewing for top-tier robotics conferences (RSS, ICRA, CORL) and AI venues (NeurIPS, AAAI). Research Infrastructure: The Logos Robotics Lab operates as his primary research vehicle, focusing on natural language interfaces for robot training, hierarchical task decomposition, and real-world deployment of language-grounded learning systems. Current projects integrate large language models with robotic control frameworks to enable zero-shot task generalization across different robot embodiments.
Michael Karas is an Assistant Professor of Applied Linguistics at Brock University's Faculty of Social Sciences. He holds a PhD from the University of Western Ontario (2019). His research focuses on language teacher self-efficacy, reflective practice, and learner silence, with notable contributions to meta-analyses in language education. He teaches courses such as Second Language Acquisition (LING 3Q91) and Pedagogical Grammar (LING 5P02). Karas serves as Book Review Editor for the TESL Canada Journal and TESL Ontario Academic Coordinator, demonstrating active engagement in academic service. Education : PhD in Applied Linguistics, University of Western Ontario (2019) Research Specialization : Explores intersections between teacher proficiency, classroom dynamics, and innovative methodologies like duoethnography. His work bridges theoretical research with practical applications in teacher education and language policy. Service Contributions : Editorial roles at TESL Canada Journal (2017–present) Coordinator for TESOL Doctoral Forum (2017–2018)
Christiane C. Schubert is an Assistant Professor in Medical Education at the School of Medicine and an Assistant Professor in Interdisciplinary Studies at the School of Behavioral Health at Loma Linda University. Her dual appointments reflect her interdisciplinary approach to healthcare research and education, bridging medical education with behavioral health perspectives. Dr. Schubert's educational background includes: PhD from Loma Linda University (2008) MS from Northern Arizona University (1999) BS from Northern Arizona University (1997) Her research program focuses on understanding healthcare systems through multiple lenses. She investigates how patients with chronic illnesses navigate self-care within complex healthcare environments, with particular attention to macroergonomic factors that influence patient work systems. Dr. Schubert examines resilience in healthcare settings, exploring how both patients and providers adapt to challenges in clinical environments. Her work addresses cultural factors in healthcare, particularly examining how acculturation affects health-promoting behaviors among Arab Americans. Through her studies on novice-expert differences in emergency medicine, she contributes to understanding cognitive work processes in high-stakes clinical settings. Her interdisciplinary approach integrates insights from medical education, behavioral health, and systems engineering to address complex healthcare challenges. Dr. Schubert's scholarly output from 2012-2017 demonstrates consistent contributions across healthcare resilience, patient work systems, medical education, and cultural competence. Her publications reveal a trajectory of increasingly sophisticated systems thinking applied to healthcare delivery challenges, with a particular emphasis on understanding patient experiences and clinician cognition within complex healthcare environments. Dr. Schubert has maintained an active research and publication record since completing her PhD in 2008. Her work demonstrates a commitment to improving healthcare delivery through better understanding of patient experiences, clinician cognition, and system-level factors that influence healthcare outcomes. Her interdisciplinary appointments position her to bridge traditional academic boundaries in addressing complex healthcare challenges.
Susanne Sahlin is a Senior Lecturer at Mid Sweden University's Department of Education in Sundsvall, Sweden. She holds a Doctor of Philosophy (PhD) degree and has established herself as a prominent researcher in educational leadership and school administration. Dr. Sahlin's research primarily focuses on school leadership development, with particular emphasis on principal preparation, leadership identity formation, and professional development for educational leaders. Her work examines how school principals navigate their roles through various lenses including: Novice principals' professional confidence and identity development Peer mentoring as a mechanism for professional socialization Adaptive leadership during crises, particularly the COVID-19 pandemic Collaboration between schools and external partners for school improvement Cross-national comparisons of leadership preparation programs Her extensive publication record demonstrates a clear trajectory of research examining leadership practices from multiple perspectives. Recent work increasingly addresses contemporary challenges facing school leaders, including crisis management, equity considerations, and technological integration in educational leadership. Dr. Sahlin frequently collaborates with researchers both within Sweden and internationally, particularly with colleagues Styf, Lund, and Sjöstrand, as well as international partners in England and Australia. Dr. Sahlin completed her doctoral thesis in 2019 titled "Moving Beyond Internal Affairs: Making Sense of Principals' Leadership Practices in Collaboration for School Improvement" at Mid Sweden University. Her ongoing research continues to explore how school leaders develop their professional identities and navigate complex educational landscapes.
Lisa Yan serves as a Teaching Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, appointed in Spring 2022. She teaches core computer science education courses including CS 195 (Social Implications of Computer Technology), CS H195 (Honors variant), CS 294-189 (Teaching Process Design), and CS 375 (Teaching Techniques), holding regular office hours in Soda Hall for student engagement. Her academic credentials include: PhD in Electrical Engineering from Stanford University (2019) MS in Electrical Engineering from Stanford University (2015) BS in Electrical Engineering and Computer Science from UC Berkeley (2013) Dr. Yan's research centers on data-driven analysis of student learning in large-scale computer science courses, with significant contributions to computing ethics pedagogy and teaching assistant development programs. Her work develops innovative methodologies for assessing student earnestness in interactive lectures, creating flexible learning extensions, and designing integrity-focused assessments. Earlier research focused on software-defined networking and network switch performance optimization, demonstrating technical depth before her pivot to educational innovation. Current projects emphasize scalable teaching techniques and mastery learning frameworks that address challenges in modern CS education. Analysis of her 14 publications (2013-2024) reveals a strategic shift from computer networking (pre-2018) to computer science education research (2018-present). Recent work (2020-2024) dominates in venues like SIGCSE, featuring tools such as Otter-Grader for Jupyter notebook grading and the Earnest Insight Toolkit for lecture participation analysis. This evolution highlights her commitment to solving practical educational challenges through data analysis and tool development, particularly for large undergraduate courses. She received recognition through: The Faculty Award for Outstanding Mentorship of GSIs (2024) Lisa actively mentors Graduate Student Instructors and collaborates with educational technology initiatives. Her research team includes dedicated support staff like Taylor Kaserman (taylor.kase@berkeley.edu), reflecting structured collaboration in developing teaching innovations. She contributes to curriculum design committees within EECS, focusing on assessment integrity and scalable pedagogical methods for growing student populations. Her work operates through the EECS department's educational infrastructure, utilizing Soda Hall resources for both teaching coordination and research development, with strong connections to Berkeley's broader computing education ecosystem.
Emily Bonner is a Professor in the Department of Interdisciplinary Learning and Teaching at the University of Texas at San Antonio (UTSA) and serves as the Associate Dean for Research and Faculty Affairs in the College of Education and Human Development (COEHD). Her work focuses on equity in mathematics education, professional development in high-need schools, and parent education. Ph.D. in Curriculum and Instruction (Mathematics Education), University of Florida, 2009 M.A.T. in Secondary Education/Special Education, Trinity University, 2002 B.A. in Mathematics, Trinity University, 2001 Bonner’s research emphasizes culturally responsive teaching, community-based interventions, and the role of parents in mathematics education. She has led projects like the Community Mathematics Project and the San Antonio Mathematics Collaborative (SAMC), addressing systemic inequities and teacher preparation gaps. Her recent publications highlight frameworks for teacher development, equity strategies in Hispanic-serving institutions, and adaptations to virtual learning environments. These works span mathematics education, pedagogy, and policy studies. Key grants include the Community Math Project ($3.7M, DOE), ReLaTe SA ($444,474, NSF), and Texas Higher Education Coordinating Board funding for SAMC. These support initiatives to strengthen teacher education and math proficiency in underserved communities.
Carlos R. Rivero is an Associate Professor in the Department of Computer Science at the Rochester Institute of Technology (RIT), located within the Golisano College of Computing and Information Sciences. His primary research focuses on graph theory applications in knowledge graphs, graph databases, and computer-aided program comprehension. He holds a PhD from the University of Seville (Spain), completed in 2012, with postdoctoral work at the University of Idaho (USA). His teaching responsibilities include courses such as Principles of Data Management, Data Mining, and Big Data exploration. Rivero has advised numerous PhD and Master’s students, contributing to research projects in link prediction, knowledge graph completion, and educational technology. He actively serves on program committees for conferences like The Web Conference and SIGKDD, and has reviewed for journals including the VLDB Journal and Communications of the ACM. His research emphasizes evaluating knowledge graph embeddings, improving link prediction methodologies, and developing tools for educational feedback in programming. He has contributed to projects like AYNEXT, which streamlines link prediction evaluation, and CAFE, a neighborhood-aware knowledge graph completion tool. Rivero’s work bridges theoretical advancements with practical applications in education and industry. Notable contributions include frameworks for automated feedback in programming courses and methodologies for assessing inference patterns in knowledge graphs. His grants and service roles reflect a commitment to advancing computational methods and fostering academic collaboration in data science and education.
Thomas Yeh is an Assistant Professor of Teaching in the Department of Computer Science at the University of California, Irvine. His academic background includes a Ph.D. in Computer Science from UCLA and a BS in Electrical Engineering and Computer Science from UC Berkeley. Prior to academia, he gained industry experience across research, architecture, design, verification, marketing, and management roles. His educational credentials: Ph.D. in Computer Science, UCLA BS in Electrical Engineering and Computer Science, UC Berkeley Dr. Yeh's research spans computer architecture, accelerated machine learning, and computer science education. In architecture, he pioneers error-tolerant physics simulation and heterogeneous computing. His ML work focuses on adaptive precision techniques for energy-efficient acceleration. In education, he develops interactive tools for novice programmers and experiential learning frameworks for computer architecture. His cross-disciplinary approach bridges hardware-software co-design with pedagogical innovation. Publication trends reveal consistent focus on computational efficiency across physics simulation, ML acceleration, and educational technology. His work connects real-time systems optimization with emerging AI applications, particularly in interactive environments and physics-based animation. No scientific awards are documented in the provided materials. While advising details and grant funding specifics are absent from available information, his industry-academia transition informs practical research directions. Teaching responsibilities include core courses like Introduction to CS, Data Structures, and Efficient ML Computing. Research infrastructure details remain unspecified, though his publications suggest collaborations in physics simulation and heterogeneous computing environments.
Marisa Exter serves as Associate Professor of Learning Design and Technology within Purdue University's Department of Curriculum and Instruction since 2020, following promotion from Assistant Professor (2013-2020). With 15+ years of software design and development experience, she holds dual expertise in Computer Science (BS/MS) and Instructional Systems Technology (PhD). Her educational foundation includes: PhD in Instructional Systems Technology, Indiana University (2011) MS in Computer Science, Illinois Institute of Technology (2003) BS in Computer Science, Elmhurst College (1999) Dr. Exter's research pioneers transdisciplinary educational innovation , focusing on how design processes transform technology-creation fields like Instructional Design, Computing, and Engineering. She investigates formal and non-formal learning experiences to enhance undergraduate education through interdisciplinary programs, while simultaneously examining online graduate program structures that support adult learners' connection to faculty and peers. Her work integrates heutagogical principles for lifelong learning and rigorously documents design successes/failures through scholarly design cases. Analysis of her 15 most recent publications reveals accelerating focus on dispositional development in computing professions , competency-based curriculum models, and transdisciplinary experience design. Her methodological evolution includes increased use of Q methodology and collaborative autoethnography to capture diverse perspectives in educational innovation. As Purdue PI for a $3M multi-institutional computing competencies grant and co-coordinator of AECT's Summer Research Symposium, she drives national curriculum reform. Her mentorship approach cultivates the Exploring Disruptive Education research family group, which investigates interdisciplinary design processes across technology-rich learning environments. Professional service spans Computing Curriculum 2020 Task Force leadership and ACM/AERA membership. The Exploring Disruptive Education research collective she co-leads operates as an interdisciplinary incubator for educational innovation. This team examines how design thinking transforms learning experiences through technology integration, with particular emphasis on creating connections between formal education and industry practices in computing and engineering fields.
Allison Sullivan is an Assistant Professor of Computer Science at the University of Texas at Arlington (UTA), where she also serves as the Undergraduate Software Engineering Program Director. She is a member of the Software Engineering Research Center (SERC) at UTA and serves as faculty advisor for UTA's Society of Women Engineers (SWE) club. Dr. Sullivan received her PhD in Software Verification, Validation and Testing (SVVAT) from the University of Texas at Austin in 2017 under Sarfraz Khurshid. Her educational background includes: PhD in Software Verification, Validation and Testing, University of Texas at Austin (2017) M.S. in Software Engineering, University of Texas at Austin (2014) B.S. in Software Engineering, University of Texas at Dallas (2012) Dr. Sullivan's research focuses on two primary areas: Automated Software Engineering : Test/Oracle Generation, Automated Bug Localization and Repair, Mutation Testing, and Regression Testing Formal Methods and Programming Languages : Abstractions, Finite Model Finders, Program Synthesis, and SAT/SMT Solvers She leads the SCOPE lab which focuses on 'showing the correctness of all program executions' and has published extensively on Alloy modeling language applications. Her recent publications demonstrate a strong focus on applying formal methods to software engineering problems, with a growing emphasis on the intersection of large language models and software development practices. Her work spans theoretical foundations, tool development, and empirical studies of how developers use modeling languages. Her scientific achievements have been recognized with: NSF CAREER Award (2024) UTA CSE department Rising Star Research Award (2024) UTA College of Engineering Outstanding Early Career Faculty Award (2025) NSF grant for building an educational tool for software modeling ($400k) Dr. Sullivan has successfully advised two PhD students to completion: Dr. Ana Jovanovic (defended November 2024) and Dr. Anahita Samadi (defended February 2025). She actively mentors undergraduate researchers and has secured significant research funding including the NSF CAREER grant. Her service includes committee roles for major conferences including ASE, ISSRE, and FormaliSE. She leads the SCOPE lab at UTA, which brings together graduate and undergraduate researchers to develop techniques for improving software verification and validation, with particular emphasis on making formal methods more accessible to practitioners.
Associate Professor Peter Sutton is an academic at the University of Queensland (UQ), holding roles as Deputy Head of School (Teaching and Learning) and Associate Professor in the School of Electrical Engineering and Computer Science. His research focuses on Engineering Education, Embedded Systems, Reconfigurable Computing, and Electronic Design Automation. He has contributed to curriculum design, remote lab management during the pandemic, and hardware-software co-design for embedded systems. Sutton completed his undergraduate studies at UQ and earned advanced degrees at Carnegie Mellon University, with over three decades of experience in computer systems research and education. Education Bachelor of Science, University of Queensland Bachelor (Honours) of Engineering, University of Queensland Masters of Science (Coursework), Carnegie Mellon University Doctor of Philosophy, Carnegie Mellon University Research Interests Sutton’s work spans engineering pedagogy, embedded system design, and reconfigurable computing. Recent projects include adapting hands-on labs for remote learning during the pandemic and optimizing FPGA-based architectures for data compression and encryption. His contributions to cache optimization and multiprocessor systems highlight his expertise in hardware-software integration. Publications His 50+ publications cover topics like FPGA implementations of neural networks, code compression techniques for VLIW processors, and embedded system design tools. Notable contributions include frameworks for reconfigurable system-on-chip development and methods to enhance debugging practices in post-novice students. Labs & Teams He collaborates within UQ’s School of Electrical Engineering and Computer Science, contributing to research groups focused on embedded systems and engineering education innovation.
Kathleen H. Sienko is the Arthur F. Thurnau Professor in the Department of Mechanical Engineering at the University of Michigan's College of Engineering. She directs the Sienko Research Group, a multidisciplinary lab focused on developing technological solutions at the intersection of healthcare and engineering. Her work spans medical device design, design science, and engineering education with a strong emphasis on global health contexts. Dr. Sienko earned her Ph.D. in Medical Engineering and Bioastronautics from the Harvard-MIT Division of Health Sciences and Technology (HST) program in 2007, an S.M. in Aeronautics & Astronautics from MIT in 2000, and a B.S. in Materials Engineering from the University of Kentucky in 1998. Ph.D., Medical Engineering and Bioastronautics, Harvard-MIT Division of Health Sciences and Technology, 2007 S.M., Aeronautics and Astronautics, Massachusetts Institute of Technology, 2000 B.S., Materials Engineering, University of Kentucky, 1998 Her research focuses on sensory augmentation, rehabilitation engineering, biomechanics, and medical device design with emphasis on global health contexts and task-shifting devices. She has pioneered efforts to incorporate global health technology constraints within engineering design education at undergraduate and graduate levels, establishing field sites in sub-Saharan Africa and Asia where numerous devices have been conceptualized and refined with local stakeholders. Her work in design science examines how and when designers use prototypes in development cycles and how prototypes assist during stakeholder interactions and user requirements identification. Her recent publications reveal a strong trend toward human-centered approaches in global health design, with increasing focus on stakeholder engagement, contextual factors in engineering design, and equity considerations in health technology development. Her work bridges biomechanics, rehabilitation engineering, and design methodology with applications in balance assessment, medical device development for low-resource settings, and engineering education. Dr. Sienko has received numerous prestigious awards including the NSF CAREER Award, University Undergraduate Teaching Award, Provost's Teaching Innovation Prize, and the Miller Faculty Scholar Endowed Award. Her recognition spans teaching excellence, research innovation, and outreach contributions. NSF CAREER Award, 2009 Provost's Teaching Innovation Prize, 2012 Miller Faculty Scholar Endowed Award, 2013 University Undergraduate Teaching Award, 2012 Raymond J. and Monica E. Schultz Outreach and Diversity Award, 2011 She has advised numerous graduate students including Nick Moses (who defended his dissertation in December 2023), Lucy Spicher, Marty Kilbane, and Ibrahim Mohedas. Her research has been supported by significant grants from the National Science Foundation, including the CAREER program, Research Initiation Grants in Engineering Education, and the Graduate Research Fellowship program, as well as funding from the University of Michigan's Rackham Merit Fellows program and Center for Research on Learning and Teaching. The Sienko Research Group operates as a talented multidisciplinary lab developing novel methodologies to create technological solutions addressing pressing societal needs at the healthcare-engineering intersection. Current research thrusts include Design Science, Autonomous Vehicles, Balance, Sensory Augmentation, and Wearable Devices, with particular emphasis on how design ethnography can inform medical device development and how engineering students develop ethnographic skills for global health contexts.
