جستجوی استاد راهنمای دانشگاهی

Bernard Comrieمشاهده پروفایل

استاد پژوهش

• Language Universals
• Linguistic Typology
• Historical Linguistics
• +۵ مورد دیگر

Bernard Comrie is a Research Professor Emeritus in Linguistics at the University of California, Santa Barbara (UCSB), affiliated with the College of Letters and Science. He previously served as Director of the Department of Linguistics at the Max Planck Institute for Evolutionary Anthropology in Leipzig (1998–2015) and held a Distinguished Professorship at UCSB (2002–2021). His career includes teaching positions at the University of Cambridge, University of Southern California, and leadership roles in major research institutions. Comrie’s research focuses on Language universals and typology Historical linguistics Languages of the Caucasus, New Guinea, and Great Andamanese He emphasizes fieldwork-driven cross-linguistic analysis of topics like tense/aspect, transitivity, numeral systems, and prehistoric migration studies through collaborations with archaeologists and geneticists. His recent publications explore morphosyntactic variation (e.g., verb indexing in Asian languages, reflexivity in Tsez), language contact (Kanashi prehistory), and numeral system typology. Articles often bridge theoretical linguistics with empirical data from understudied languages. Notable contributions include the World Atlas of Language Structures and foundational work on Nakh-Daghestanian and Andamanese languages. He advocates for interdisciplinary approaches to reconstructing prehistoric human movements via linguistic evidence.

Bimal Viswanathمشاهده پروفایل

دانشیار

• Cybersecurity
• Privacy Engineering
• Machine Learning
• +۴ مورد دیگر

Bimal Viswanath is an Associate Professor in the Department of Computer Science at Virginia Tech's College of Engineering. His research focuses on cybersecurity, privacy engineering, and machine learning, particularly addressing adversarial AI and ML system vulnerabilities. He holds a Ph.D. from Saarland University and Max Planck Institute for Software Systems, and has held postdoctoral positions at UCSB and Nokia Bell Labs. Education Ph.D., Computer Science, Saarland University/Max Planck Institute (2016) M.S., Computer Science, IIT Madras (2008) B.Tech, Computer Science, Cochin University (2005) Research interests include: Adversarial attacks using/against ML systems Generative AI security (deepfakes, chatbots) Cybersecurity for online services Grants & Funding Recipient of CCI, NSF, and 4-VA grants supporting projects like robust AI defense mechanisms and adversarial image classification. Recent grants include $1.2M for AI security initiatives (2022-2025). Awards Distinguished Paper Award (SOUPS 2014) Best Paper Award (COSN 2015) AI2000 Most Influential Scholar Honorable Mention (2020) Advising Guided over 15 students including Jiameng Pu (PhD 2022), Connor Weeks (MS 2023), and current advisees Sifat Muhammad Abdullah (PhD 2021-). Notable student achievements include Facebook Fellowship nominations and industry placements at CVENT and University of Michigan. Labs & Teams Leading Virginia Tech's AI Security Lab focusing on generative models, adversarial ML, and applied cybersecurity solutions.

Akhilesh Jaiswalمشاهده پروفایل

استادیار

• Device-Circuit Co-design
• Processing-in-Pixel
• In-Memory Computing
• +۴ مورد دیگر

Dr. Akhilesh Jaiswal serves as Assistant Professor of Electrical and Computer Engineering at the University of Wisconsin-Madison, where his research pioneers device-circuit co-design for next-generation computing systems. His work focuses on enabling extreme-edge intelligence through processing-in-pixel technology, in-memory computing architectures, and bio-inspired neuromorphic systems. His academic credentials include: PhD in Nano-electronics from Purdue University (2019) MS from the University of Minnesota (2014) Bachelor of Technology from Shri Guru Gobind Singhji Institute of Engineering and Technology (2011) Dr. Jaiswal's research program centers on revolutionizing edge computing through hardware innovations that integrate sensing and processing. His device-circuit co-design approach leverages alternate state variables to create energy-efficient systems for real-time applications, with particular emphasis on retina-inspired sensors and photonic memory architectures. This work bridges semiconductor physics with AI acceleration needs, targeting applications from autonomous systems to biomedical devices. Analysis of his 2023-2025 publications reveals dominant themes in photonic SRAM-based in-memory computing (40% of output), retina-inspired motion processing (30%), and secure hardware architectures (20%). His team consistently develops novel bitcell designs that enable XOR logic execution within memory arrays while maintaining compatibility with CMOS fabrication processes. Recent work shows increasing focus on biomedical applications of processing-in-pixel technology. His distinguished recognition includes: Three consecutive ISI Exploratory Research Awards (2020-2023) IEEE Brain Community Best Paper Award (2022) 27 issued US patents with multiple pending applications Nomination for USC Moore Inventor Fellowship (2022) Dr. Jaiswal actively mentors graduate researchers through ECE 790/890/990 courses while securing exploratory funding through ISI and Keston Foundation awards. His patent portfolio demonstrates exceptional translational impact, with industry game-changer classifications from USPTO. The 2022 VLSI-SoC nomination and multiple research highlights in major outlets validate his contributions to hardware security and neuromorphic vision sensors. His laboratory develops integrated hardware platforms combining magnetic tunnel junctions, photonic memory, and CMOS image sensors to create unified processing-in-sensor systems. Current projects include retina-inspired motion segmentation for event cameras and electro-optic frequency transducers for quantum computing interfaces, with strong industry collaboration through patent licensing.

Theo Damoulasمشاهده پروفایل

استاد

• Probabilistic Machine Learning
• Bayesian Statistics
• Digital Twins
• +۵ مورد دیگر

Theo Damoulas is a Professor of Machine Learning at the University of Warwick with a joint appointment in the Department of Computer Science and Statistics. He is a Turing AI Fellow (2021-2026) through UK Research and Innovation, an ELLIS member, and a Visiting Professor at New York University's Center for Urban Science and Progress (CUSP). He founded and leads the Warwick Machine Learning Group and has directed major projects at The Alan Turing Institute including Project Odysseus and the London Air Quality project. Education includes: PhD in Probabilistic Multiple Kernel Learning (University of Glasgow, 2009) MSc in Informatics (Distinction, University of Edinburgh, 2004) MEng in Mechanical Engineering (1st Class, University of Manchester, 2003) His research focuses on probabilistic machine learning and Bayesian statistics, emphasizing the integration of structural priors, spatiotemporal dependencies, physical laws, and causal relationships. Key applications include Digital Twins, urban science, and computational sustainability. His work advances robust and scalable inference methodologies for complex real-world systems. Publications demonstrate strong emphasis on Bayesian methods, spatiotemporal modeling, and uncertainty quantification, with applications spanning battery modeling, urban mobility, federated learning, and causal inference. Recent work shows increased focus on physics-informed models, federated learning frameworks, and causal abstraction techniques. Major scientific awards: Turing AI Acceleration Fellowship (2021-2026) Best Paper Awards (Wilkes 2024, AISTATS 2022, IEEE ICMLA 2010) ACM SIGMOD Most Reproducible Paper (2017) Dissertation Award (Classification Society 2012) Teaching Excellence nominations (Warwick 2015-2017) He actively advises PhD students and secured significant grants including the £multi-million Turing AI Fellowship. Current doctoral researchers investigate federated learning, causal inference, and spatiotemporal modeling. He leads the Warwick Machine Learning Group, a cross-departmental team developing foundational ML methods for scientific and societal challenges.

Yayun Duمشاهده پروفایل

استادیار

• Bioelectronics
• Intelligent Systems
• Wearable and Implantable Sensors
• +۷ مورد دیگر

Dr. Yayun Du is an Assistant Professor in the Department of Electrical and Computer Engineering at Vanderbilt University School of Engineering. She holds a Ph.D. in Robotics and System Control (Minor: Solid Mechanics) from UCLA (2022) and was a postdoctoral scholar at Northwestern University's Rogers Group through 2024. Current faculty at Vanderbilt University Ph.D. from University of California, Los Angeles Postdoctoral experience at Northwestern University Her research integrates bioelectronics and robotics through three core directions: 1) Developing multimodal wearable/implantable sensors for health monitoring, 2) Creating human-in-the-loop interaction systems using brain-computer interfaces, and 3) Applying machine learning to medical environment robotics. She has deployed four sensor types across seven hospitals globally, serving users from neonates to elderly patients. Dr. Du's recent publications focus on wireless bioelectronic devices ( PNAS ), sustainable sensor materials ( ACS Sustainable Chemistry & Engineering ), and agricultural robotics ( ICRA , IROS ). She serves as Associate Editor for ICRA 2025 and has received two Best Paper Award final nominations at IROS 2021. Finalist - Best Paper Award in Agri-Robotics (IROS 2021) Finalist - Best Paper Award in Robot Mechanisms and Design (IROS 2021) As head of the Du Group, she leads interdisciplinary research with applications in both healthcare and agricultural contexts, collaborating with Vanderbilt Institute for Surgery and Engineering (VISE) and clinical partners. Her work emphasizes deployable systems that transition from academic research to real-world implementation in medical and industrial environments.

Aleksandar Kosticمشاهده پروفایل

مدرس

• Philosophy of Architecture
• Design Theory
• Architectural Design
• +۵ مورد دیگر

Aleksandar Kostic is a Lecturer in the Department of Architecture and Built Environment at South East Technological University (SETU), where he also serves as Lead Researcher. He holds a PhD from University College Dublin, awarded in 2022, and is actively contributing to the academic and professional architecture community. PhD in Design Theory, University College Dublin (2022) His research lies at the intersection of philosophy and architectural design, with a strong focus on design theory, epistemology, ethics, and aesthetics. He explores fundamental questions such as aporia (intellectual impasses) in design, the influence of Platonic philosophy, and the ethical responsibilities of architects. His work emphasizes critical thinking and philosophical inquiry in architectural practice and education. The trends in his publications reveal a consistent engagement with philosophical concepts applied to architectural problems. From examining 'aporetic' design challenges to analyzing Plato’s views on expertise, his research bridges abstract thought and practical design. Recent works continue this trajectory, addressing ethical values, non-material aspects of design, and the role of contradiction in innovation. Nomination for MIES EU Award for Architecture (2009) Aleksandar Kostic advises PhD students and is actively involved in research dissemination through publications, peer-review, and conference organization. He serves on the steering committee of the All Ireland Architecture Research Group and is a member of the Centre for Platonic Studies at Trinity College Dublin and the Royal Institute of the Architects of Ireland. His peer-review activities include journals such as She JI and Building Material . He is a key member of the Architecture Research Group at SETU and collaborates across disciplines, particularly with philosophy. His upcoming activity includes organizing the 'Ethics in Architecture' conference in 2025, highlighting his leadership in integrating ethical discourse into architectural research.

Claudia Schwabeمشاهده پروفایل

استاد

• German Studies
• Romantic Literature
• Fairy Tales
• +۱۲ مورد دیگر

Claudia Schwabe is a Professor in the Department of World Languages and Cultures at Utah State University, within the College of Humanities and Social Sciences. She holds a Ph.D. in German Studies from the University of Florida and has been teaching at USU since 2012. Her academic work bridges German language, literature, and cultural studies with a strong focus on fairy tales and folklore in both historical and contemporary contexts. Education: Ph.D., German Studies, University of Florida, 2012 M.A., Teaching Business Education, Georgia College & State University, 2005 B.A., International Business Administration, Northumbria University, UK, 2003 B.A., International Administrative Management, Accadis, Germany, 2003 Her research centers on 18th- and 19th-century Romantic literature, literary and folk fairy tales (Kunstmärchen), East German cinema, German Orientalism, and the adaptation of fairy tales in new media and popular culture. She explores how traditional narratives are transformed across media and cultures, especially in American television and film. Her teaching reflects this interdisciplinary approach, covering German language, literature, film, business German, and translation. Her recent scholarly publications reveal a strong trend in analyzing the cultural and political significance of fairy tales, particularly in DEFA films and modern adaptations like Grimm and Once Upon a Time . She has published monographs, edited volumes, and peer-reviewed articles with leading presses and journals in folklore and German studies, demonstrating sustained scholarly impact. Scientific Awards and Honors: Faculty Undergraduate Advisor of the Year Award, LPCS, USU (2015) Ed Glatfelter Service Award, LPCS, USU (2016-2017) Nominations for Dean’s Giraffe Award (2016, 2018) Nominations for Researcher of the Year (2016, 2017) Travel Awards from College of Humanities and Social Sciences and Center for Women and Gender Studies (2014) Graduate Student Teaching Award, University of Florida (2010) Grinter Fellowship, University of Florida (2008–2010) Claudia Schwabe has been actively involved in academic service, grant writing (participant in grant proposal seminar), and mentoring. She has served as a faculty advisor and contributed to curriculum development, particularly in interdisciplinary folklore and fairy-tale pedagogy. Her editorial work on volumes like New Approaches to Teaching Folk and Fairy Tales highlights her leadership in shaping scholarly discourse. She has also reviewed books for major journals, contributing to peer evaluation in her field. While no formal lab or research team is mentioned, her work is deeply collaborative, involving co-edited volumes, co-authored entries, and invitations to contribute to high-impact academic projects. Her ongoing research suggests continued exploration of fairy tales in global media, pedagogy, and cultural politics.

Susana Castro-Kempمشاهده پروفایل

دانشیار

• Inclusive Education
• Special Educational Needs and Disabilities
• Education Policy
• +۷ مورد دیگر

Dr. Susana Castro-Kemp is an Associate Professor in Psychology and Human Development at University College London's Institute of Education (IOE), where she serves as Director of the Centre for Inclusive Education (CIE) since September 2023. Previously, she was a Reader in Education at the University of Roehampton for eight years. Her work focuses on inclusive education policy and practice globally, with particular expertise in special educational needs and disabilities (SEND), early childhood intervention, and mental health in schools. The IOE has been ranked number one in the world for Education for several consecutive years, providing an ideal environment for her impactful research. Dr. Castro-Kemp holds a PhD in Psychology jointly awarded in 2012 by the University of Porto (Portugal) and the University of North Carolina at Chapel Hill (USA). Her doctoral research was fully funded by the Foundation for Science and Technology/European Commission and the Global Education and Development Studies scholarships. She is a Chartered Psychologist with the British Psychological Society, a Senior Fellow of Advance HE, and a Recognised Research Supervisor by the UK Council for Graduate Education. Dr. Castro-Kemp's research centers on policy regulating education, health, and welfare services for children, particularly those with support needs. She examines inclusive education practices from users' perspectives, policy models leading to effective inclusive pedagogy, and country-level policy impacts on outcomes for children with special educational needs. Her work moves away from diagnostic labels toward engagement and civic participation as educational outcomes. She also investigates inclusion and early intervention in low- and middle-income countries, mental health in schools, and quality of early childhood education. Her recent publications reveal several key trends in inclusive education research. There's growing emphasis on understanding educational experiences through the voices of children and families rather than diagnostic labels. Much of her work examines the implementation gap between inclusive education policy and classroom practice. She has conducted significant research on how children with special educational needs experienced the pandemic, revealing both challenges and unexpected "silver linings" for some groups. Her corpus analysis of Ofsted reports shows narrow focus in early childhood education inspections, while her work on SEND policy increasingly takes an international comparative approach. Dr. Castro-Kemp has received recognition for her impactful work, including: Best Digital Humanities Project for Community Engagement Prize (2023) from the National Institute of Humanities and Social Sciences of South Africa for her project "Optimising collaborations and reducing inequalities of Early Childhood Intervention in post-Covid-19 South Africa" Dr. Castro-Kemp has secured approximately £1.3 million in research funding from various sources including ESRC, British Academy/Leverhulme Trust, European Commission, and private sponsors. Her current major project is 'ScopeSEND' (2024-2026), funded by the Nuffield Foundation (£250,000), examining international SEND policies. She has led numerous projects including "Transdisciplinary provision for children with disabilities in the Global South" (£3,500), "Optimising collaborations in South Africa" (£47,200), and "Froebel meets Ofsted" (£19,185). As a supervisor, she mentors MA/MSc and PhD students in education policy, early childhood, and inclusive education, having been nominated for student choice awards for excellent feedback and outstanding research supervision. As Director of the UCL Centre for Inclusive Education since 2023, Dr. Castro-Kemp leads a team focused on advancing knowledge exchange and research in inclusion and special needs. The Centre works with schools, educators, parents, and early years settings to translate research into practice. Her international collaborations include work with the World Health Organization as a technical advisor on the use of the International Classification of Functioning, Disability and Health (ICF) system in educational contexts. She also serves on the SEN Policy Research Forum and has provided oral evidence to the House of Commons Education Select Committee.

Richard Garnerمشاهده پروفایل

مدرس

• Category Theory
• Algebraic Structures
• Homotopy Type Theory
• +۳ مورد دیگر

Richard Garner is a lecturer at Macquarie University's School of Mathematical and Physical Sciences, Faculty of Science and Engineering. He specializes in teaching mathematics to engineering and computing students in units like MATH2055 and MATH1007, focusing on problem-solving and real-world applications. His teaching philosophy emphasizes authentic mathematical experiences, blending abstract concepts with practical examples, such as connecting multivariable calculus to AI technologies. School: School of Mathematical and Physical Sciences University: Macquarie University Teaching Areas: Mathematics for engineering and computing, convolution, multivariable calculus Richard won a Student Nominated Award in the 2023 Vice Chancellor’s Learning and Teaching Awards, reflecting his commitment to student-centered education. He prioritizes clarity in course design, using visual tools and accessible materials to enhance learning, and fosters a supportive environment where students feel comfortable asking questions. Key Teaching Strategies Organized iLearn layouts following Macquarie University's standards Multiple formats for lecture materials (diagrams, color-coded slides) Weekly task clarity and real-world problem framing Live worked examples and transparent success criteria His research spans category theory, computational effects, and homotopy theory, with publications on topics like comodels, monoidal bicategories, and enriched categories. Richard's work bridges abstract mathematics with applications in computer science and logic. Scientific Awards 2023 Vice Chancellor’s Learning and Teaching Award (Student Nominated) Students praise his ability to make complex concepts intuitive, his enthusiasm for mathematics, and his dedication to explaining the 'why' behind the subject. His teaching design, including time-sensitive banners and structured weekly content, has been highlighted as exemplary.

• Chinese Language Pedagogy
• Chinese Linguistics
• Chinese Cinema
• +۵ مورد دیگر

Zhiqiang Yu serves as an Associate Professor in the Department of Modern Languages and Comparative Literature at Baruch College's Weissman School of Arts and Sciences, City University of New York. With over two decades of teaching experience, he has established himself as a dedicated educator specializing in Chinese language, cinema, and civilization courses. Education: Ph.D. in Chinese, University of Washington M.A. in Asian Civilization, University of Iowa B.A. in Chinese Literature, Fudan University (Shanghai) Professor Yu's research focuses on innovative approaches to Chinese language pedagogy, with particular interest in applying economic principles and artificial intelligence to language teaching. His work bridges traditional linguistic scholarship with modern educational technology, examining how efficiency, resource allocation, and technological advancements can enhance language learning outcomes. His research spans Chinese linguistics, dialectology, cinema studies, and cultural elements in language teaching. His publication record reveals a consistent trajectory toward optimizing language instruction through systematic analysis. Recent work increasingly focuses on AI applications in language education and the economic framework of pedagogical efficiency. His scholarship demonstrates a progression from traditional linguistic analysis toward innovative teaching methodologies that incorporate modern technological and theoretical frameworks. Scientific Awards: Award of Excellent Academic Research Reviewer from Journal of International Chinese Education (2016) Graduate Teaching Fellowship from University of Washington (1993) Graduate Teaching Fellowship from University of Iowa (1989) Graduate Research Fellowship from University of Iowa (1988) Student Excellency Award from Fudan University (1984) Professor Yu has served extensively on departmental committees including as Department Assessment Coordinator and Secretary of the Asian and Asian-American Studies Committee. He has organized numerous academic events featuring prominent Chinese cultural figures and has contributed to developing Chinese language curriculum resources including online placement tests. His professional service extends to editorial work for CUNY publications and Chinese language training for the New York Police Academy. He maintains active involvement with multiple professional organizations including the American Name Society, American Oriental Society, American Society of Geolinguistics, Association for Asian Studies, and Chinese Language Teachers Association, frequently presenting at international conferences on Chinese language pedagogy.

Steven Andrew Culpepperمشاهده پروفایل

استاد

• Quantitative Methods in the Social Sciences
• Psychometrics
• Latent Class Models
• +۶ مورد دیگر

Steven Andrew Culpepper is a Professor of Statistics at the University of Illinois at Urbana-Champaign, holding additional appointments as Professor in the Beckman Institute for Advanced Science and Technology, Psychology, and Educational Psychology. He specializes in quantitative methods for social sciences, focusing on psychometric models, latent class analysis, and statistical computing. Education: PhD, Educational Psychology, University of Minnesota, 2006 BS, Economics, Bowling Green State University, 2001 Research interests include advanced statistical methodologies such as latent class models, high-stakes testing analysis, and applications of Bayesian computing in education and organizational research. His work emphasizes improving large-scale assessment systems through innovative modeling approaches. His publications consistently address latent structure modeling, cognitive diagnosis frameworks, and methodological advancements in educational and behavioral statistics. While no scientific awards are explicitly listed, his contributions to psychometric theory and statistical software development are notable. Steven has grants and consulting projects related to statistical methodologies but specific grant details are not provided in the texts. He has no listed advisees/PhD students in the provided information. He collaborates across disciplines through affiliations with the Beckman Institute and maintains active software development projects, including R packages like 'rrum' and 'pathmodelfit'.

Carey E. Priebeمشاهده پروفایل

استاد

• computational statistics
• statistical pattern recognition
• statistical image analysis
• +۵ مورد دیگر

Carey E. Priebe is a Professor in the Department of Applied Mathematics and Statistics at the Whiting School of Engineering, Johns Hopkins University. He maintains strong affiliations with multiple research centers including the Johns Hopkins University Center for Imaging Science, the Mathematical Institute for Data Science, and the Human Language Technology Center of Excellence. His academic career spans several decades with significant contributions to statistical methodology and theory. Dr. Priebe's research focuses on computational statistics, statistical pattern recognition, and statistical inference for high-dimensional and graph data. His work bridges theoretical statistics with practical applications in areas such as brain connectome mapping, network analysis, and image processing. He has made significant contributions to spectral graph theory, graph matching, and vertex nomination, with applications ranging from neuroscience to national security. His publication record demonstrates consistent contributions to statistical methodology, with a notable emphasis on graph-based statistical methods. His research trajectory shows increasing focus on network data analysis, particularly in the last decade, with applications to brain mapping and connectome analysis as evidenced by his NSF BRAIN Initiative grant and Nature publication. 2013 Erskine Fellow (University of Canterbury) 2011 McDonald Award for Excellence in Mentoring and Advising 2010 ASA SDNS Distinguished Achievement Award 2009 Erskine Fellow (University of Canterbury) 2008 National Security Science and Engineering Faculty Fellow 2008 Pond Award for Excellence in Teaching NSF BRAIN EAGER grant recipient (2014) Professor Priebe has supervised an extensive number of doctoral students whose work spans statistical methodology, network analysis, and machine learning. His students have secured positions at prestigious institutions including academia (University of Wisconsin, Boston University), government research labs, and major technology companies (Microsoft, Facebook, Amazon). His research has been supported by significant grants from NSF, DARPA, and other agencies focused on national security applications and fundamental statistical methodology development. He maintains active collaborations across multiple disciplines and institutions, as evidenced by his numerous conference presentations and visiting appointments including at The Alan Turing Institute and The Isaac Newton Institute. His work bridges theoretical statistics with practical applications in neuroscience, security, and data science.

• Graph Representation Learning
• Graph Neural Networks
• Deep Generative Models
• +۵ مورد دیگر

Jian Tang is an Assistant Professor at HEC Montréal and a core member of the Montreal Institute for Learning Algorithms (MILA). His research focuses on graph representation learning, generative models, and their applications in drug discovery and material science. Prior to this, he was a postdoctoral researcher at the University of Michigan and Carnegie Mellon University, and a researcher at Microsoft Research Asia (2014-2016). He has received several prestigious recognitions, including the Canada CIFAR Artificial Intelligence Chairs (CCAI Chair) and best paper nominations at WWW’16. His work on LINE (WWW’15) was recognized as the most cited paper in its year. Tang’s research spans theoretical foundations and practical systems, such as GraphVite for scalable graph embedding and TorchDrug for drug discovery. Key research interests include geometric deep learning for molecular structures, generative models for protein design, and neural-symbolic reasoning for knowledge graphs. He actively collaborates with leading biological labs and leverages industry partnerships for GPU resources. Recent publications emphasize molecular property prediction, 3D conformation generation, and algorithmic reasoning frameworks. He has secured grants from IBM/MILA, Amazon, and the National Research Council Canada, supporting projects like molecular pretraining and geometric representation learning. Tang teaches courses on graph representation learning and deep learning, and mentors a vibrant team of PhD and master’s students. His lab has developed impactful software tools like LINE, PTE, and LargeVis, widely used in the research community.

Carolyn Rouseمشاهده پروفایل

استاد

• Development
• Medical Anthropology
• Visual Anthropology
• +۷ مورد دیگر

Carolyn Rouse is the Ritter Professor of Anthropology at Princeton University and an HMEI Associated Faculty member in the Grand Challenges Program. Her work interrogates the intersections of race, religion, healthcare disparities, and development through ethnographic and visual anthropological methods. Research Interests: Development, medical anthropology, visual anthropology, resistance, critical race theory, consciousness, North America, Ghana, environmental humanities, and environmental policy/ethics. Key Affiliations: Department of Anthropology, Princeton University; Environmental Humanities and Environmental Policy and Ethics through HMEI Grand Challenges Program. Her research critically examines how evidence shapes narratives of social inequality, particularly in healthcare access, racial disparities, and international development. She authored Engaged Surrender , Uncertain Suffering , and Televised Redemption , and created the Ethnographic Data Visualization Lab (VizE Lab) in 2016 to bridge biological and social scientific data. Recent publications explore necropolitics, liberal bias in the Trump era, and epistemological challenges in evidence-based policy. Her films include Chicks in White Satin (Academy Award-nominated), Purification to Prozac , and Listening as a Radical Act . Scientific Awards: 1995 American Anthropological Association Award for Excellence ( Tales from Arab Detroit ) Academy Award nomination for Chicks in White Satin

Sanjeev Baskiyarمشاهده پروفایل

استاد

• Scheduling and Cloud Computing
• Computer Architecture
• Real-time and Embedded Computing
• +۱۱ مورد دیگر

Sanjeev Baskiyar is a Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. He has been actively involved in research, teaching, and academic leadership, with a strong focus on computer systems, real-time and embedded computing, scheduling, cloud and fog computing, and energy-aware architectures. Education: Ph.D., Electrical and Computer Engineering, University of Minnesota M.S., Electrical and Computer Engineering, University of Minnesota B.S., Electronics and Communications, Indian Institute of Science, Bangalore B.S., Physics (with honors), and distinction in Mathematics Dr. Baskiyar’s research interests span scheduling, real-time and embedded systems, computer architecture, fog/cloud computing, thermal/energy-aware computing, and STEM education. His recent work explores machine learning applications in scheduling and quantum computing for fake news detection. He has supervised over 25 graduate students, many of whom now hold academic and industry positions. His recent publications emphasize fog computing simulation, service placement, quantum-inspired fake news detection, and adaptive scheduling using machine learning. These works reflect a trend towards intelligent, scalable, and energy-efficient computing systems, particularly in distributed and edge environments. Scientific Awards and Honors: Walker Teaching Excellence Award, Auburn University, 2020 Summer Faculty Fellow, Air Force Research Labs, 2020 Nominated Best Teaching Assistant, University of Minnesota, 1992 Multiples Merit and State-merit Scholarships Honors in Physics and Distinction in Mathematics Dr. Baskiyar has successfully advised numerous MS and PhD students and secured over $2 million in research funding as Principal Investigator from the National Science Foundation, DARPA, NASA, and industry partners like Wind River Systems and Mentor Graphics. His grants focus on parallel computing education, real-time micro-architectures, and embedded systems. He has also served on editorial boards, program committees, and as a reviewer for NSF and IEEE journals. He has held leadership roles including Senator in the University Faculty Senate and Chair of the E-day Committee. Labs and Research Groups: While not explicitly named, Dr. Baskiyar leads a research group focused on computer systems, scheduling, and embedded computing, as evidenced by his long list of graduate student supervision and funded projects in fog, cloud, and real-time systems.