Zhonghai Lu is a Professor of Electronic Systems Design (specializing in Dependable and Autonomous Systems) at KTH Royal Institute of Technology, part of the Department of Electrical Engineering in the School of Electrical Engineering and Computer Science (EECS). He serves as Program Director for KTH's Embedded Systems master's program and Director of Studies at the Division of Electronics and Embedded Systems. His research focuses on Network-on-Chip (NoC), computer architecture, embedded systems, and Prognostics and Health Management (PHM) of power electronics. He leads a research group exploring in-network processing and embedded intelligence, transforming passive networks into active computational frameworks. Lu holds a BSc from Beijing Normal University (1989), MSc and PhD from KTH (2002, 2007), and an MBA in Innovation and Growth from the University of Turku (2012). He has authored over 240 scientific papers, including journal articles and peer-reviewed conferences, with notable recognitions such as Best Paper Awards at NOCS’2015 and EU HiPEAC, and a Featured Paper in IEEE Transactions on Computers (2020). He serves as Associate Editor for ACM Transactions on Architecture and Code Optimization (TACO) and has chaired major conferences like HiPEAC’2017 and NOCS’2018. His research group’s recent work includes integrating AI into hardware acceleration, fault-tolerant neural networks, and RUL estimation for power electronics using recurrent neural networks. Lu has secured grants from the Swedish Research Council and Intel Corporation and developed courses like IL2230 (Hardware Architectures for Deep Learning) and IL2233 (Embedded Intelligence), pioneering embedded AI education at KTH. Education: BSc (Beijing Normal University), MSc/PhD (KTH), MBA (University of Turku) Awards: Best Paper Awards (NOCS, EU HiPEAC), Swedish Research Council Grants, Intel Research Gifts Labs/Teams: Research Group on In-Network Processing and Embedded Intelligence
Sishuai Gong is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill, focusing on system reliability and security. His research bridges machine learning, software engineering, and computer architecture to address challenges in large-scale software systems. Education : Ph.D. in Computer Science from Purdue University (2025), B.S. in Computer Science from the University of Science and Technology of China (2019). Research Interests : System reliability and security, kernel concurrency testing, verified security modules, and machine learning for systems. He develops interdisciplinary techniques to identify and mitigate functional interference bugs in OS virtualization and latency-sensitive applications. Scientific Awards : Jay Lepreau Best Paper Award at OSDI (2024) Google Cloud Research Innovator (2024) Bilsland Dissertation Fellowship at Purdue (2024) Teaching : Offering COMP 790: Reliable and Secure Systems (Fall 2025) with a focus on empirical studies, static/dynamic analysis, and machine learning for systems. Course grading includes paper presentations (30%), class participation (30%), and research projects (40%).
John P. O'Doherty serves as the Fletcher Jones Professor of Decision Neuroscience within Caltech's Division of Humanities and Social Sciences, holding continuous faculty appointments since 2004 (Assistant Professor 2004-07, Associate Professor 2007-09, Professor 2009-present, Fletcher Jones Professor 2021-present). He previously directed the Caltech Brain Imaging Center (2013-17) and maintains affiliations with the T&C Chen Center for Social and Decision Neuroscience. His educational background includes a B.A. from University of Dublin, Trinity College (1996) and D.Phil. from University of Oxford (2000). His research focuses on computational and neural mechanisms of reward-based learning and decision-making , employing fMRI, intracranial recordings, and mathematical modeling to investigate how the brain solves complex decision problems through evolutionarily conserved algorithms. Key areas include Reinforcement learning systems (model-based/model-free arbitration) Observational and social learning mechanisms Neural representation of value, risk, and uncertainty Computational phenotyping of mental disorders Temporal dynamics of goal persistence Analysis of his 2023-2025 publications reveals dominant trends in computational psychiatry (problem gambling, autism traits), hierarchical decision-making, and neuroeconomic modeling of social behavior. His work consistently integrates cross-species computational frameworks with human neuroimaging to identify transdiagnostic mechanisms. While specific awards beyond his endowed professorship aren't detailed, his leadership as Brain Imaging Center Director and prolific high-impact publications demonstrate significant recognition. Current advising includes graduate researcher Sneha Aenugu on goal-persistence projects, with administrative support from Mary A. Martin (mmartin@caltech.edu). His active research program continues to pioneer computational approaches to understanding decision pathologies.
Frank L. Hammond III serves as Assistant Professor at Georgia Tech's Woodruff School of Mechanical Engineering since April 2015, directing the Adaptation Robotic Manipulation (ARM) Laboratory. A Carnegie Mellon PhD graduate, he previously held postdoctoral positions at MIT and Harvard as a Ford Fellow. His interdisciplinary work bridges mechanical engineering, biomedical applications, and computational design. Education Ph.D. in Mechanical Engineering, Carnegie Mellon University M.S. in Mechanical Engineering, University of Pennsylvania M.S. in Electrical Engineering, University of Pennsylvania B.S. in Electrical Engineering & Biomedical Engineering, Drexel University Hammond's research pioneers adaptive robotic manipulation (ARM) systems that operate in unstructured human environments through bioinspired computational design. His lab develops xenomorphic (non-biomorphic) robots using soft pneumatic actuation, flexible electronics, and machine learning to achieve biological-level versatility. Key application domains include wearable human augmentation devices , haptic-enabled surgical teleoperation , and autonomous soft platforms for medical and industrial use. The ARM methodology integrates empirical biomechanics characterization with simulation-driven optimization and rapid prototyping. Analysis of his 15 most recent publications (2023-2025) reveals three dominant trends: (1) Medical rehabilitation breakthroughs through intention-driven exoskeletons with soft bioelectronics, (2) Novel locomotion strategies for soft robots in complex environments (sand, water, cluttered spaces), and (3) Advanced haptic feedback systems leveraging multimodal sensory substitution for proprioceptive restoration. These works consistently bridge biomechanics, control theory, and human factors. Awards Ford Postdoctoral Research Fellowship at Harvard School of Engineering Hammond actively mentors graduate researchers including PhD candidates Lucas Tiziani (soft actuators) and Bangyuan Liu (earthworm robotics), and Master's student Alex Hart (pediatric haptics). His lab secures research funding for projects like tunable mechanical interfaces for neuropathy treatment and cognition-focused wearable devices, with strong industry and clinical partnerships evident in co-authored medical device publications. The ARM Lab maintains robust collaborations across Georgia Tech's robotics, neuroscience, and biomedical engineering communities. The Adaptation Robotic Manipulation Laboratory operates from Whitaker Building Room 4102, housing specialized facilities for soft robot fabrication (3D printing, shape deposition manufacturing) and biomechanics testing. Current projects include pediatric haptic feedback displays, biomimetic swimming robots, and kirigami-skinned earthworm robots for subsurface locomotion. The lab emphasizes translational research with multiple pending medical device patents and active participation in K-12 STEM outreach programs.
Anantha Chandrakasan is the Vannevar Bush Professor of Electrical Engineering and Computer Science at MIT, serving as Dean of the MIT School of Engineering and Chief Innovation and Strategy Officer. His research focuses on energy-efficient integrated circuits, medical devices, and AI hardware security. He leads the MIT Energy-Efficient Circuits and Systems Group, developing systems for biomedical applications, wireless communication, and quantum computing. He holds appointments at MIT's Microsystems Technology Laboratories and has contributed to collaborations like the MIT-Takeda Program in AI-driven healthcare and a partnership with GlobalFoundries for energy-efficient AI chips. His work spans implantable drug delivery systems, conformable ultrasound patches, and secure edge computing architectures. Chandrakasan's innovations include ultra-low-power circuits for IoT devices, cryptographic processors for post-quantum security, and AI accelerators for edge applications. He emphasizes interdisciplinary research bridging electrical engineering with biomedical and quantum fields, supported by leadership roles in MIT's strategic initiatives. His contributions to energy-efficient computing have led to advancements in wearable health monitors, batteryless sensors, and secure communication protocols for medical devices. Ongoing projects include THz integrated systems and AI-enhanced analog circuit design optimization.
Peter Strasser is a Full Professor of Chemistry and Chemical Engineering at the Technical University Berlin, Germany. He holds a Diplom (MSc) in Physical Chemistry from Tübingen University (1995) and a PhD from the Fritz-Haber-Institute of the Max-Planck-Society (1999), supervised by Prof. Gerhard Ertl. His research focuses on electrocatalysis, CO₂ electroreduction, and materials science for energy storage/conversion. He has held roles at the University of Houston (2004–2007) and Symyx Technologies (2000–2004). Education : Tübingen University (1988–1995), Stanford University (1991), Università di Pisa (1992) Affiliations : German Chemical Society (GDCH) leadership roles, Electrochemical Society (ECS) committee memberships Research interests include structure-function relations in electrocatalysts, electrochemical oxygen evolution/reduction reactions, and in-situ spectroscopic techniques. He has organized major conferences such as the “Electrochemistry 2022” meeting and co-chairs symposia on fuel cells and electrolyzers. His entrepreneurial activities include mentoring startups like DexLeChem GmbH and LiquidLoop GmbH. Awards : Carl Wagner Memorial Award (2023), Faraday Medal (2021), Otto-Hahn Medal (2000) Grants/Advising : Extensive funding and mentorship in energy materials research He leads the Technische Chemie division at TU Berlin and collaborates internationally, including guest professorships in China. His work bridges fundamental electrochemistry with industrial applications in renewable energy systems.
Asma Sayeed is an Associate Professor and Program Director of Islamic Studies at UCLA's Near Eastern Languages and Cultures department, part of the UCLA College. She holds a PhD in Near Eastern Studies from Princeton University (2005) and previously served as an Assistant Professor at Lafayette College. Her research focuses on early Muslim social history, Muslim education, gender studies, and hadith transmission by women. She has authored Women and the Transmission of Religious Knowledge in Islam (2013) and contributed to numerous journals and encyclopedias. Sayeed received a Fulbright Fellowship (2010) for archival research on Muslim women’s education in Syria. She teaches courses such as 'Introduction to Islam' and graduate seminars on research methodologies. Her current work examines textual practices in Muslim education across historical contexts. Education: PhD, Near Eastern Studies, Princeton University (2005) MA, History, Binghamton University (1994) BA, Politics, Princeton University (1991) Certificate in Near Eastern Studies, Princeton University (1991) Research Interests: Her scholarship emphasizes women’s roles in religious knowledge transmission, legal and social history intersections, and medieval Muslim educational systems. She frequently addresses how gender shaped access to religious authority and spaces. Awards: Fulbright Fellowship (2010) Teaching and Professional Engagement: Sayeed’s courses cover Quranic studies, Islam in the West, and methodological frameworks in Islamic studies. She actively participates in academic conferences and initiatives, including keynote lectures on women’s intellectual engagement in classical Islam and digital humanities projects mapping women’s educational histories.
John D. Murray is the Gregg L. Engles Associate Professor of Psychological and Brain Sciences at Dartmouth College and an Adjunct Associate Professor of Psychiatry at Yale School of Medicine. He holds a PhD in Physics from Yale University (2013) and a BS in Physics and Mathematics from Yale (2006). His research focuses on computational neuroscience and computational psychiatry, with secondary appointments in Physics and Neuroscience at Yale until 2023. His work integrates computational modeling, neuroimaging, and systems neuroscience to study decision-making processes, cortical organization, and psychiatric disorders. Collaborators include prominent researchers like Dr. John Krystal and Dr. Anticevic. Research interests include hierarchical brain organization, neuroimaging analysis techniques, and pharmacological effects on neural circuits. His lab (Murray Lab) develops computational tools like PsychRNN for cognitive task modeling. Notable contributions include linking transcriptomic data to neuroimaging patterns and modeling LSD’s effects on brain topography. He has been featured in YaleNews and Nature Communications for innovations in mapping mental illness variability and neural circuit dynamics. Grants and collaborations span translational neuroscience, addiction, and PTSD research through partnerships with Yale’s Center for Biomedical Data Science and VA National Center for PTSD. His interdisciplinary approach bridges physics, computer science, and clinical psychiatry to advance understanding of brain function and dysfunction.
Felicity McArdle is a Professor in the Department of Early Childhood Education within the Faculty of Education at Queensland University of Technology. With a distinguished career spanning over two decades, her work centers on reimagining early childhood pedagogy through critical lenses of social justice, art education, and play-based learning. Her research has significantly influenced Australian early childhood policy and practice. McArdle's research interests demonstrate a consistent commitment to transformative education. She critically examines how art and play function as vehicles for social justice, challenging neoliberal discourses in early childhood education. Her work on refugee children's artistic expression and anti-bias curriculum development reveals her dedication to equity-oriented pedagogy. Through collaborative drawing methodologies and visual research approaches, she has pioneered innovative ways of understanding children's perspectives. Her publication trends reveal a sophisticated evolution from foundational work on visual arts in education (2001-2010) toward increasingly critical examinations of power, policy, and social justice (2011-2021). The consistent citation impact of her work—particularly her 2002 paper 'Early Childhood Art Education: A Palimpsest' with over 13,000 citations—demonstrates her field-defining contributions to reconceptualizing art education as critical praxis. McArdle has held significant editorial roles including co-editing the influential 2013 volume 'Young Children, Pedagogy and the Arts' and serving on the editorial board of Australian Journal of Early Childhood. Her collaborations with leading scholars like Susan Grieshaber, Jennifer Sumsion, and Linda Knight have produced seminal work on intentional teaching and play-based learning. Her research methodology expertise centers on visual and arts-based approaches, particularly collaborative drawing techniques that engage children as active research participants. This methodological innovation reflects her commitment to ethical research practices that honor children's agency while generating meaningful insights about early childhood experiences.
Julia R. Greer serves as the Ruben F. and Donna Mettler Professor of Materials Science, Mechanics and Medical Engineering at the California Institute of Technology (Caltech), where she also holds the position of Executive Officer for Applied Physics and Materials Science since 2025. She earned her B.S. from MIT (1997) and M.S./Ph.D. from Stanford University (2000/2005), joining Caltech as Assistant Professor in 2007, promoted to Professor in 2013, and appointed to her current named professorship in 2019. Her research spans mechanics of hierarchical architectures , nanomaterials , and additive manufacturing , with significant contributions to energy storage systems and biomedical materials . Key focus areas include nano-scale mechanical properties, in-situ deformation analysis, and development of novel fabrication techniques for micro-architected materials. Her group pioneered hydrogel infusion additive manufacturing for metals and multiphoton 3D lithography standards. Analysis of recent publications reveals strong emphasis on solid-state battery interfaces (2025), bioresorbable microrobots (2024), and AI-enabled material design (2024), demonstrating cross-disciplinary impact across energy, healthcare, and quantum technologies. Her work consistently bridges fundamental nanomechanics with practical applications in energy storage and medical devices. 2024 ASME Nadai Medal 2024 SES A.C. Eringen Medal Elected to National Academy of Sciences (2025) Fletcher Jones Foundation Director (2019-2025) Professor Greer has advised over 40 PhD students including Seola Lee (2025) and Wenxin Zhang (2025), with research funded by collaborations spanning MIT, UCSF, Purdue, and ETH Zurich. Her group maintains active projects in lightweight nanoarchitected materials for impact absorption, electroactive polymers for braille devices, and 3D interdigitated solid-state batteries. Current leadership includes Editor-in-Chief of the Journal of Applied Physics (2024-) and direction of Caltech's Materials Science department.
Martha Ann Bell is a University Distinguished Professor of Psychology and College of Science Faculty Fellow at Virginia Tech. She leads the Cognition, Affect, and Psychophysiology (CAP) Lab, focusing on developmental cognitive neuroscience and the integration of emotion and cognition in early development. Her work examines EEG/ECG biomarkers, executive function, temperament, and maternal-child interactions. Dr. Bell holds a PhD in Human Development from the University of Maryland (1992), an MS in Child and Family Studies from the University of Tennessee (1983), and a BS in Home Economics from Carson-Newman College (1978). She has held progressive roles from Assistant Professor (1996) to her current distinguished title. Her research interests include developmental changes in brain-behavior relations, neurophysiological correlates of emotion regulation, and longitudinal predictors of child development. Recent work explores maternal emotion coaching, EEG neuromarkers of ADHD, and the neurodevelopmental impacts of nutrition. Key awards include the Virginia Tech University Distinguished Professorship (2021) and College of Science Faculty Fellowship (2019–2025). Her publications span developmental psychobiology, neuroimaging methods, and temperament-behavior links. Dr. Bell’s advising and grants focus on interdisciplinary developmental science. The CAP Lab collaborates on projects involving infant neuroimaging, maternal-child physiology, and early childhood interventions.
Alexey Vladimirovich Vdovin is a Professor and Senior Research Fellow at the National Research University Higher School of Economics (HSE), working within the Faculty of Humanities and School of Philological Sciences. He began his tenure at HSE in 2012 and has accumulated 15 years of scientific and teaching experience. His academic journey includes a Doctor of Philology degree from HSE (2023), a PhD from the University of Tartu (2011), and his initial degree in 'Russian language and literature' from Vyatka State Humanitarian University (2007). He has held significant roles including Deputy Dean for Science at the Faculty of Humanities (2018-2020) and serves on numerous academic councils and committees. Vdovin's educational background demonstrates both depth and international perspective. After completing his undergraduate studies at Vyatka State Humanitarian University in 2007, he pursued doctoral studies at the University of Tartu, where he earned his PhD in 2011 with a dissertation on 'The concept of 'chapter of literature' in Russian criticism of the 1830-1860s.' His academic development has been enriched by numerous international experiences, including visiting researcher positions at Selwyn College, University of Cambridge (2019), Jordan Center at New York University (2017), and multiple research stays at Humboldt University in Berlin through the Aurora Erasmus Mundus program. Professor Vdovin's research focuses on Russian intellectual history, the history of ideas, the Russian Empire, Russian literature of the 19th century, and nationalism studies. His work particularly examines the formation of the Russian literary canon, representations of peasants in literature, and the relationship between literature and society. He has authored approximately 80 articles and 4 monographs on 19th-century Russian literature, culture, and criticism, with works on major figures like Turgenev, Dostoevsky, Tolstoy, Goncharov, Belinsky, Chernyshevsky, Dobrolyubov, and Nekrasov. His recent book 'Monsters at the Threshold: Dracula, Frankenstein, Viy and Other Literary Monsters' (2024) demonstrates his expanding interest in literary archetypes and cultural phenomena. Vdovin has received numerous awards and recognitions for his scholarly work, including the Moscow Government Prize for young scientists (2017), multiple 'Best Teacher' awards (2013-2015, 2017-2024), and recognition as a winner of HSE's competition for best Russian-language scientific works (2022, 2024). He has also received various letters of gratitude from HSE administration, the Faculty of Humanities, and the School of Philology for his contributions to academic life. As an advisor, Vdovin has supervised numerous student research projects, including Smirnova T.V.'s 2014 master's thesis on 'Representation of 'Russianness' and 'Otherness' in Russian essays of the 1840s.' He has also served as a curator for HSE's Personnel Reserve Program at the School of Philological Sciences and has been actively involved in dissertation councils. His research has been supported by significant grants, including a 2024-2025 Russian Science Foundation grant 'The Genre of 'Peasant Life Story' in Russian Literature Before 1861: Poetics, Plots, Socio-Cultural Functions' (No 24-28-00184) and a 2018-2020 RFBR grant on 'State and Literary Institutions: From Peter I's Reforms to the 'Great Reforms.' Professor Vdovin is actively engaged in academic communities beyond HSE, serving as editor-in-chief of the HSE preprint series 'Literary Studies' and participating in the Big Project 'Literature and Society: An Experience of Sociocultural Description.' He is also involved in public scholarship, frequently giving public lectures through platforms like 'Arzamas,' 'Postnauka,' and 'Stradarium,' and appearing on the 'Observer' television program (Culture channel). Since 2015, he has been a mentor at Maya Kucherskaya's Creative Writing School, bridging academic scholarship with creative practice.
Dr. Lourdes Pena-Castillo is a Professor jointly appointed in the Departments of Computer Science and Biology at Memorial University of Newfoundland's Faculty of Science. Her research focuses on applying machine learning and bioinformatics to study bacterial gene regulation, with emphasis on transcriptomics, gene expression pathways, and microbiology. She leads the Bioinformatics Lab at MUN, developing computational tools like Promotech for promoter prediction and sRNARFTarget for sRNA target identification. Education: BSc in Information Systems Engineering, ITESM-Mexico MSc in Computer Science, University of Alberta PhD in Computer Science (Doktoringenieurin), Otto-von-Guericke Universität Magdeburg Postdoc in Bioinformatics, University of Toronto Research Interests: Bioinformatics, Genomics, Machine Learning, Artificial Intelligence, Transcriptomics, Gene Regulation, Microbiology Her work integrates computational methods with biological data to address challenges in molecular biology, including analyzing bacterial sRNA functions, promoter recognition, and disease diagnostics using machine learning. She has advised numerous graduate students, including PhD candidates Purvikalyan Pallegar and Bonita McCuaig, and MSc students like Ruben Chevez-Guardado and Kratika Naskulwar. Her lab focuses on translational research with applications in both basic science and clinical contexts. Publications span computational methods for bacterial gene regulation, bioinformatics tool development, and interdisciplinary projects in VR and healthcare informatics. Her research has contributed to understanding symbiotic relationships in marine organisms, inflammatory bowel disease diagnostics, and clavulanic acid production in Streptomyces. Grants & Collaborations: Works with interdisciplinary teams across computer science and biology, supported by grants enabling projects in bacterial genomics and computational tool development. Labs & Teams: Leads the Bioinformatics Lab at MUN, fostering collaborations with researchers in microbiology, computer science, and healthcare.
Judith Driscoll is Professor of Materials Science at the University of Cambridge in the Department of Materials Science & Metallurgy. She holds the prestigious Royal Academy of Engineering Chair in Emerging Technologies and serves as a Visiting Staff Member at Los Alamos National Laboratory. As the founding Editor-in-Chief of APL Materials, she has significantly contributed to the materials science community. Dr. Driscoll's research focuses on Energy Efficient Oxide Materials for Information and Communications Technologies and energy devices. Her work spans the development of non-volatile memory, resistive switching devices, and ferroelectric materials for neuromorphic computing applications. She investigates oxide thin films for applications ranging from data storage to energy generation and conversion, with particular emphasis on creating more energy-efficient device technologies to handle the exponential growth of data-centric applications. Her recent publications demonstrate strong trends in developing novel oxide-based memory devices with improved energy efficiency, particularly for AI applications. The work shows significant progress in hafnium-zirconium oxide ferroelectrics, resistive switching mechanisms, and vertically aligned nanocomposite structures for enhanced device performance. These innovations address critical challenges in reducing the unsustainable energy demands of modern computing, particularly for artificial intelligence systems. Fellow of the Royal Academy of Engineering Fellow of the Materials Research Society Fellow of the American Physical Society Fellow of IOM3, IOP, and Women Engineers Society Fellow of the American Academy of Arts and Sciences Recipient of ERC Advanced Grant Editor-in-Chief of APL Materials Dr. Driscoll leads a vibrant research group that has secured significant funding including her Royal Academy of Engineering Research Chair, an ERC Advanced Grant, and an ECCS-EPSRC grant in collaboration with researchers from the USA. She has founded the Cambridge Centre for Neuromorphic Computing (Neucam) in 2023. Her group operates world-leading growth equipment including pulsed laser deposition with RHEED control, high temperature oxide sputtering, and spatial ALD systems. She collaborates extensively across the University of Cambridge and with international partners to solve complex materials challenges, with her group's role often being to identify optimal materials for functional goals, predict fabrication methods, and then create and characterize these materials.
Jennifer A. Smith, PhD, MPH is an Associate Professor of Epidemiology and Research Associate Professor of Survey Research at the University of Michigan School of Public Health . She also serves as Director of the Certificate in Public Health Genetics and is Assistant Director of the Cohort Development working group for U-M Precision Health and the Michigan Genomics Initiative. Education: PhD, Epidemiology, University of Michigan (2011) MA, Statistics, University of Michigan (2009) MPH, Health Management and Policy, University of Michigan (2005) BS, Biological Sciences, Cornell University (2001) Research Interests: Dr. Smith is a genetic epidemiologist whose work lies at the intersection of genomics, epigenomics, and social epidemiology . She investigates how genetic, epigenetic, and transcriptomic variation influence age-related chronic diseases such as cardiovascular disease, hypertension, dementia, and cognitive decline. A major focus is understanding how social, psychosocial, and neighborhood determinants interact with genetic risk to shape socioeconomic and racial/ethnic health disparities . Research Projects: Her work leverages large, multi-ethnic cohorts including the Health and Retirement Study (HRS), GENOA, SWAN, MESA, and LASI. She is a core faculty member of the Center for Social Epidemiology and Population Health (CSEPH) , and affiliated with MiCDA, the Center for Midlife Science, and the PNG Program . She also collaborates with leading consortia such as CHARGE and TOPMed. Selected Trends in Publications: Her recent work (2022–2025) emphasizes epigenetic mediation of social determinants on cardiovascular and cognitive health, polygenic risk scores across diverse ancestries , and multi-omics integration in aging and disease. These studies consistently highlight how social environments and genetic architecture jointly influence health outcomes across populations. Contact: Email: smjenn@umich.edu Office: 734-615-9455 Address: 2631 SPH I, 1415 Washington Heights, Ann Arbor, MI 48109
