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Virend SomersView profile

Professor

Mayo Clinic College of Medicine and ScienceUnited States

Virend Somers, M.D., Ph.D. , is a Professor of Medicine at Mayo Clinic in Rochester, Minnesota, with primary appointments in the Department of Cardiovascular Medicine, and joint appointments in Physiology & Biomedical Engineering and Nephrology & Hypertension. He directs the Cardiovascular and Sleep Facilities within Mayo Clinic's Center for Clinical and Translational Science. Education: MB ChB, University of Natal D.Phil., University of Oxford Resident, Internal Medicine, University of Iowa Fellow, Cardiovascular Diseases, University of Iowa Hospitals and Clinics Research Interests: Dr. Somers' research centers on neural and vascular mechanisms in circulatory control, particularly in sleep disorders such as obstructive and central sleep apnea, hypertension, obesity, and heart failure. His team investigates autonomic nervous system regulation, chemoreflex responses, and vascular biology in humans. His work bridges basic physiology with clinical applications to improve cardiovascular outcomes. Publication Trends: His recent publications (2021–2025) show a strong emphasis on sleep-cardiovascular interactions, including blood pressure regulation during sleep, cardiovascular mortality in the context of comorbidities like obesity and COVID-19, and neurocardiological mechanisms in arrhythmias and syncope. His work frequently appears in high-impact journals such as Sleep , Journal of the American Heart Association , and Journal of Physiology . Scientific Awards: Alice Sheets Marriott Professor (2016) CTSA Mentor of the Year (2012) Distinguished Scientist in Cardiopulmonary Physiology, American College of Chest Physicians (2017) Stanford University World's Top 2% Scientists (2021) Lifetime Achievement Award, South African Society of Sleep Medicine (2012) Doctor Honoris Causa, Masaryk University (2007) Advising and Grants: Dr. Somers has mentored numerous trainees who have won national awards. His research is supported by four NIH R01 grants, a Dana Foundation grant, and a NATO grant. His leadership in collaborative research spans institutions in the U.S., Europe, and South Africa. Labs and Teams: He leads the Cardiovascular Facility and Sleep Facility at Mayo Clinic’s Center for Clinical and Translational Science, fostering interdisciplinary research on sleep and cardiovascular disease.

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Patrick SkebaView profile

Academic

University of PittsburghUnited States

Patrick Skeba is a Teaching Assistant Professor at the University of Pittsburgh's Department of Computer Science within the School of Computing and Information. He holds a PhD in Computer Science from Lehigh University (2022) and bachelor's degrees in Cognitive Science and Computer Science from Johns Hopkins University (2017). His research focuses on internet privacy, AI ethics, and the responsible use of data. He teaches courses in machine learning and programming. Research Interests: Skeba's work bridges technology and societal impact, emphasizing privacy risks in data systems, algorithmic fairness, and user-centric privacy frameworks. His recent studies explore informational friction in data collection, community-based privacy strategies, and lay-expert disparities in understanding privacy-enhancing technologies (PETs). Publications: His articles analyze privacy dynamics in digital spaces, from pandemic-era discourse on r/privacy to methodological approaches for categorizing technology non-use. His earlier work includes breakthroughs in sleep disorder diagnostics, particularly periodic leg movement (PLM) analysis and telemedicine applications for neurological conditions. Awards: No scientific awards listed. Grants and advising details are currently unspecified. Labs/Teams: No specific lab affiliations mentioned in provided materials. His teaching and research emphasize collaboration across computational and social domains.

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Andrew BestView profile

Assistant Professor

University of Massachusetts AmherstUnited States

Dr. Andrew Best is an Assistant Professor of Biology at Massachusetts College of Liberal Arts (MCLA), specializing in biological anthropology with a focus on human physiological evolution. His primary research examines the role of sweating in human evolution, contemporary human sweat characteristics, and the metabolic limits of endurance performance. He holds a Ph.D. from the University of Massachusetts (2021), an M.A. from the University of Massachusetts (2016), an M.A. from Quinnipiac University (2006), and a B.A. from Saint Michael’s College (2004). Dr. Best teaches courses including BIOL 101: Biology Seminar for Majors , BIOL 342/343: Anatomy and Physiology , BIOL 440: Exercise Physiology , and BIOL 484: Biomechanics . His research integrates evolutionary biology, thermal physiology, and exercise science to explore how human metabolic and thermoregulatory systems have evolved to support extreme endurance activities. Key projects include studying sweat gland density variation across populations and the physiological constraints of ultra-endurance events. His publications span topics such as ultramarathon energy expenditure, strength training’s impact on endurance, and primate sweat gland evolution. He actively participates in academic conferences and collaborates with researchers globally. No scientific awards are explicitly noted in the provided materials. Dr. Best’s work reflects interdisciplinary approaches to understanding human biological adaptation, with ongoing projects likely extending into nutritional strategies for endurance athletes and comparative analyses of primate thermoregulation systems.

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Omer T InanView profile

Assistant Professor

Georgia Institute of TechnologyUnited States

Omer T Inan is the Regents Entrepreneur Endowed Chair and Assistant Professor at the School of Electrical and Computer Engineering (ECE) at Georgia Institute of Technology. His work bridges biomedical engineering and wearable technology, focusing on non-invasive physiological monitoring for chronic disease management. He holds a Ph.D. in Electrical Engineering from Stanford University (2009) and previously worked at Countryman Associates (2007-2013) as Chief Engineer, developing professional audio systems. Education: B.S., M.S., Ph.D. in Electrical Engineering, Stanford University (2004-2009) His research interests include medical devices for home-based cardiovascular monitoring, musculoskeletal sound analysis, and neuromodulation of stress responses. He has pioneered technologies for heart failure patients, PTSD treatment, and osteoarthritis diagnostics. Recent publications highlight innovations in AI-driven cardiac parameter estimation, motion artifact removal in seismocardiograms, and multimodal stress tracking via wearables. His work spans biomedical signal processing, clinical translation, and portable diagnostic systems. Scientific Awards 2024 IEEE Fellow 2023 IEEE Distinguished Lecturer 2023 American College of Cardiology Fellow 2022 American Institute for Medical and Biological Engineering Fellow 2021 Academy Award for Technical Achievement (The Oscars) 2018 ONR Young Investigator Award 2018 NSF CAREER Award At Georgia Tech, Inan leads the Inan Research Lab, which develops technologies for physiological monitoring and modulation. Projects include musculoskeletal sound analysis for joint health, non-invasive cardiovascular sensing, and neuromodulation to treat PTSD via vagal nerve stimulation.

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Rong-Hao LiangView profile

Assistant Professor

Eindhoven University of TechnologyNetherlands

Dr. Rong-Hao Liang is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with both the Future Everyday Group (Department of Industrial Design) and the Signal Processing Systems Group (Department of Electrical Engineering). His research bridges intelligent sensing systems and user interface technology for ubiquitous computing and embodied human-computer interaction . He co-organized international ACM conferences (CHI, UIST, DIS) and has over 70 peer-reviewed publications and 10 patents. PhD in Computer Science (2014) and MSc in Electrical Engineering (2010) from National Taiwan University Founded GaussToys Inc. in 2015, focusing on magnetic-field sensors Cross-appointed to Electrical Engineering in 2021 His research explores intelligent sensing systems , tangible user interfaces , and physiological sensors for real-world challenges. Key trends in his work include ubiquitous health monitoring (e.g., preterm infants), wearable technology , and innovative interaction design . Articles like GaussBits and NFCStack demonstrate his focus on magnetic and RFID-based tangible systems . Scientific awards include the ACM CHI 2013 Best Paper Award , 2014 Honorable Mentions , and the ACM SIGGRAPH Asia 2012 Emerging Technologies Prize . He mentors passion-driven projects in user interface design and embedded systems , emphasizing technical rigor and creativity. His STRAP project (2020–2025) addresses heart disease prevention via big data and AI . Labs and teams include the Future Everyday Group and Signal Processing Systems Group , with collaborations across healthcare , education , and technology startups . His work aligns with UN Sustainable Development Goals , particularly good health and well-being .

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Maria Camila Ceballos BetancourtView profile

Assistant Professor

University of CalgaryCanada

Maria Camila Ceballos Betancourt is an Assistant Professor (Teaching & Research) in Beef Cattle Welfare at the Faculty of Veterinary Medicine , University of Calgary . She holds a Ph.D. and M.Sc. in Animal Welfare and Behaviour from São Paulo State University (UNESP) , Brazil, and a B.Sc. in Animal Science from National University of Colombia . Her research focuses on animal welfare , human-animal interactions , and cattle temperament , with an emphasis on livestock handling practices and sustainable production systems . Education: B.Sc. in Animal Science, National University of Colombia (2010) M.Sc. in Animal Welfare and Behaviour, UNESP (2014) Ph.D. in Animal Welfare and Behaviour, UNESP (2017) She teaches VETM322: Animal Welfare and Behaviour annually since 2020. Her research integrates animal behavior , physiological and reproductive performance measures , and applied handling interventions . Recent publications address grimace scales for pain assessment , human-animal dynamics in livestock systems , and technological innovations for piglet monitoring , reflecting her interdisciplinary approach between agricultural science , veterinary medicine , and behavioral neuroscience . Her work spans continents, including internships at the Animal Welfare Science Centre (University of Melbourne, Australia) and postdoctoral research at the University of Pennsylvania (USA). While no formal awards are listed, her research has been highlighted in media outlets like Canadian Cattlemen’s The Beef Magazine and CBC Calgary .

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Tiffany HoView profile

Assistant Professor

University of California, Los AngelesUnited States

Dr. Tiffany Ho is an Assistant Professor in the Department of Psychology at the University of California, Los Angeles (UCLA). She is also affiliated with the Cognition, Affect, and Neurodevelopment in Youth (CANDY) lab, where she leads research on adolescent neurodevelopment, depression, and the neurobiological impacts of early adversity. Her work integrates neuroimaging, psychophysiology, and immunology to understand how stress and adversity shape brain circuits underlying emotion and behavior during adolescence. Education: Ph.D. in Psychology, University of California, San Diego B.A. in Cognitive Science, University of California, Berkeley Postdoctoral Fellowship in Clinical Neuroscience, University of California, San Francisco Postdoctoral Training in Affective Science, Stanford University Research Interests: Dr. Ho’s research focuses on understanding how brain circuits underlying thoughts, emotions, and behaviors change during adolescent development. She investigates how experiences of adversity and perceptions of stress shape neurodevelopment, and how these changes impact the etiology, course, and treatment of depression. Her lab uses a multimodal approach, including behavioral, cognitive, endocrine, immune, and neuroimaging techniques, and leverages big data and global initiatives to identify robust brain imaging markers associated with depression and related conditions. Grants and Funding: Her research has been generously funded by the Klingenstein Third Generation Foundation and the National Institute of Mental Health . Publications and Impact: Dr. Ho has published extensively in high-impact journals, with over 100 peer-reviewed articles. Her recent work includes studies on the effects of COVID-19 on adolescent mental health, the role of inflammation in depression, and the use of machine learning to classify major depressive disorder using neuroimaging data. She is also a key contributor to the ENIGMA consortium, a global initiative aimed at understanding brain alterations in psychiatric disorders.

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Nicole NovielliView profile

Associate Professor

University of BariItaly

Nicole Novielli, Ph.D., is Associate Professor at the University of Bari “A. Moro” , Italy, where she conducts research on affective computing applied to software engineering and human-computer interaction. She leads the Collaborative Development Group and coordinates national projects investigating emotions in software teams, AI quality and IoT ecosystems. Education: Ph.D. in Computer Science, University of Bari, 2010 – thesis on “Lexical Semantics of Dialogue Acts” M.Sc. in Computer Science (Knowledge & Software Engineering), University of Bari, 2006 – summa cum laude B.Sc. in Computer Science, University of Bari, 2004 – summa cum laude Visiting researcher at USC-ICT, University of Aberdeen, FBK-irst (Trento) Research interests revolve around recognizing and exploiting affective and cognitive states in computer-mediated cooperative work. She studies sentiment and emotion mining in developers’ textual communication, multimodal emotion recognition via low-cost biometric sensors, and natural-language dialogue simulation for intelligent interfaces. Her work couples software engineering with natural language processing , social media analytics and human-computer interaction . Recent articles (2021-2025) reveal a clear trend: integrating deep learning and large language models into software engineering tasks—automated issue labelling, sentiment classification, technical-debt detection—while validating these techniques through rigorous empirical studies and biometric experiments . A parallel stream explores developer experience , measuring how emotions and cognitive load influence productivity, code quality and collaboration. Scientific awards include the 2020 Apex Award for Publication Excellence , multiple Distinguished Reviewer Awards at flagship venues (ESEC/FSE, ICSME, MSR), the Best Paper Award SANER 2019 and the Best Student Paper Award ACII 2009 . She currently teaches “Sentiment Analysis” in the Data-Science MSc and “Computer Networks” in the ITPS programme. She has advised numerous B.Sc., M.Sc. and PhD projects and is PI or Co-PI of four ongoing grants: EmoQuest (SIR), EMPATHY (PRIN), FAIR-Spoke 6 (PnRR), and QualAI (PRIN 2022). Dr. Novielli serves on the editorial boards of Empirical Software Engineering and Journal of Systems and Software , has guest-edited special issues on affect awareness in SE, and has chaired tracks at ICSE, SANER, MSR, ICSME and SSBSE. She co-leads the Collaborative Development Group and actively releases datasets and open-source tools for the community.

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Bettina Sandgathe HusebøView profile

Professor

University of BergenNorway

Bettina Sandgathe Husebø is a Professor and Head of the Center for Geriatric and Nursing Home Medicine at the Department of Global Health and Community Medicine, Faculty of Medicine, University of Bergen (UiB). She also serves as Innovation Manager at IGS, UiB since 2019. Her extensive career spans clinical practice, research, and leadership roles in geriatric and palliative care. Dr. Husebø completed her medical education at the University of Bonn, Germany in 1988, followed by specialization in Anaesthesiology and Intensive Care in 1995. Her Norwegian qualifications include Medical Specialization in Palliative Medicine (2012) and Nursing Home Medicine (2014) from UiB, along with a PhD from the Faculty of Medicine Dentistry at UiB in 2008. She further enhanced her expertise with a Postgraduate Safety, Quality, Informatics and Leadership (SQIL) Program from Harvard University in 2021. Her research focuses on critical geriatric issues including pain assessment and management in dementia patients, behavioral disturbances in dementia, palliative care in nursing homes, and digital phenotyping applications for elderly care. She has pioneered work on the relationship between pain, agitation, and neuropsychiatric symptoms in dementia patients, particularly through the COSMOS trial and LIVE@Home.Path study. Her recent publications (2023-2025) demonstrate a strong emphasis on digital health solutions for dementia care, with particular focus on activity monitoring, pain assessment through technology, and community-based interventions for aging populations. Her work bridges clinical geriatrics, technology innovation, and patient-centered care models. Among her notable recognitions are the National Dementia Award by His Majesty King Harald of Norway (2022) and multiple awards for research excellence in pain management and palliative care. Her work has significantly influenced Norwegian healthcare policy regarding dementia care and end-of-life practices. As an educator, she lectures in English, German, and Norwegian on dementia, pain in dementia, innovation technologies for older adults, symptom management at end-of-life, systematic medication review, and advance care planning. She has received teaching awards including 'Teacher of the Year' from the Faculty of Medicine and Dentistry at UiB. Dr. Husebø leads the Center for Geriatric and Nursing Home Medicine (SEFAS) and has been instrumental in establishing Norway's first palliative care ward in a nursing home. Her research group focuses on translating evidence into practice to improve quality of life for elderly patients, particularly those with dementia.

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Courtney N. ReedView profile

Lecturer

University of LondonUnited Kingdom

Courtney N. Reed is a Lecturer in Digital Technologies at Loughborough University London, where she joined in November 2023. She maintains a dual role as a visiting research fellow at the Max Planck Institute for Informatics. Her academic journey includes a BMus in Electronic Production and Design from Berklee College of Music (2016), followed by an MSc (2018) and PhD (2023) in Computer Science from Queen Mary University of London. Prior to her current position, she completed postdoctoral research at both the Max Planck Institute for Informatics and King's College London. Bachelor of Music: Electronic Production and Design, Berklee College of Music (2016) Master of Science: Computer Science, Queen Mary University of London (2018) Doctor of Philosophy: Computer Science, Queen Mary University of London (2023) Dr. Reed's research explores the entangled relationships between humans, bodies, instruments, and technology in music interaction, with particular focus on vocal electromyography (VoxEMG) and the vocalist-voice relationship. Her work incorporates feminist and post-human theories to examine sociopolitical contexts within arts technology, aiming to design for creativity while acknowledging individual, messy bodies in artistic practice. She has developed an open-source platform for vocal electromyography to investigate how biosignal feedback changes understanding and perception of the body in vocal performance. Her interdisciplinary approach bridges music technology, human-computer interaction, and embodied interaction studies. Analysis of Dr. Reed's recent publications (2023-2025) reveals a strong thematic focus on embodied interaction in music technology, with particular emphasis on vocal performance, biosignal feedback, and the philosophical underpinnings of digital instrument design. Her work consistently integrates theoretical frameworks like Karen Barad's agential realism with practical applications in digital musical instruments. Key trends include the exploration of ambiguity in data representation, the sociocultural dimensions of timbre in instrument design, and the development of novel methodologies for understanding embodied musical experiences through micro-phenomenology and ethnographic approaches. ACM SIGCHI Outstanding Dissertation Award (2024) for her thesis 'Imagining & Sensing: Understanding and Extending the Vocalist-Voice Relationship Through Biosignal Feedback' Best Newcomer Award at Loughborough University London's Community Awards Celebration (2024) Dr. Reed actively contributes to the academic community through conference organization and leadership roles. She serves as Member-at-Large on the NIME Board, previously chaired papers for NIME 2024, and co-organized the IBM SkillsBuild Sprint at Loughborough London. She has also chaired sessions at the ACM TEI Conference and co-chaired the Student Design Competition. Her collaborative work spans multiple institutions and includes significant contributions to interdisciplinary projects that bridge music, technology, and human experience. She has been instrumental in developing the senSInt research group and the RaveNET wearable network project. Dr. Reed leads the senSInt research group which focuses on sensorimotor interaction in music and performance contexts. The group develops innovative technologies including the VoxEMG platform for vocal electromyography, the Bones anti-corset for vocal performance, and the RaveNET network of wearable biosensing nodes. These projects explore the intersection of biosignals, embodied interaction, and musical expression, creating novel frameworks for understanding how technology mediates human creativity and performance. The group frequently collaborates with musicians, technologists, and theorists to develop and test these systems in real-world performance contexts.

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Matthew PriceView profile

Professor

University of VermontUnited States

Matthew Price is the George W. Albee Green & Gold Professor of Psychological Science and Director of the Clinical Psychology Training Program at the University of Vermont's College of Arts and Sciences. He holds a B.A. from SUNY Binghamton (2004), an M.A. (2006), and Ph.D. (2011) from Georgia State University. His research focuses on expanding clinical care access for trauma survivors and anxiety disorder patients via technology-driven interventions. Key areas include mobile health applications, wearable sensors, and acute trauma care in Emergency Departments. His interdisciplinary approach involves collaborations with computer science, bioinformatics, and medicine. Current projects explore digital biomarkers (e.g., heart rate variability), technology adoption barriers, and culturally adapted therapies. He leads the Center for Research on Emotion, Stress, and Technology, emphasizing translational frameworks bridging basic research and clinical practice. Recent work includes randomized controlled trials evaluating mobile apps like 'Bounce Back Now' for disaster-related PTSD, and sleep-monitoring studies using wearable devices. Over 150 peer-reviewed articles highlight his focus on trauma mechanisms, symptom networks in veterans, and tech-enabled mental health innovations. His lab actively addresses global mental health disparities through mHealth solutions.

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Michael StevensView profile

Senior Lecturer

University of New South WalesAustralia

Dr. Michael Stevens is a Senior Lecturer at University of New South Wales (UNSW) Canberra , where he focuses on advanced manufacturing and biomedical device control systems . His work bridges digital manufacturing for SMEs with smart artificial heart technologies , emphasizing industry collaboration and translational research. Specializes in physiological control systems for rotary blood pumps Develops unobtrusive fall detection systems for dementia patients Leads international projects on total artificial heart development Education : B.Eng (Medical - First Class Honours), Queensland University of Technology (2010) PhD in Physiological Control for Biventricular Assist Devices, University of Queensland (2014) Research Trends show consistent focus on: Machine learning for biomedical diagnostics (2018–2025) mmWave radar and thermal sensors in patient monitoring (2021–2024) Computational fluid dynamics in artificial heart modeling (2016–2024) Physiological control algorithms for rotary blood pumps (2011–2025) Scientific Awards : UNSW Scientia Education Award (2021) for contextual teaching Heart Foundation Runner-up for "Smart Artificial Hearts" pitch (2021) ARC PGC Supervisor Award (2017) for mentoring Grants & Supervision : Holds over $6 million in competitive funding including MRFF and ARC grants. Currently supervises 4 PhD students while maintaining industry partnerships with VitalCare and BiVACOR. Labs & Facilities : Works across UNSW Engineering labs and Graduate School of Biomedical Engineering platforms, including mock circulation loops and high-performance computing clusters for CFD simulations.

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Daniel PowellView profile

Senior Lecturer

University of AberdeenUnited Kingdom

Daniel Powell is a Senior Lecturer in Health Psychology and Programme Director of the MSc Health Psychology at the University of Aberdeen, School of Medicine, Medical Sciences and Nutrition. He is a core member of the Aberdeen Health Psychology Group and the interdisciplinary Centre for Labour Market Research. He holds a PhD from the University of Southampton and became a Fellow of the Higher Education Academy in 2019. His educational background includes: BSc (Hons) Psychology – University of the West of England, 2007 MSc Health Psychology – University of Southampton, 2009 PhD Psychology – University of Southampton, 2014 Daniel's research focuses on health psychology, particularly using intensive longitudinal methods such as ecological momentary assessment (EMA) to study stress, fatigue, self-regulation, and decision-making in real-world contexts. His work spans chronic illness (e.g., multiple sclerosis, diabetes), healthcare professionals (e.g., doctors, nurses), and occupational settings (e.g., fly-in fly-out workers). He leads the Stress and Health Research Theme and convenes regular workshops to support health psychology researchers. His methodological expertise includes real-time data collection, psychophysiology (e.g., heart rate variability, cortisol), and interdisciplinary collaboration with health economics, primary care, and bioengineering. His recent publications (2024–2025) reveal a strong trend in investigating decision fatigue in healthcare, stress and recovery patterns in medical professionals using biometric monitoring, and the psychosocial impact of shift and rotation work. He frequently employs EMA and systematic reviews to explore behavioral patterns in context. His work also extends to sustainable clinical research and digital health tools for pandemic response. His scientific recognition includes: Stan Maes Early Career Award, European Health Psychology Society (2019) Rosemary Anne Price Student Award, MS Society (2013) Daniel actively supervises five PhD students on topics including decision fatigue in healthcare, quality of life after limb loss, stress in medical and dental students, and low-carbon clinical trials. He teaches across postgraduate programs, coordinates the PU5053 course on Stress, Personality & Health, and co-founded an annual Summer School in Intensive Longitudinal Methods. He has no indication of part-time status and is actively engaged in research, teaching, and leadership. He is affiliated with several professional organizations, including the British Psychological Society (Chartered Psychologist), Division of Health Psychology, European Health Psychology Society, and UK Society for Behavioural Medicine. His research lab is embedded within the Aberdeen Health Psychology Group, which fosters interdisciplinary collaboration and methodological innovation in health behavior research.

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Steven LivingstoneView profile

Associate Professor

Ontario Tech UniversityCanada

Steven Livingstone is an Associate Professor in the Department of Computer Science at Ontario Tech University, Faculty of Science. His research focuses on affective data science, applying machine learning and statistical modeling to understand emotion and its disorders. He leads the Affective Data Science Lab (ADSL), specializing in emotion recognition technologies using physiological data like EEG and motion capture. Livingstone holds a PhD from The University of Queensland (2008) and has published over 70 peer-reviewed papers, with over 2,400 citations. His RAVDESS dataset is widely used in speech emotion recognition research. His research interests span data science, affective computing, and music's role in emotion. Recent work emphasizes data provisioning for deep learning applications. Livingstone teaches courses including Scientific Data Analysis and Information Visualization. He actively mentors undergraduate and graduate students in his lab, focusing on research assistantships in emotion technology development. Key contributions include studies on musical tempo’s physiological effects, Parkinson’s disease facial mimicry deficits, and ensemble performance dynamics. His work has been featured in The Atlantic, NBC Today, and on the cover of Informatik Spektrum. The ADSL lab collaborates on projects combining data analytics with human-computer interaction to advance emotion-aware systems.

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James LacefieldView profile

Professor

Western UniversityCanada

James Lacefield is a Professor in both the Department of Electrical and Computer Engineering and the Department of Medical Biophysics at Western University. He serves as Director of the School of Biomedical Engineering and maintains his research laboratory in the Amit Chakma Engineering Building. His academic appointments span multiple disciplines, reflecting the interdisciplinary nature of his work in biomedical ultrasound imaging. Dr. Lacefield earned his Ph.D. and B.S.E. in Biomedical Engineering from Duke University. His educational background established the foundation for his current research program that bridges engineering principles with medical applications. His research focuses on the physical acoustics and signal processing aspects of ultrasound imaging, with particular emphasis on quantitative vascular imaging applications. Dr. Lacefield's laboratory develops novel methods for color Doppler, power Doppler, and contrast-enhanced ultrasound imaging, with primary applications in cancer research. Current projects include optimization of high-resolution ultrasound systems for tumor vascular characterization and development of methods to quantify spatial blood flow distribution in tumors. Analysis of his recent publications reveals a strong focus on quantitative ultrasound techniques for cancer applications, with particular attention to tumor perfusion assessment using contrast-enhanced ultrasound. His work demonstrates increasing sophistication in speckle analysis methods to improve the reliability of perfusion measurements in preclinical tumor models. Associate Editor, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control Member, Council of Chairs of Bioengineering and Biomedical Engineering Member, College of Reviewers, Canadian Institutes of Health Research Dr. Lacefield maintains active collaborations with multiple research groups including the Imaging Research Laboratories at Robarts Research Institute. His professional activities include editorial work for major ultrasound journals and participation in national review panels for biomedical research funding.

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