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Clemens MaidhofView profile

Research Fellow

• Music Therapy
• Neuroscience
• Cognitive Neuroscience
• +4 more

Clemens Maidhof is a Senior Research Fellow at the Cambridge Institute for Music Therapy Research within the Faculty of Arts, Humanities, Education and Social Sciences at Anglia Ruskin University. He joined the institution in 2016 after conducting research at the University of Cologne, Max Planck Institute for Human Cognitive and Brain Sciences, and the Finnish Centre for Interdisciplinary Music Research. He holds an MA in Musicology from the University of Cologne and a PhD in Psychology from Freie Universität Berlin. Research Focus: His work bridges cognitive neuroscience and music therapy, with core interests in: Neural dynamics of clinical improvisation during therapy sessions Brain-computer music interfaces for therapeutic applications EEG hyperscanning techniques in dyadic therapist-patient interactions Syntactic processing parallels between music and language Error monitoring mechanisms in musicians' performance Multimodal data acquisition (EEG, motion capture, MIDI) His research consistently applies neuroscientific methods to clinical contexts including dementia care, stroke rehabilitation, and substance misuse treatment. Publication Trends: Maidhof's recent work (2019-2023) focuses on EEG hyperscanning applications in music therapy, particularly examining brain synchrony during therapeutic improvisation for neurological conditions. Earlier publications (2010-2014) established foundational research on error processing in musicians and cross-domain syntactic attention. His methodology evolved from single-modality ERP studies to complex multimodal hyperscanning designs. Professional Engagement: He regularly reviews for journals including NeuroImage , Journal of Cognitive Neuroscience , and Frontiers in Psychology , and has presented at major conferences like the European Music Therapy Conference. He contributed to the BBC documentary Our Dementia Choir featuring clinical applications of his research.

Matias ZurbriggenView profile

Research Professor

• Synthetic Biology
• Optogenetics
• Plant Biology
• +5 more

Matias Zurbriggen is a Research Professor at the Institute of Synthetic Biology, Heinrich Heine University Düsseldorf, where he leads a pioneering research group at the interface of engineering and life sciences. His work focuses on developing theoretical-experimental synthetic biology approaches to understand and control eukaryotic signaling processes with quantitative and spatiotemporal precision. Dr. Zurbriggen's research interests center on synthetic biology principles applied to biological signaling systems, with particular emphasis on optogenetics. He pioneered cellular optogenetics - engineering synthetic photoswitches to control molecular processes with high precision, minimal toxicity, and non-invasive methods. His group has successfully overcome the fundamental challenge of implementing optogenetics in plants, which normally require light for growth, opening new possibilities for plant engineering. His research spans microbial, yeast, mammalian, and plant systems, with applications in tissue engineering, biomedical research, and crop improvement. His recent publications demonstrate significant advances in optogenetic tools, including genetically-stable optogenetic switches for 3D tissue cultures, image-guided optogenetic patterning, and specialized biosensors for plant hormones. These innovations enable precise spatiotemporal control of cellular processes using light of different colors, with applications spanning from fundamental biological research to practical agricultural improvements. Selected by Nature Methods as one of the top methods of 2023 Dr. Zurbriggen's research program integrates synthetic biology with advanced imaging and computational approaches to reconstruct semisynthetic signaling and metabolic networks. His group performs de novo engineering of genetic circuits, biosensors, and synthetic metabolic pathways, including intracellular and cell-cell communication systems. The work has significant implications for understanding developmental processes, metabolic regulation, and creating novel biotechnological applications in medicine and agriculture.

Wei ChenView profile

Professor

• Statistical Genetics
• Computational Biology
• Genomics
• +4 more

Wei Chen serves as Professor of Pediatrics (primary appointment) with secondary appointments in Biostatistics and Human Genetics at the University of Pittsburgh, where he leads the Chen Lab focused on statistical genomics and computational biology. His research develops innovative methods for analyzing high-throughput genomic data to study complex diseases including childhood asthma, age-related macular degeneration, and COPD. Dr. Chen earned his PhD in Biostatistics from the University of Michigan, MS in Mathematics from Michigan State University, and BS in Mathematics from Nanjing University. His expertise bridges mathematical theory with biomedical applications through rigorous statistical modeling. His research program centers on creating computational frameworks for single-cell and spatial multi-omics data integration, with particular emphasis on developing novel algorithms for doublet detection, spatial transcriptomics super-resolution, and longitudinal disease progression modeling. Current projects leverage bulk and single-cell multi-omics (DNA-seq, RNA-seq, methylation, ATAC-seq, Spatial Transcriptomics) to uncover disease mechanisms in pediatric asthma and macular degeneration. Recent publications demonstrate consistent leadership in statistical genomics, with 2024-2025 work advancing spatial transcriptomics transformer models and pediatric asthma endotype characterization published in Nature Communications and JAMA. His research shows increasing focus on multi-modal data integration and clinical translation of genomic findings. Pediatric Discovery Award from Department of Pediatrics (2025) Secretary of Chinese-American Lung Association (2024) Chapter Representative, Pittsburgh Chapter American Association Society (2024) Dr. Chen actively mentors 6 current PhD students and has guided over 20 trainees to successful careers in academia and industry. His lab secures substantial external funding including NIH R01 grants from NEI, NHGRI, NHLBI, NIAMS, and NIDDK, plus support from NSF, Scleroderma Research Foundation, Helmsley Charitable Trust, and UPMC. Recent grants include an NIAMS R01 for scleroderma subgroup identification and DoD funding for pediatric scleroderma multi-omics studies. The Chen Lab operates within the Rangos Research Building at Children's Hospital of Pittsburgh, maintaining a collaborative environment with biostatisticians, geneticists, and clinicians. Current projects integrate spatial transcriptomics with histology imaging and develop AI-driven models for disease progression prediction, supported by active partnerships with NIH institutes and disease-specific foundations.

Zeyu SunView profile

Researcher

• Software Engineering
• Program Repair
• Machine Learning for Code
• +4 more

Zeyu Sun is a researcher at the Institute of Software, Chinese Academy of Sciences, with an extensive publication record in premier software engineering conferences including ASE, ICSE, and ESEC/FSE from 2020 through 2025. Their academic service includes program committee membership for multiple conferences, demonstrating recognition as a domain expert in software engineering and programming languages. Dr. Sun's research program bridges traditional software engineering with artificial intelligence, focusing on neural program repair, software testing, and compiler optimization. Their work develops innovative techniques for code understanding and generation, with particular emphasis on type-aware repair systems, syntax-guided editing approaches, and context-enriched representations of code changes. Recent publications show increasing sophistication in integrating machine learning with software engineering tasks, moving from basic program analysis to specialized architectures that maintain structural integrity of code. Analysis of publication trends reveals a consistent focus on improving software quality through AI-enhanced methods, with expanding applications across compiler design, smart contract security, and fairness testing. The research demonstrates both technical depth in core software engineering challenges and breadth across multiple application domains, reflecting an evolving research trajectory that continually identifies new intersections between AI and software development practices. Dr. Sun actively contributes to the academic community through program committee service at major conferences including ASE, ICSE, and ESEC/FSE across multiple years. This sustained service commitment indicates peer recognition as a subject matter expert. While specific grant details aren't provided in available materials, the consistent publication output across multiple funding cycles suggests successful acquisition of research support for their work in software engineering and AI for code.

Carlos A. ArtimeView profile

Professor

• Anesthesiology
• Airway Management
• Neuromuscular Blockade
• +5 more

Carlos A. Artime, MD is a Professor and Clinical Executive Vice Chair at McGovern Medical School, part of the University of Texas Health Science Center at Houston (UTHealth Houston). He also serves as Vice Chair of Finance and Operations and Associate OR Director at Memorial Hermann - TMC. Dr. Artime is a prominent figure in anesthesiology with expertise in airway management and patient safety protocols. Vanderbilt University: BSE in Biomedical Engineering with minor in Molecular Biology (1997-2001) Baylor College of Medicine: Doctor of Medicine (2001-2005) McGovern Medical School at UT Health: Transitional Year Internship (2005-2006) University of Pennsylvania: Anesthesiology Residency Program (2006-2009) Dr. Artime's research focuses on airway management, particularly for difficult airway scenarios, neuromuscular blockade monitoring, and sedation techniques. His current projects include the SEGA trial comparing sedation versus general anesthesia for endovascular therapy in acute ischemic stroke, and a study comparing Sugammadex versus placebo to prevent residual neuromuscular block. His work bridges clinical practice with evidence-based approaches to improve patient outcomes in anesthesia. Dr. Artime's publication record reveals a consistent emphasis on airway management techniques across multiple clinical settings. His research spans randomized clinical trials, systematic reviews, and educational contributions that address critical challenges in anesthesia practice. The thematic consistency in his work demonstrates a dedicated research trajectory focused on improving airway management protocols and patient safety. Dr. Artime has co-edited significant textbooks including "A Practical Guide to the Difficult Airway" (Oxford University Press, 2013) and "Hagberg and Benumof's Airway Management" (Elsevier, 2017). He has contributed numerous book chapters to authoritative texts such as Miller's Anesthesia and Benumof's Airway Management, establishing himself as a thought leader in the field. As Clinical Executive Vice Chair, Dr. Artime oversees departmental operations while maintaining an active research program. His leadership extends to medical education, as evidenced by his work on faculty evaluation scoring systems for anesthesiology resident applicants. Dr. Artime collaborates extensively with colleagues across multiple institutions, reflecting a team-based approach to advancing anesthesiology practice and education.

• Orthodontics
• Orthodontic root resorption
• Biological basis of orthodontic tooth movement
• +9 more

Dr Alexandra Papadopoulou is an Honorary Senior Lecturer in the Discipline of Orthodontics and Paediatric Dentistry at the University of Sydney’s School of Dentistry , Faculty of Medicine and Health. She teaches and supervises graduate and postgraduate students, co-ordinates continuing professional development courses for dental professionals, and conducts impactful clinical and translational research in orthodontics and craniofacial biology. Education & Training Dental Degree – Aristotle University of Thessaloniki, Greece 3-year full-time Postgraduate Course in Oral Surgery, Implantology & Dental Radiology – Aristotle University of Thessaloniki 40-month full-time Postgraduate Specialty Program in Orthodontics (ERASMUS-accredited) – Aristotle University of Thessaloniki PhD – "Effects of orthodontic forces in guided tissue regeneration" – Aristotle University of Thessaloniki Research Focus Dr Papadopoulou’s research spans the biological and clinical spectrum of orthodontics. Her work interrogates orthodontic root resorption , periodontal ligament regeneration , temporary anchorage devices (TADs) , clear aligner biomechanics , maxillary expansion , accelerated tooth movement , laser-assisted orthodontics , and craniofacial growth modification . She employs systematic reviews, randomized controlled trials, micro-CT imaging, CBCT, smartphone-based 3D facial scanning, and molecular analyses to translate laboratory insights into improved patient care. Scientific Awards & Recognition European Orthodontic Society (EOS) Houston Award – 2006 (invited oral presentation) Grants & Collaborative Projects 2017 – "Changing faces, changing lives: A preliminary investigation of the social outcomes of orthognathic surgery" – ANZAOMS Research Grant (Co-Investigator) Professional Associations Dr Papadopoulou is an active member of the Australian Society of Orthodontists , World Federation of Orthodontics , European Orthodontic Society , American Association of Orthodontists , and several national orthodontic societies in Greece and Italy, underscoring her global engagement in research, education, and clinical standards.

• Alzheimer Disease
• Dementia
• Biomarkers
• +7 more

Maria Bjerke is a Researcher in Clinical Biology at the Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB), with affiliation to Universitair Ziekenhuis Brussel (UZ Brussel). Her work focuses on neuroprotection and neuromodulation, with extensive contributions to Alzheimer's disease research and biomarker development. With an h-index of 37 and over 7,202 citations, she has established significant impact in her field through 96 research outputs spanning from 2007 to 2024. Dr. Bjerke's research interests center on cerebrospinal fluid biomarkers, amyloid pathology, and cognitive dysfunction in neurodegenerative diseases. Her fingerprint analysis reveals strong activity in Alzheimer Disease (90%), Biomarkers (64%), dementia (48%), Dementia (36%), Cognitive Dysfunction (34%), Amyloid (33%), and Intermediate Filaments (20%). She bridges laboratory research with clinical applications to improve diagnosis and monitoring of dementia patients. Her recent publications demonstrate a sophisticated approach to understanding brain aging, Alzheimer's progression, and potential therapeutic interventions. She employs advanced methodologies including neuroimaging, cerebrospinal fluid analysis, and cutting-edge analytical chemistry techniques. Dr. Bjerke actively contributes to major international conferences on Alzheimer's disease and frontotemporal dementias, maintaining visibility in the global neuroscience community. She currently participates in the IOF GEAR project (2022-2026), which applies artificial intelligence to neurology, neurosurgery, and psychiatry. This €4 million initiative focuses on Applied Cognition (100%), Machine Learning (95%), Brain Diseases (80%), Psychiatry (62%), and Deep Learning (57%). Dr. Bjerke also serves as research supervisor, having guided at least one Master's student in neurofilament light chain quantification research.

• Radiotherapy
• Radiobiology
• Molecular Biology
• +3 more

Mark De Ridder is a Clinical Professor at the Vrije Universiteit Brussel (VUB) and affiliated with the Research Centre for Digital Medicine at UZ Brussel. He holds roles such as Department Chair and leads projects in advanced radiotherapy techniques. His research focuses on radiotherapy optimization, radiobiology, and immunology-driven cancer treatments. Key projects include markerless SBRT development and FLASH radiotherapy evaluations. He has authored over 550 publications, with h-index 64, and received multiple awards for his contributions. His work bridges technological innovation (e.g., dynamic tumor tracking) with clinical outcomes, emphasizing personalized radiation doses using radiomics and quantitative imaging. Affiliations: VUB Faculty of Medicine and Pharmacy, Research Centre for Digital Medicine (UZB) Grants: SRP53 (Markerless SBRT), HERC69 (FLASH Radiotherapy) Research interests include hypoxia in tumors, radiosensitizers (e.g., hydrogen peroxide), and predictive biomarkers for treatment response. He has advised 7 thesis students and collaborates internationally on translational oncology projects. Media coverage highlights his contributions to MRI-guided prostate and rectal cancer therapies.

Hesam JadidbonabView profile

Assistant Professor

• Cyber Security
• Cyber-Physical Systems
• Connected and Autonomous Vehicles (CAVs)
• +11 more

Dr. Hesam Jadidbonab is an Assistant Professor (Research) at Coventry University, affiliated with the Centre for Future Transport and Cities. His research is centered on cybersecurity in cyber-physical systems, particularly in connected and autonomous vehicles (CAVs), with a focus on real-time security, intrusion detection, and secure over-the-air (OTA) updates. He leads and contributes to multiple Innovate UK-funded projects aimed at enhancing the safety and security of future transportation systems. Doctorate in Mechanical Engineering, City, University of London MEng in Automotive Engineering, Aachen University of Applied Science His research interests span Cyber Security , Automotive Systems , Machine Learning for Security , Testbed Development , and Experimental Fluid Mechanics . He has developed expertise in advanced imaging techniques such as Particle Image Velocimetry (PIV), X-ray imaging, and computed-tomography reconstruction during his doctoral and post-doctoral work. The recent publications of Dr. Jadidbonab reflect a strong trend in applying ontology modeling , language models , and fuzzing techniques to automotive and IoT security. His work integrates context-awareness , real-time threat detection , and adaptive security policies to address evolving cyber threats in intelligent transport systems. The interdisciplinary nature of his research bridges mechanical engineering, computer science, and systems engineering. Scientific Awards: No specific awards listed in the provided text. Dr. Jadidbonab has been actively involved in research advising and project leadership. He serves as a Co-Investigator and Researcher in multiple high-impact projects including: Secure-CAV : Focused on testbed development and machine learning for intrusion detection in autonomous vehicles. Trade-off Management between Safety and Cybersecurity : Investigating the balance between functional safety and cyber resilience. SCALE : Solihull & Coventry Automated Links Evolution, contributing to automated mobility integration. A Roadmap to Cybersecurity for CI-SRN Integration : Developing strategic cybersecurity frameworks for connected infrastructure. He has collaborated with academic and industrial partners such as Lubrizol Ltd., University of Bergamo, FAU Erlangen-Nürnberg, and Argonne National Laboratory. His lab work includes the design and deployment of multi-bus automotive testbeds to validate security mechanisms in realistic vehicle environments.

Michel de MathelinView profile

Professor

• Medical Robotics
• Image-Guided Surgery
• Teleoperation
• +4 more

Michel de Mathelin is a Professor at the University of Strasbourg and Director of the ICube Laboratory (UMR CNRS 7357) since 2013. He leads the robotics research team (AVR) and serves as head of robotics research at the Institut de Recherche sur les Cancers de l'Appareil Digestif (IRCAD) for 15 years. Since 2017, he has been Vice-President for Innovation and Technology Transfer at the University of Strasbourg. His roles include coordinating the national Robotex robotics platform (2011) and co-founding Axilum Robotics, specializing in medical robotics for transcranial magnetic stimulation. He previously served as Scientific Delegate of CNRS-INSIS (2012–2014). His research focuses on Medical robotics and surgical automation Image-guided interventions Teleoperation systems Adaptive control algorithms Publications highlight advancements in robotic surgical tools, AI-driven medical imaging, and interventional oncology. Key contributions include OCT-based endoluminal scanning systems, semi-autonomous robotic control modes, and MRI-guided therapies. His work bridges robotics engineering with clinical applications in oncology and minimally invasive surgery. Labs/Teams: ICube Lab (Engineering & Imaging) IRCAD (Digestive Cancer Research) Axilum Robotics (Medical Startup) Labex CAMI & IHU Strasbourg (Image-Guided Surgery)

• Surgical Robotics
• Medical Robotics
• Autonomous Surgical Systems
• +4 more

Pierre Berthet-Rayne serves as Chief Technical Officer at Caranx Medical and holds a Chair at the 3IA Institute of Artificial Intelligence, University of the Côte d'Azur. His research pioneers AI-driven autonomous surgical robots to transition from teleoperated systems to clinician-supervised autonomous platforms. Education: Master’s in Electronics and Control, Polytech’Montpellier (France), 2009 MRes in Medical Robotics and Image Guided Intervention (with distinction), Imperial College London (UK), 2015 PhD in Robotics, Hamlyn Centre for Robotic Surgery (development of i²Snake endoscopic robot) His core research spans surgical robotics, tendon-driven mechanisms, snake-like robots, and human-robot collaboration, with emphasis on AI for context-aware surgical planning and execution. Current work integrates image processing, sensor data fusion, and control systems to enable autonomous procedure execution under clinician oversight. Professional trajectory includes two years as an embedded software engineer, postdoctoral research at King’s College London’s Robotics and Vision in Medicine Lab, and visiting scholar roles at UNC Chapel Hill’s Computational Robotics Research Group and University of Arizona’s Model Based Design Lab. He actively collaborates with the Robotics and Vision in Medicine Lab (King’s College), Computational Robotics Research Group (UNC), and Model Based Design Lab (Arizona), driving innovation in surgical robotics through Caranx Medical’s technical leadership.

Samer Al-KhudariView profile

Associate Professor

• Head and Neck Oncology
• Transoral Robotic Surgery
• HPV-related Oropharyngeal Cancer
• +5 more

Samer Al-Khudari, MD, is an Associate Professor in the Department of Otorhinolaryngology – Head and Neck Surgery at Rush University Medical Center. He serves as Head of the Section of Head and Neck Surgical Oncology, Director of Transoral Robotic Surgery, and Medical Student Clerkship Director for ENT. Dr. Al-Khudari graduated from Rush Medical College with AOA honors, completed residency at Henry Ford Health System, and a fellowship at the Cleveland Clinic in head and neck oncology and microvascular reconstruction. Education: Rush University Medical College (Medical Degree) Residency: Henry Ford Health System (Otolaryngology) Fellowship: Cleveland Clinic (Head and Neck Oncology & Reconstructive Surgery) Research & Clinical Focus: Dr. Al-Khudari’s work centers on HPV-related oropharyngeal cancer, robotic surgery, microvascular reconstruction, and global health initiatives for displaced refugees. He has authored numerous publications and lectures nationally on head and neck cancer and international surgical care. His research emphasizes patient-centered care, survival rates, and quality of life post-treatment. Awards: Rush Medical Staff I-Care Award Department of Anatomy Anthony Schmidt Award Articles & Trends: Recent publications focus on reconstructive techniques for salvage laryngectomy, nationwide analyses of fibromatoses and laryngeal cancer in the elderly, and innovations like 3D-printed patient immobilization for radiation therapy. His work balances surgical advancements with global health equity. Grants & Teams: Dr. Al-Khudari collaborates with multidisciplinary teams at Rush, focusing on oncology, surgical innovation, and global health missions. He participates in national committees for the American Academy of Otolaryngology and American Head and Neck Society. Labs/Teams: Leadership in head and neck surgical oncology teams, advancing robotic and minimally invasive techniques through clinical research and translational medicine.

Ming LiuView profile

Academic

• Rehabilitation Engineering
• Human Motion Analysis
• Wearable Sensors
• +7 more

Ming Liu is a Research Associate Professor in the Department of Biomedical Engineering at NC State University. His work focuses on the design and control of powered prostheses, human motion analysis, wearable sensors, robots, nonlinear dynamics, and image processing. He holds a Ph.D. in Mechanical Engineering & Applied Mechanics from the University of Rhode Island, along with a M.Sc. and B.S. in Mechatronics from Beijing Institute of Technology. Dr. Liu’s research emphasizes interdisciplinary approaches to biomedical engineering, particularly in rehabilitation technology and neuroimaging analysis. His recent work leverages deep learning and graph neural networks to analyze functional MRI data for brain disorder detection, domain adaptation in medical imaging, and progression forecasting of cognitive impairments. He has contributed to tools like ACTION for brain network analysis and frameworks for MRI harmonization and cross-domain adaptation. His publications span topics such as federated learning for medical data, self-supervised learning in neuroimaging, and multimodal fusion for cognitive decline prediction. His work addresses challenges in clinical translation, data heterogeneity, and model interpretability, with applications in Alzheimer’s disease, depression, and neurocognitive disorders. Notable contributions include domain generalization methods for medical image classification, attention-guided frameworks for dementia diagnosis, and disentangled representation learning for MRI analysis. His research bridges advanced computational techniques with clinical needs, aiming to improve diagnostic accuracy and personalized healthcare solutions.

Trevor DarrellView profile

Professor

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +3 more

Professor Trevor Darrell is a faculty member in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. He leads research in computer vision, machine learning, and robotics, focusing on algorithms for visual recognition and perception-based interfaces. His affiliations include the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Center for Responsible, Decentralized Intelligence (RDI), and the International Computer Science Institute (ICSI). Education: PhD, MIT (1996) BSE in Computer Science, University of Pennsylvania (1988) Research Interests: Professor Darrell’s work spans Artificial Intelligence , Computer Vision , Robotics , and Multimodal Learning . His recent efforts emphasize vision-language models, embodied AI, and ethical AI frameworks for healthcare and robotics. Notable Contributions: His articles in 2025 highlight advancements in multimodal generation, humanoid control, and model alignment. Trends include leveraging vision-language integration for robotics tasks and addressing AI bias and hallucination. Awards: ICML Test of Time Award (2024) ACM SIGMM Test of Time Paper Award (2024) CVPR Longuet-Higgins Prize (2024) Labs & Collaborations: Leads BAIR and RDI, advancing responsible AI and geospatial analysis through initiatives like Berkeley Deep Drive and the CITRIS People and Robots (CPAR) program.

• Mechanobiology
• Cell Adhesion
• Biophysics
• +3 more

Prof. Leckband is a Professor in the Department of Chemical & Biomolecular Engineering at the University of Illinois, affiliated with the School of Chemical Sciences. Her research focuses on fundamental biophysical interactions at bio-interfaces, with two core directions: mechano-transduction in cell adhesion and biomaterial design for biomedical applications. Key projects include studying cadherin-mediated intercellular adhesion, force-dependent signaling pathways, and material properties that control protein adsorption. Her work bridges cell biology and engineering through projects like designing non-fouling materials, manipulating tissue functions via engineered cues, and understanding glycolysis' role in endothelial barrier integrity. Collaborations with tissue engineers aim to apply these insights to muscle differentiation and stem cell therapies. Recent articles highlight advancements in single-molecule cadherin studies, microfluidic platforms for mechanical stress analysis, and the role of glycolysis in junction mechanics. Her lab's biomaterials research addresses protein-stabilizing hydrogels and zwitterionic polymer surfaces for medical implants. The Leckband Group emphasizes translational research, integrating computational modeling with experimental validation to uncover mechanistic principles. Advising efforts involve mentoring graduate students in interdisciplinary projects at the bioengineering interface. Lab activities include developing modular hydrogels conjugated with cadherins to guide neural growth, and investigating how substrate stiffness and cyclic stretch impact endothelial monolayer integrity. Current work explores combinatorial cadherin complexes as mechano-switches regulating cell mechanics. Lab infrastructure includes advanced AFM, microfluidic systems, and live-cell imaging setups. Ongoing projects aim to correlate mechanical forces at junctions with global cell behavior, and to engineer biomaterials that preserve protein stability in non-biological environments.