Aline Eid is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Michigan Ann Arbor, directing the Beam Dynamics research group. Her work bridges electromagnetics, wireless systems, and autonomous technologies, with a focus on mmWave/sub-THz sensing, backscatter communications, and wireless power transfer. PhD in Electrical and Computer Engineering (Georgia Tech, 2021) MS in Electrical and Computer Engineering (American University of Beirut, 2017) Postdoctoral Associate at MIT Media Lab (Signal Kinetics group) Research Interests: She pioneers systems that use electromagnetic waves to address societal challenges in Sustainable energy networks Smart cities/infrastructures Autonomous vehicles/robots Her group develops mmID tags for radar vision, batteryless sensors, and 5G-based wireless power grids. Scientific Impact: Recognized with awards including IEEE RFID Best Paper (2023) Proceedings of the IEEE Best Paper (2023) IEEE MTT-S Graduate Fellowship (2020) She leads commercialization efforts for warehouse robotics via MTRAC grant and startup Atheraxon. Advising: Mentors 8 students across PhD (Skanda Harisha, Sepideh Ghasemi, Yunfei Liu), Master's (Longyu Guo), and undergraduates (Mohamed Safawi, Katherine Shih, Andy Wang, Adrian Velazquez) in projects spanning robotics, IoT, and electromagnetic engineering. Labs: Beam Dynamics group at U-M Radiation Laboratory, collaborating with Atheraxon and MTRAC for technology translation.
Elahe Soltanaghai is an Assistant Professor in the Department of Computer Science and a Faculty Affiliate in Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. She is also a 2022 NCSA Fellow and received her PhD in Computer Science from the University of Virginia (2019), MS in Computer Engineering from Sharif University of Technology (2014), and dual BS degrees in Computer and Information Technology Engineering from Amirkabir University of Technology (2011, 2013). PhD: University of Virginia, Computer Science, 2019 MS: Sharif University of Technology, Computer Engineering, 2014 BS (Computer Engineering): Amirkabir University of Technology, 2011 BS (Information Technology Engineering): Amirkabir University of Technology, 2013 Her research spans wireless sensing and communication, focusing on Millimeter-wave Radar Sensing (for automotive, mixed reality, structural monitoring), Machine Learning for Wireless Systems (adaptive sensing/communication), Forest IoT (through-canopy biomass and soil sensing), Metaverse Technologies (gaze-based VR/AR), and Low-Power Backscatter Communication (WiFi/power-line tags). She directs the Wireless, Sensing & Embedded Networked Systems (iSENS) Lab and co-directs the Illinois Center for IoT. Her work bridges wireless networking with cyber-physical sensing , emphasizing environmental monitoring (e.g., wildfire fuel detection via radar tags) and human-computer interaction (e.g., gaze-tracking in VR). Recent articles include innovations in passive radar profiling , through-canopy biomass characterization , and integrated communication-sensing protocols . Scientific Awards: Google Research Scholar Award (2022) N2Women Rising Star (2021) ACM SIGMOBILE Dissertation Award (2020) EECS Rising Stars (2019) NCSA Faculty Fellowship (2023) Best Demo Runner-up, IPSN (2023) Teaching Excellence Award (2023) Grants: NASA FireTech Program Grant (2025) NSF Grant for Radar-based Perception (2024) Insper-Illinois Grant for VR Research (2024) Keysight Research Gifts (2022, 2023) T-Mobile Research Gift (2022)
Professor Hong Hao is a John Curtin Distinguished Professor at Curtin University, affiliated with the School of Civil and Mechanical Engineering and the Curtin Research Centre for Infrastructural Monitoring & Protection. His expertise spans Structural Dynamics, Earthquake Engineering, Blast and Impact Engineering, and Structural Health Monitoring. He holds prestigious roles like Fellow of ATSE, ISEAM, and ASCE, and has led organizations such as the International Association of Protective Structures and the Australian Earthquake Engineering Society. Education: BE (Tianjin University, 1982), MSc (UC Berkeley, 1985), PhD (UC Berkeley, 1989). Awards include the Tan Chin Tuan Fellowship and multiple Ko Medals. He has authored over 200 journal articles, with recent work focusing on blast-resistant materials, seismic fragility, and AI-driven structural health monitoring. His research emphasizes resilient infrastructure, including metaconcrete structures, corrosion-resistant materials, and sensor-based damage detection. Ongoing projects involve smart tunnel safety under BLEVE explosions and modular building systems.
Professor Rainer Böhme is a prominent academic in the field of IT security and privacy at the University of Münster's School of Business and Economics, Department of Information Systems. He also holds a professorship for Security and Privacy at the University of Innsbruck's Institute of Computer Science. His research spans multiple dimensions of digital security, with particular expertise in steganography, digital forensics, privacy-enhancing technologies, and the economic aspects of cybersecurity. Dr. Böhme earned his Doctoral Degree from TU Dresden's Faculty of Computer Science in 2008, following studies in Communications, Economics and Computer Science at Technische Universität Dresden and Université Paris XII. His academic journey includes positions as Assistant Professor at the University of Münster (2010-2015), Postdoctoral Fellow at the International Computer Science Institute in Berkeley (2009-2010), and Scientific Staff at TU Dresden's Chair of Privacy and Data Security. His research interests focus on steganography and steganalysis, digital forensics, privacy-enhancing technologies, security and usability, economic and behavioral aspects of information privacy, virtual currencies, and the economics of information security. His work bridges technical security mechanisms with economic and behavioral considerations, creating a unique interdisciplinary approach to cybersecurity challenges. Analysis of his recent publications reveals a strong trend toward the economics of security, particularly regarding blockchain technologies, cryptocurrency, and privacy valuation. His work increasingly examines the intersection of technical security mechanisms with market dynamics, regulatory frameworks, and user behavior. The research spans theoretical game-theoretic models, empirical studies of user behavior, and practical applications in digital forensics and privacy protection. Program Co-Chair, Financial Cryptography and Data Security (2015) Program Co-Chair, New Security Paradigms Workshop (NSPW) (2015) General Chair, 8th International Conference on IT Security Incident Management & IT Forensics (2014) Organizer and Program Co-Chair, 1st Workshop on Bitcoin Research (2014) Associate Editor, Electronic Commerce Research (since 2013) Associate Editor, EURASIP Journal on Information Security (since 2013) Professor Böhme has supervised multiple Master's theses in Information Systems, including work on static code analysis for smart contracts, remote maintenance protocol security, and application protection requirements in retail banking. His research is supported by significant grants from the German Federal Ministry of Research, Technology and Space, the DFG, and the EU FP7 program, with projects focusing on digital forensics, privacy-enhancing technologies, and cryptocurrency crime prevention. He leads the IT Security Research Group at the University of Münster, which investigates theoretical and applied aspects of information security with particular emphasis on the economic dimensions of security decisions.
Dr. Daniel J. Preston is an Assistant Professor of Mechanical Engineering at Rice University, leading the Preston Innovation Laboratory (PI Lab). He holds a B.S. from the University of Alabama (2012), M.S. and Ph.D. from MIT (2014, 2017), and postdoctoral training at Harvard University (2017-2019). His research focuses on energy efficiency, soft materials, fluid mechanics, and robotics, with applications in wearable technologies and sustainable systems. Key achievements include the NSF CAREER Award (2022) and pioneering work on necrobotics using biotic materials. The PI Lab collaborates widely, with projects involving biomimetic surfaces, smart textiles, and fluidic control systems. Education: B.S. Mechanical Engineering, University of Alabama (2012) M.S./Ph.D. Mechanical Engineering, MIT (2014/2017) Research Interests: Energy : Thermal management, heat transfer optimization, and waste heat recovery. Materials : Soft actuators, surface coatings, and functional biomaterials. Fluids : Interfacial phenomena, droplet dynamics, and fluid-structure interactions. Notable Publications: Recent work includes advancements in wearable haptic devices ( Science Advances ), necrobotics ( Advanced Science ), and fluidic logic textiles ( PNAS ). Over 50 peer-reviewed articles span multidisciplinary topics from magnetic levitation to virus decontamination. Honors: In addition to the CAREER Award, Dr. Preston has received the NSF Graduate Research Fellowship, Tau Beta Pi Fellowship, and Wunsch Foundation Award. His lab fosters innovation through grants and industry partnerships. Advising & Grants: Supervises ~15 graduate and undergraduate students, including NSF GRFP recipients. Active in mentoring initiatives like the Randall Research Scholars Program and AATCC grants. Labs & Teams: The PI Lab collaborates with MIT’s DRL, Harvard’s Whitesides Group, and institutions globally. Core projects include smart wearables, energy harvesting fabrics, and autonomous soft robots.
Christopher D.P. Baxter is a Professor and Department Chair of Civil and Environmental Engineering at the College of Engineering, University of Rhode Island , with expertise in geotechnical engineering, offshore wind energy, and coastal resilience. He holds a Ph.D. in Civil Engineering from Virginia Tech (1999), an M.S. from Purdue University (1994), and a B.S. from Tufts University (1990). Research Focus: Geotechnical characterization of marine sediments, liquefaction resistance analysis, fiber-optic sensing for infrastructure monitoring, and coastal protection systems. Recent Publications: 15+ articles (2011–2025) covering topics like shear wave velocity, offshore wind foundation dynamics, and tsunami hazard modeling. Grants: Led projects on offshore wind monitoring (2019–2024) and fiber-optic seismic sensing (2021–2023). Key Collaborations: Work with teams on submarine landslide analysis, coastal dune reinforcement, and Rhode Island infrastructure resilience. His work bridges experimental geomechanics with practical coastal engineering solutions.
Roberta Sinatra is a Professor in Social Data Science at the University of Copenhagen, with part-time affiliations at ITU Copenhagen, ISI Foundation (Italy), and CSH (Austria). She co-founded the NERDS Research Group at ITU and co-leads the Pioneer Centre for AI in Copenhagen. Research Interests: Her work spans computational social science, network science, and data science, focusing on fairness in AI, scientific careers, and human mobility. Recent projects include analyzing child protection algorithms and modeling urban bicycle networks. Scientific Awards: ERC Consolidator Grant Villum Young Investigator Grant Complex Systems Society Junior Prize DPG Young Scientist Award for Socio- and Econophysics Sapere Aude: Starting Grant Publications: Her research, often in top-tier venues like Nature and Science , explores interdisciplinary themes, including AI ethics, gender disparities in science, and social network dynamics. Labs & Teams: She leads research initiatives at the Center for Social Data Science (KU) and co-founded the NERDS Research Group at ITU, fostering international collaboration in network science and AI ethics.
Dr. Binbin Xie is an Assistant Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington (UTA). She holds a Ph.D. from the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst, where she was a recipient of the prestigious Google PhD Fellowship in Mobile Computing. Her research focuses on wireless sensing, mobile health, cyber-physical systems, smart IoT, and wireless networking. Dr. Xie’s academic journey includes a tenure-track position at UTA since September 2024. She has received notable awards such as the Emerging Rockstar (IEEE Pervasive Computing, 2025), Rising STARs Award (UT System, 2024), and multiple scholarships including the Krithi Ramamritham Computer Science Scholarship (2023). Her work spans innovative applications in wireless sensing, leveraging LoRa, mmWave radar, and RFID technologies for real-world challenges like in-vehicle sensing and indoor localization. Her recent publications highlight advancements in LoRa sensing coexistence with communication, mmWave radar human sensing using secondary reflections, and combating interference in multi-target localization. She actively contributes to the academic community through service roles, including Technical Program Committee memberships for MobiSys 2025 and EWSN 2025, and as a reviewer for top-tier conferences like IMWUT/UbiComp and journals such as ACM Transactions on Sensor Networks. Dr. Xie’s teaching includes courses like CSE 4321 (Software Testing & Maintenance). Her research and educational efforts aim to bridge theoretical innovations with practical implementations in wireless and IoT systems.
Michael Bartlett is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech , leading the Soft Materials and Structures Lab within the College of Engineering. His research focuses on bio-inspired materials , soft robotics , and multifunctional composites with applications in adaptive adhesives , stretchable electronics , and self-healing systems . Education: Ph.D., Polymer Science & Engineering, University of Massachusetts Amherst (2013) B.S.E., Materials Science & Engineering, University of Michigan (2008) His work explores the intersection of soft materials , morphing structures , and functional composites , leveraging techniques like kirigami and liquid metal integration to create innovations such as octopus-inspired underwater gloves and shape-shifting drones . His recent articles highlight advancements in programmable adhesion , liquid metal conductors , and multiscale material design . Scientific Awards: National Academy of Inventors Senior Member (2024) NSF CAREER Award (2023) Office of Naval Research Young Investigator Award (2021) Soft Matter Emerging Investigator (2021) DARPA Director’s Fellowship (2020) Adhesion Society Early Career Scientist (2020) DARPA Young Faculty Award (2018) 3M Non-Tenured Faculty Award (2017) Bartlett has mentored over 40 undergraduate students and numerous graduate researchers, resulting in 12 peer-reviewed articles with student co-authors. His lab receives funding from federal agencies like NSF , ONR , and DARPA , as well as industry partnerships. The group also engages in K-12 outreach programs and collaborates with institutions such as University of Nebraska-Lincoln and Iowa State University .
Olga Fink is a Tenure Track Assistant Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Department of Intelligent Maintenance and Operations Systems (IMOS) within the School of Architecture, Civil and Environmental Engineering (ENAC). She also holds roles in PhD program committees for Civil and Environmental Engineering (EDCE) and Robotics, Control, and Intelligent Systems (EDRS). Her research focuses on machine learning for infrastructure monitoring, predictive maintenance, and physics-informed AI models. She teaches courses on machine learning, data science for infrastructure, and advanced deep learning topics. Fink advises multiple PhD students and is involved in interdisciplinary projects such as ThermoNeRF (multimodal 3D thermal modeling) and physics-informed neural networks for fault diagnostics. Her work bridges AI and engineering with applications in smart infrastructure, energy systems, and industrial IoT. Education: PhD in Engineering (inferred from role) Affiliations: IMOS Lab, ENAC-SGC, EPFL PhD Committees (EDCE, EDRS) Key Research Themes: Explainable AI, Digital Twins, Structural Health Monitoring, Domain Adaptation Her publications (2023–2025) emphasize robust AI for industrial systems, including fault detection in high-voltage equipment, multimodal data fusion, and physics-consistent models. She collaborates on EU and industry-funded projects, focusing on real-world applications like predictive maintenance and energy efficiency.
Dr. Yunjie Yang is an Associate Professor at the University of Edinburgh's School of Engineering, with affiliations at the Edinburgh Futures Institute (EFI), the Edinburgh Generative AI Laboratory (GAIL), and the Edinburgh Centre for Robotics. He previously held the Chancellor's Fellow in Data Driven Innovation (2018-2023) and Bayes Innovation Fellow (2023-2024) positions. His research focuses on AI-powered sensing and imaging, machine learning, and soft sensors & electronics for robotics. Yang received his PhD in Engineering Electronics from the University of Edinburgh, MSc in Control Science & Engineering from Tsinghua University, and BEng in Measurement & Control Engineering from Anhui University. After his PhD, he worked as a Postdoctoral Research Associate in Chemical Species Tomography before securing his lectureship. His research interests center on developing intelligent sensing systems that replicate human perception capabilities for robotics and intelligent systems. He pioneers flexible sensing and imaging technologies across various scales through innovative multi-modal sensors, soft electronics, and their modeling using machine learning approaches. His work aims to enable autonomous physical artificial intelligence by bridging the gap between robotic systems and human-like perception. Analysis of his recent publications reveals a strong focus on soft robotics perception, particularly through electrical impedance tomography (EIT) and transformer-based architectures. His research spans medical imaging applications, digital twin modeling for industrial processes, and machine learning approaches for sensor data interpretation. The trend shows increasing integration of physics-informed deep learning with traditional tomographic techniques to achieve higher accuracy and efficiency. European Research Council (ERC) Starting Grant (2024) IEEE J. Barry Oakes Advancement Award (2024) IEEE I&M Society Graduate Fellowship Award (2015) Multiple Best Paper Awards Senior Member of IEEE Fellow of the International Society for Industrial Process Tomography Fellow of the Higher Education Academy ESI highly cited papers Dr. Yang serves as Associate Editor for IEEE Transactions on Instrumentation and Measurement and holds editorial positions with Scientific Reports and IEEE Sensors Journal. His research has been licensed to overseas research institutes and industry partners and received wide media coverage including BBC, EFE, USA Today, and STV. He has secured significant grant funding including the prestigious ERC Starting Grant. He leads the Edinburgh SMART Lab (Sensing/imaging + Machine Learning + Robotics), which aims to replicate human perception capabilities for robotics and advance flexible sensing technologies through innovative multi-modal sensors and machine learning approaches. The lab focuses on enabling autonomous physical artificial intelligence with applications spanning medical diagnostics, industrial monitoring, and advanced robotics systems.
Dr. Jiaqi Gong serves as Associate Professor in Computer Science and Adjunct Associate Professor in Mechanical Engineering at The University of Alabama's College of Engineering, while directing the Alabama Center for the Advancement of Artificial Intelligence. His academic foundation includes: B.S. in Engineering, China University of Geoscience (2004) Ph.D. in Engineering, Huazhong University of Science and Technology (2010) Dr. Gong's research pioneers human-AI convergence through cyber-physical systems and smart health technologies, developing mobile/wearable platforms to enhance human perceptual, cognitive, and physical capabilities. His work spans artificial intelligence, machine learning, computer vision, and IoT with applications in healthcare, environmental monitoring, and education. The Sensor-Accelerated Intelligent Learning (SAIL) laboratory he founded drives innovation in behavior change interventions, human movement modeling, and educational data mining. Recent publications reveal strong interdisciplinary trends: healthcare AI dominates with medication adherence prediction and surgical classification systems, while environmental applications feature flood-risk communication and drought analysis. His work increasingly integrates generative AI and LLMs across domains, demonstrating methodological innovation in federated learning, knowledge graphs, and explainable storytelling frameworks. Notable recognitions include: Best Student Paper Award, IEEE/ACM Connected Health Conference (2022) Best Student Paper Award, Body Sensor Networks Conference (2019) Data Challenge Win, IEEE Biomedical Health Informatics (2018) Best Paper Award, Body Area Networks Conference (2014) Best Demonstration Award, IEEE Wireless Health Conference (2014) Dr. Gong leads significant funded projects including a $2M CDC/NIOSH grant for first responder safety and $3M NSF funding for hydrologic research. As SAIL laboratory director, he mentors students in developing clinically deployed technologies for multiple sclerosis, dementia, and mental health. Future work focuses on scaling AI applications in chronic disease management and climate resilience through the Alabama AI Center. The SAIL laboratory (founded 2017) operates as a multidisciplinary hub developing wearable/mobile systems for health applications, with active collaborations across medical clinics and engineering departments for real-world deployment of behavior change interventions and movement analysis tools.
Ian Miers serves as an Assistant Professor in the Department of Computer Science at the University of Maryland, holding a joint appointment with the University of Maryland Institute for Advanced Computer Studies (UMIACS) and serving as a core faculty member of the Maryland Cybersecurity Center (MC2). His academic home resides within the Department of Computer Science, though the overarching college/school structure is not explicitly stated in available materials. His research program centers on applied cryptography with a context-driven methodology: starting from real-world security challenges to develop deployable cryptographic protocols. Key focus areas include blockchain privacy (notably Zerocoin/Zerocash), zero-knowledge proofs, anonymous credentials, and secure messaging systems. Miers emphasizes practical implementations that address subtle security requirements in production environments, bridging theoretical cryptography with tangible system security. Analysis of his 15 most recent publications reveals dominant trends in zero-knowledge proof scalability (zkSNARKs), privacy-preserving infrastructure for blockchains, and cryptographic solutions for content moderation in encrypted messaging. His work consistently targets deployable systems, with increasing focus on balancing privacy guarantees with accountability requirements in real-world applications. Miers actively recruits PhD students for hands-on research in his small lab, emphasizing direct collaboration on applied security and blockchain problems. As a founding scientist of Aleo, Bolt Labs, and Zcash, he translates academic research into commercial products, with his work receiving coverage from major media outlets including The Washington Post, The New York Times, and Wired.
Abbas Milani is a tenured Professor of Mechanical Engineering at the University of British Columbia's Okanagan campus, where he holds the Tier 1 Principal's Research Chair in Sustainable & Smart Manufacturing and serves as Director of the Materials and Manufacturing Research Institute (MMRI). He also serves as Technical Director of the Composites Research Network (CRN), Lead of the Canadian-International Biocomposites Research Network, and leads multiple major initiatives including the UBC-Pacific Economic Development Canada-Advancing Circular Economy (ACE) program and the UBC-NRC IRAP National Circular Economy CtO Program. Dr. Milani's primary research focuses on advanced modeling, simulation, and multi-criteria design optimization of composite and biocomposite materials, structures, and manufacturing processes. His expertise spans Textile Composites/Biocomposites, Materials Constitutive Relations, Finite Element Modeling, Robust Inverse Methods, Material Selection for End-of-Life Design Strategies, Multiple Criteria Decision Making, and Industry 5.0 applications. His interdisciplinary research bridges mechanical engineering, sustainable materials science, and smart manufacturing technologies. Analysis of his recent publication record reveals a strong emphasis on sustainable materials development, with particular focus on biocomposites, life cycle assessment methodologies, and optimization of manufacturing processes. His work integrates computational modeling with experimental validation across diverse application areas including medical devices, sustainable packaging, and circular economy strategies. The publications demonstrate increasing integration of artificial intelligence and machine learning approaches with traditional engineering methods. 2015 UBC Okanagan Researcher of the Year Award Killam Faculty Research Award (2016) Inducted into Royal Society of Canada - College of New Scholars (2020) Gold Medal Service Contribution Award by Academics World Reviewer Contribution Award by ASM International Multiple teaching excellence awards from UBC Dr. Milani has successfully mentored over 100 students and postdoctoral fellows who have secured positions in both industry and academia. His research program has been supported by more than $15 million in funding from government and industrial organizations. He leads the NSERC CREATE in Immersive Technologies (CITech) program and co-leads the Advanced Materials and Fabrication Core Competency within the Survive and Thrive Applied Research (STAR) program, demonstrating his commitment to training the next generation of engineers and advancing applied research.
Houman Savoji is an Associate Professor in the Department of Pharmacology and Physiology at the Faculty of Medicine, University of Montreal. He is also a full-time researcher at the CHU Sainte-Justine Research Center and principal investigator in regenerative medicine, organs-on-chip, and bioprinting at TransMedTech Institute. Dr. Savoji received his PhD in Biomedical Engineering from the Institute of Biomedical Engineering at Polytechnique Montréal in 2016. He then completed a postdoctoral fellowship at the Institute of Biomaterials and Biomedical Engineering at the University of Toronto. His research expertise combines advanced manufacturing technologies (micro- and nano-fabrication, 3D bioprinting, microfluidics, cell electrospinning) with functional and composite materials for applications in tissue engineering, regenerative medicine, and organs-on-chip. His work focuses on the design, development, optimization, implementation, and characterization of innovative functional biomaterials using emerging engineering technologies, with particular emphasis on cardiac tissue engineering and biomimetic pulmonary heart valves for pediatric patients. Dr. Savoji has published extensively on biomaterials, tissue engineering, 3D bioprinting, and organ-on-chip technologies. His recent publications demonstrate expertise in viscoelastic characterization of soft tissues, engineering immune responses to biomaterials, ceramic engineering for biomedical applications, and advanced 3D bioprinting techniques for cardiac and vascular tissue engineering. 2017-2020, Postdoctoral Research Grant, CIHR 2017-2019, Postdoctoral Research Grant, FRQNT 2017-2018, Human Society of International Grant, Human Toxicity Assessment Project 2016, CR-CHUM Research Center Award 2015, Star Student-Researcher Award, FRQNT 2014-2015, Jane and Frank Warchol Fellowship, Society of Vacuum Coaters Foundation 2013, Institute of Textile Science Award 2012-2015, Excellence Doctoral Scholarship for Foreign Students, FRQNT Dr. Savoji has supervised Master's students including Ines Barrakad (2024) working on 'Advanced manufacturing technologies versus molding of corneal implants: 3D printing vs molding of a Keratoprosthesis' and Zineb Ajji (2023) researching 'Development of perfusable patches by 3D bioprinting for potential application in cardiac tissue regeneration.' He has secured numerous research grants from organizations including CIHR, NSERC, FRQNT, FRQS, MITACS, and others for projects related to 3D bioprinting of cardiac tissues, biomimetic heart valves, and other tissue engineering applications. The Savoji Laboratory, located within the Department of Pharmacology and Physiology and Institute of Biomedical Engineering of the Faculty of Medicine of the University of Montreal, the Research Center of the CHU Sainte-Justine (CHUSJ), and the TransMedTech Institute, focuses on multidisciplinary research involving 3D bioprinting using stem-cell derived human cardiac cells to fabricate functional cardiac tissues for transplantation and drug discovery applications.
