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Douglas C. NollView profile

Professor

• Medical Imaging
• Biomedical Engineering
• Functional MRI (fMRI)
• +5 more

Douglas C. Noll is the Ann and Robert H. Lurie Professor of Biomedical Engineering and Professor of Radiology at the University of Michigan. He holds key roles as Co-Director of the Functional MRI Laboratory, Co-Lead of the NeuroImaging Core at the Michigan Alzheimer’s Disease Research Center, and collaborator at the Michigan Institute for Imaging Technology and Translation (MIITT). His affiliations include the Michigan Neuroscience Institute, Center for Computational Medicine and Bioinformatics, and Michigan Concussion Center. His research focuses on advancing MRI and fMRI technologies to study brain function and neurological disorders. Key projects include rapid image acquisition, artifact elimination, physiological modeling, and MRI-guided therapies like histotripsy. Recent work emphasizes pre-clinical MRI-guided focused ultrasound systems and collaborations with neuroscientists to map brain organization in health and disease. Notable contributions include developing the Oscillating Steady State Imaging (OSSI) technique, the TOPPE framework for MRI sequence prototyping, and tools like FieldMapNet MRI for off-resonance correction. His lab addresses challenges in high-resolution fMRI, real-time motion compensation, and translational imaging for clinical applications. Current efforts span improving MRI hardware-software integration, advancing non-invasive brain therapies, and applying machine learning to enhance image reconstruction and artifact correction. Collaborations bridge engineering, neuroscience, and clinical medicine to tackle complex neurological conditions like Alzheimer’s and brain tumors.

Amin Reza RajabzadehView profile

Associate Professor

• Biochemical Engineering
• Biosensors
• Separation Processes
• +7 more

Dr. Amin Reza Rajabzadeh is an Associate Professor at the W Booth School of Engineering Practice and Technology, McMaster University, with affiliate roles in the McMaster School of Biomedical Engineering and Mechanical Engineering. He specializes in biochemical engineering, focusing on biosensors, bioseparation processes, and bioprocess monitoring. His research includes developing biosensors for biological process monitoring and nanotechnology-based cancer therapies. He holds a Professional Engineer license (P.Eng.) and is a member of the Canadian and American Engineering Education Associations. Dr. Rajabzadeh's teaching spans core biochemical engineering courses like Bioreactor Design and Bioprocess Control. He has received the McMaster President’s Award for Teaching and a MacPherson Leadership in Teaching Fellowship. His research clusters span Energy, Environment, Health & Bio-innovation, and Micro-Nano Systems. Recent work includes nanoplatforms for photothermal cancer therapy (ACS Applied Materials & Interfaces, 2021) and innovations in sustainable protein enrichment via tribo-electrostatic separation. Collaborations span biomaterials, environmental engineering, and nanotechnology. Awards: Teaching Excellence Awards, Leadership Fellowships Research Themes: Biosensors, Nanomedicine, Bioseparation Technologies Labs/Teams: Biomedical Engineering Research Group, Nanotechnology Applications Lab

Soufiene DjahelView profile

Professor

• Connected and Autonomous Vehicles (CAVs)
• Unmanned Aerial Vehicles (UAVs)
• Cyber Security
• +7 more

Soufiene Djahel is a Professor at the Centre for Future Transport and Cities (CFTC) at Coventry University, UK. His research focuses on connected and autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), cyber security, and smart cities. He holds a PhD in Secure Routing and Medium Access Protocols from Université des Sciences et Technologies de Lille (2010), and has held academic positions including Senior Lecturer at the University of Huddersfield and Manchester Metropolitan University. His research interests include CAV coordination protocols, cyber-physical security solutions, and intelligent transportation systems. Djahel leads projects such as the £1.2M AeroPharma Logistics initiative and has secured funding from the Newton Fund and JSPS. He is a recipient of the 2021 JSPS Invitational Fellowship and has published extensively in IEEE journals and conferences. Current projects explore UAVs-as-a-service, digital twins for CAVs, and B5G/6G for smart infrastructure. He advises PhD students on topics like AI-based threat mitigation and transport electrification. Djahel also serves as an external examiner and editorial board member for journals like IEEE Transactions on Intelligent Transportation Systems.

Janki BhimaniView profile

Professor

• Emerging Memories
• Flash-Based Storage Systems
• Machine Learning
• +7 more

Janki Bhimani is a Professor and Director of the Data Management Research Lab (DaMRL) at the School of Computing and Information Science, Florida International University (FIU). Her research focuses on Memory and Storage Systems, Cloud Computing, Performance Modeling, and Applied Machine Learning. She holds a Ph.D. in Computer Engineering from Northeastern University (2019), an M.S. in Electrical and Computer Engineering (2016), and a B.S. in Electrical and Electronics Engineering from GITAM University (2013). Prior to FIU, she taught at Northeastern University and collaborated with Samsung Semiconductor Research Labs on flash-based SSDs. Her research interests include emerging memory technologies, high-performance computing, and datacenter reliability management. She leads innovative projects like Heimdall (machine learning for storage I/O optimization) and MoKE (modular key-value storage emulation). Awards include FIU Top Scholar and KFSCIS Excellence in Applied Research. Teaching highlights include CIS 3530 (Data Structures), CIS 5346 (Storage Systems), and EECE 2560 (Engineering Algorithms). Her work emphasizes bridging theory and practice, with patents on storage system optimization and machine learning integration.

Omprakash GnawaliView profile

Associate Professor

• Internet of Things
• Smart Devices
• Wireless Sensor Networks
• +3 more

Omprakash Gnawali is an Associate Professor in the Department of Computer Science at the University of Houston, with expertise in Internet of Things, wireless sensor networks, and artificial intelligence. His research focuses on advanced networking protocols, mobility analysis, and safety monitoring systems. Postdoctoral work at Stanford University PhD in Computer Science from University of Southern California Masters and Bachelors from Massachusetts Institute of Technology His research interests include Ultra-Wideband (UWB) localization, network protocol design, edge computing for monitoring systems, and mobile sensor networks. He leads the Networked Systems Laboratory , where he develops frameworks like the Collection Tree Protocol and CodeDrip for efficient data dissemination. Recent publications highlight trends in UWB-based safety monitoring, routing optimization in dual-radio networks, and deception detection in cybersecurity. He has secured NSF Student Travel Grants for ACM SenSys conferences in 2016 and 2017. Scientific Awards NSF Student Travel Grant (2017) NSF Student Travel Grant (2016) He actively mentors students in research projects and teaches courses such as Research Methods in Computer Science and Computer Networks . His service roles include Technical Program Committee memberships and chairing the TinyOS Network Protocol Working Group.

Ramana VinjamuriView profile

Associate Professor

• Brain-Machine Interfaces
• Neuroprosthetics and Exoskeletons
• Machine Learning
• +4 more

Ramana Vinjamuri is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a secondary appointment as Visiting Professor at the Indian Institute of Technology, Hyderabad, India. His academic journey includes a Ph.D. in Electrical Engineering from the University of Pittsburgh (2008), M.S. in Bioinstrumentation from Villanova University (2004), and B.Tech. in Electrical and Electronics Engineering from Kakatiya University (2002). Dr. Vinjamuri's research focuses on Brain-Machine Interfaces (BMIs) for upper-limb prostheses control , neuroprosthetics and exoskeletons , machine learning in motor control , and neurophysiological signal processing . His work extends synergy-based models to control 37-dimensional hand movements, addresses human-robot interaction through emotionally intelligent systems, and develops neurotechnologies for substance use disorder using wearable sensors and AI. NSF CAREER Award (2019) NSF IUCRC BRAIN Center Planning Grant (2020) Harvey N Davis Distinguished Teaching Assistant Professor Award (2018) His publications demonstrate expertise in EEG and EMG signal analysis , deep learning for motor decoding , synergy modeling , and humanoid robot control . The Vinjamuri Lab at UMBC involves graduate, undergraduate, and high school researchers, with international collaborations in India and the US.

Zhaolin ChenView profile

Associate Professor

• Machine Learning
• Deep Learning
• Medical Imaging
• +5 more

Zhaolin Chen is an Associate Professor in the Department of Data Science & AI at Monash University's Faculty of Information Technology. He holds a PhD in Biomedical Imaging from Monash University and has held roles at the University of Melbourne, Florey Neuroscience Institutes, and the medical imaging industry in Europe. He is an Australian Research Council MCR Industry Fellow and leads Australia's first Point-of-Care MRI network at the National Imaging Facility. His research focuses on AI-driven medical imaging, MRI/PET methods, and multimodal data analysis. He has secured over $8M in research funding, including leadership roles in major projects like the National Mobile MRI Network. Education: PhD in Biomedical Imaging, Monash University Research Fellowships at University of Melbourne and Florey Neuroscience Institutes Research Interests: Deep learning and machine learning in medical imaging MRI/PET acquisition/reconstruction methods Multimodal imaging (e.g., simultaneous MR-PET) Translational research with 10+ patents (5 commercialized) Awards & Grants: ARC Discovery Project (Primary Chief Investigator) 5 highly cited papers (top 10% worldwide in 2021) 2021 SciVal: 90% publications in top 10% journals Recipient of Douglas Lampard Research Prize, ISMRM Magna Cum Laude Leadership & Service: President-Elect, ANZ Chapter of ISMRM (2024) Associate Editor for IEEE ISBI (2022-2023) Program Committee Member for ISMRM (2018-2021) Labs & Teams: Monash Biomedical Imaging leadership National Mobile MRI Network project leadership Collaborations across global institutions (e.g., Hyperfine Inc., University of Queensland)

Marla KellerView profile

Professor

• HIV Prevention in Women
• Vaginal Microbicides
• Pre-Exposure Prophylaxis (PrEP)
• +4 more

Dr. Marla Keller is a tenured Professor of Medicine and Obstetrics & Gynecology at Albert Einstein College of Medicine, currently serving as Executive Dean and holder of the Jacob and Jeanne Barkey Chair in Medicine. Director, NIH-funded Harold and Muriel Block Institute for Clinical and Translational Research Interim Senior Associate Dean for Clinical and Translational Research Vice Chair of Research for Department of Medicine Dr. Keller's research focuses on: Biomedical HIV prevention strategies Vaginal microbicide development PrEP implementation in women Cervical cancer screening in HIV+ women Immune responses to SARS-CoV-2 COVID-19 clinical trials Her recent publications emphasize: HPV infection and cervical precancer Vaginal microbiome interactions PrEP delivery systems HIV/HSV coinfection dynamics Convalescent plasma therapy Metronidazole treatment response Key scientific awards include: Infectious Disease Mentoring Award (2013) COVID-19 Distinguished Service Award (2021) Spirit of Achievement Changemaker Award (2023) New York Super Doctor (2011-2015)

Rachel HarrisonView profile

Professor

• Software Engineering
• Machine Learning
• Requirements Engineering
• +3 more

Professor Rachel Harrison is a Professor in Computer Science at the School of Engineering, Computing and Mathematics, Oxford Brookes University. Her research focuses on software metrics, machine learning, and requirements engineering with emphasis on empirical and automated software engineering solutions. She has over 160 publications and extensive industry collaborations with organizations like IBM and Philips Research Labs. Her work has been recognized through roles as Editor-in-Chief of the Software Quality Journal and leadership in conferences such as ICSE and ESEM. She leads the Dependable System Engineering Centre (DSERC) and is part of the Artificial Intelligence, Data Analysis and Systems (AIDAS) Institute and the Applied Software Engineering and Data Analytics (ASEDA) Group. Her research projects include AI applications for big data analysis (AIMi), automated review classification (ReClass), and software quality improvement (SEQUIN). Professor Harrison has served on over 50 international program committees and initiated workshops like RAISE and AIRE. Her teaching includes advanced computer science modules and leadership in courses like Essential Maths for University Study and Advanced Software Development . Her work bridges academic research and practical applications, particularly in healthcare technology (e.g., diabetes management systems) and mobile application usability. She advocates for rigorous software quality practices and has contributed to frameworks for requirements validation and risk assessment in software projects.

Tina ShoaView profile

Associate Professor

• Battery Technology
• Electrochemical Engineering
• Energy Storage Systems
• +3 more

Tina Shoa is an Associate Professor in the School of Sustainable Energy Engineering at Simon Fraser University. She holds a Ph.D. in Electrical Engineering from the University of British Columbia (2010), an M.Sc. from the University of Manitoba (2004), and a B.Sc. from Iran University of Science and Technology (2000). Her research focuses on battery performance modeling, electrochemical methods for fault detection, sustainable battery manufacturing, and AI-based diagnostics. Education: Ph.D., Electrical Engineering, University of British Columbia, 2010 M.Sc., Electrical Engineering, University of Manitoba, 2004 B.Sc., Electrical Engineering, Iran University of Science and Technology, 2000 Research Interests: Battery performance modeling, analysis, and optimization Electrochemical and ultrasound-based battery fault detection Sustainable battery manufacturing processes AI-driven battery diagnostics Teaching and Courses: Advanced Battery and Fuel Cell Technologies Power Plant Systems Smart Grids Practicum SEE 354 D100 Energy Storage (Summer 2025) Patents: Battery State-of-health Determination upon charging (US Patent 11079437B2, 2022) Battery State-of-health Determination using multi-factor normalization (US Patent 10,302,709, 2019) Apparatus and Method for testing electrochemical systems (US Provisional Patent 62/994687, 2020) Key Contributions: Her work integrates electrochemical principles and AI to advance battery diagnostics and sustainable energy storage solutions. She has authored over 15 publications in top-tier journals and conferences, addressing battery aging, state estimation, and novel manufacturing techniques.

Sarthak MisraView profile

Professor

• Medical Robotics
• Surgical Robotics
• Microrobotics
• +3 more

Prof. Sarthak Misra is a Full Professor in Medical Robotics at the University of Groningen’s Faculty of Medical Sciences, affiliated with the University Medical Center Groningen (UMCG). He leads research in the Robotics and image-guided minimally-invasive surgery (ROBOTICS) group and the Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE) team. His work focuses on advancing medical robotics, microrobotics, and magnetic actuation technologies for surgical and biomedical applications. He holds an ORCID identifier and has published over 127 research outputs, including high-impact articles in journals like Advanced Materials Technologies and European Heart Journal . His research addresses challenges in minimally invasive surgery, soft robotics, and smart materials. Media engagements highlight his contributions to robotic surgery and addressing healthcare workforce shortages through automation. Research interests include: Microrobotics and fluidic systems Magnetic and acoustic actuation for medical devices Soft robotic systems for surgical applications Image-guided interventions 3D printing for biomedical robotics His recent articles emphasize innovations like MagNoFE3D printing and magnetic probes for endovascular interventions. Collaborations span global institutions, reflecting his interdisciplinary approach. No explicit awards are listed, but his extensive media coverage and 127+ publications underscore his impact. He is involved in grants, including OTP-funded projects, and mentors students in advanced robotics and medical engineering.

• Medical Imaging
• Breast Cancer Diagnosis
• Phase-Contrast Tomography
• +4 more

Dr. Amir Tavakoli Taba is a Senior Lecturer in Medical Imaging Sciences at the University of Sydney, where he co-directs the Medical Image Optimisation and Perception Group (MIOPeG). He specializes in improving medical imaging accuracy, particularly in breast cancer diagnosis, through advancements like phase-contrast tomography and AI integration. His work bridges technological innovations (e.g., low-dose imaging) with clinical practice, emphasizing quality control and radiologist performance analysis. Education: PhD (University of Sydney) MEngSc (University of New South Wales) BSc (University of Tehran) Research Interests: Dr. Taba’s research focuses on phase-contrast computed tomography (PCT), AI-driven diagnostic tools, and clinical workflow optimization. His projects include the world’s first PCT clinical trial (scheduled for 2024 in Melbourne) and collaborations with institutions like ANSTO, Harvard Medical School, and the University of Iowa. He also investigates radiologist expertise development and the role of social networks in medical decision-making. Grants & Awards: NHMRC Synergy Grant (IMPACT: Implementation of X-ray Phase-Contrast Tomography) International recognition, including the SPIE Medical Imaging Award Advising & Labs: Current students: Mohammed ALANAZI (abdominal CT optimization), Jenna ARBID (phase-contrast imaging) Labs: MIOPeG, part of the Sydney Vital and Sydney Catalyst cancer research networks Teaching: Courses in imaging technologies, medical image perception, and clinical capstone projects for diagnostic radiography students.

Noa MaromView profile

Associate Professor

• Computational Materials Science and Engineering
• Quantum Materials
• Semiconductor Materials
• +5 more

Noa Marom is an Associate Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU), holding courtesy appointments in Chemistry and Physics. She is a member of the Pittsburgh Quantum Institute (PQI) and an affiliate of the Wilton E. Scott Institute for Energy Innovation. Her research focuses on computational materials science, energy security, and quantum materials. Marom earned a B.A. in Physics and B.S. in Materials Engineering (cum laude) from the Technion-Israel Institute of Technology (2003) and a Ph.D. in Chemistry from the Weizmann Institute of Science (2010). She held postdoctoral positions at the University of Texas at Austin’s Institute for Computational Engineering and Sciences (ICES) before joining Tulane University as an Assistant Professor (2013–2016) and CMU in 2016. Her research interests include computational design of semiconductor materials, topological quantum computing, and crystal structure prediction. Key projects involve machine learning for materials discovery and quantum computing applications, such as optimizing semiconductor interfaces for stable qubits. Marom has received numerous awards, including the NSF CAREER Award (2016), DOE INCITE Awards (2017–2019), and the IUPAP Young Scientist Prize (2018). She serves as Associate Editor of npj Computational Materials. Her work spans collaborations with institutions like the Paul Scherrer Institute (Switzerland) and the Pittsburgh Supercomputing Center. Research highlights include computational studies of InAs/InSb semiconductors for quantum bits and machine learning-driven discovery of organic semiconductors.

• Biomedical Informatics
• Data Science
• Machine Learning
• +7 more

Lucila Ohno-Machado, MD, PhD, MBA, is the Waldemar von Zedtwitz Professor of Medicine and Biomedical Informatics and Data Science at Yale University. She serves as Deputy Dean for Biomedical Informatics and Chair of the Department of Biomedical Informatics and Data Science at the Yale School of Medicine. Her leadership roles include overseeing informatics infrastructure for Yale’s academic health system and fostering interdisciplinary collaboration across departments such as Medicine and the Halicioğlu Data Science Institute (previously at UCSD). Ohno-Machado holds an MD from the University of São Paulo (Brazil), an MBA from Fundação Getúlio Vargas (Brazil), and a PhD in Medical Information Sciences and Computer Science from Stanford University. She has held faculty positions at Harvard Medical School, MIT’s Health Sciences and Technology Division, and the UCSD Health Department of Biomedical Informatics, where she pioneered federated learning and privacy-preserving AI methodologies. Her research focuses on predictive analytics, federated learning, quantum computing in healthcare, and blockchain applications to enhance data security. She emphasizes addressing algorithmic bias and promoting health equity through data-driven solutions. Recent work includes developing frameworks for medical device safety evaluation and guiding principles to mitigate disparities in algorithmic healthcare applications. Key achievements include the Inaugural Helen M. Ranney Award (2024), election to the National Academy of Medicine (2024), and the William W. Stead Award (2019). She has led NIH-funded informatics centers and contributed to the first large-scale clinical data-sharing initiative across five UC medical systems. Her grants span AHRQ, PCORI, NSF, and blockchain-related initiatives through the IT/NIST Challenge Award. Ohno-Machado advises on translational research strategies and mentors teams in YBIC (Yale Biomedical Informatics & Computing). Her lab collaborates globally, leveraging federated models and AI to advance personalized medicine while prioritizing patient privacy. She also chairs the OHER Awards for Yale Research Excellence, promoting interdisciplinary health equity research.

Shalini PrasadView profile

Professor

• Bioengineering
• Nanotechnology
• Medical Diagnostics
• +3 more

Dr. Shalini Prasad is the Cecil H. and Ida Green Professor in Systems Biology Science and Associate Professor of Bioengineering at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. She also holds an adjunct professorship in Physics at Portland State University. Her research focuses on developing nanomaterial-based biosensors for medical diagnostics, environmental monitoring, and public health applications. She leads the Biomedical Microdevices and Nanotechnology Lab, which has supported over 50 researchers across graduate and undergraduate levels. Dr. Prasad earned her PhD in Electrical Engineering from the University of California, Riverside (2004) and B.E. in Electronics and Communication Engineering from the University of Madras (2000). Her career includes roles at Portland State University, Arizona State University, and Wichita State University. She has received prestigious awards, including the Bomhoff Distinguished Professorship and the Cecil Green Professorship, and holds over 30 peer-reviewed publications. Her research interests emphasize interdisciplinary approaches to create affordable, portable diagnostic tools for diseases like cancer, neurodegeneration, and cardiovascular disorders, as well as environmental sensors for soil health and water quality. Recent work includes wearable devices for monitoring inflammatory bowel disease and asthma, saliva-based THC detection, and low-cost CO₂/humidity sensors. Awards: Graduate Student Research Award (2004) Bomhoff Distinguished Professor of Bioengineering Cecil H. and Ida Green Professorship Advising & Grants: Dr. Prasad’s lab has secured funding from federal agencies and corporate partners, supporting projects like the SWEAT wearable for chronic inflammation tracking and soil health sensors. Her work bridges engineering, biology, and clinical applications, with a focus on translational technologies. Labs/Teams: Director of the Biomedical Microdevices and Nanotechnology Lab, collaborating on interdisciplinary projects with industry and academic partners.