Find Academic Supervisors

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.

Amit GoyalView profile

Professor

• Heteroepitaxial Growth
• Strain-driven Self-Assembly
• Advanced Energy Materials
• +6 more

Dr. Amit Goyal is the SUNY Empire Innovation Professor and SUNY Distinguished Professor in the Department of Chemical and Biological Engineering at the University at Buffalo. He serves as Director of the UB Initiative on Plastics Recycling and Innovation (a New York State Center of Excellence) and previously founded and led the RENEW Institute (2015–2021), focusing on interdisciplinary research in energy, environment, and water. His academic roles include leadership in both research and industry, with expertise spanning clean energy technologies, superconducting materials, and flexible electronics. Education: B. Tech in Metallurgical Engineering, Indian Institute of Technology (1996) MS in Mechanical & Aerospace Engineering, University of Rochester (1988) PhD in Materials Science & Engineering, University of Rochester (1991) Executive MBA, Purdue University International Executive MBA, Tilburg University Research Interests: Dr. Goyal’s work focuses on heteroepitaxial growth , strain-driven self-assembly , and advanced energy materials . He develops clean energy technologies, including superconducting devices and photovoltaic systems, while pioneering innovations in plastics recycling. His recent projects involve high-throughput plastic sorting techniques using molecular vibrational signatures and nanoscale defect optimization in superconducting wires. Advising & Industry: He co-founded TapeSolar Inc. and TexMat LLC, demonstrating expertise in venture capital engagement and technical project management. His RENEW Institute has attracted multidisciplinary collaborations across six schools at UB, advancing solutions for global sustainability challenges. Labs & Initiatives: Leads the NYS Center for Plastics Recycling & Innovation and oversees the UB Initiative on Plastics Recycling, integrating engineering, economics, and communication strategies to address plastic waste challenges.

• Biomedical Imaging
• X-ray Computed Tomography
• Spectral Detection
• +3 more

Prof. Julia Hearts is a Professor at the Technical University of Munich (TUM) , affiliated with the School of Natural Sciences . Her research focuses on biomedical imaging , particularly advancing X-ray computed tomography through phase-contrast and dark-field radiography for clinical and biological applications. Developing spectral detection techniques to enhance diagnostic accuracy Quantitative imaging for element-specific parameter extraction Utilizing synchrotron radiation and standard X-ray tubes Her recent publications demonstrate expertise in dark-field radiography for lung and breast imaging, phase-contrast tomography for tissue characterization, and multi-spectral X-ray analysis for material decomposition. Collaborative work spans oncology , pulmonology , and materials science . Contact: julia.herzen@tum.de

Payam BarnaghiView profile

Professor

• Machine Learning
• Neurosciences
• Healthcare Technology
• +6 more

Payam Barnaghi is a Professor and Chair in Machine Intelligence Applied to Medicine at Imperial College London's Department of Brain Sciences, part of the Faculty of Medicine. He holds multiple leadership roles, including Co-Director of the School of Convergence Science in Human and Artificial Intelligence and Deputy Head of Neurology. His research focuses on AI-driven healthcare solutions, particularly in neurosciences and dementia care. He leads the Translational Machine Intelligence group at the UK Dementia Research Institute (UK DRI) and is a Visiting Professor at University College London's Institute of Child Health. His affiliations include the NVIDIA Deep Learning Institute, the British Heart Foundation Centre for Research Excellence, and the UK DRI Care and Research Technology Centre. He has received awards such as the Wellcome Trust Mental Health Ideathon Award (2023) and the IEEE Outstanding Leadership Award (2017). His work emphasizes remote patient monitoring, digital biomarkers, and explainable AI for early health event detection. Key projects include the TIHM (Technology Integrated Health Management) initiative for dementia care, leveraging wearable sensors and machine learning. He contributes to interdisciplinary efforts in smart care ethics and has published extensively on topics like neural network applications, healthcare data analysis, and clinical decision support systems.

Robert M. WesterveltView profile

Professor

• Quantum Engineering
• Nanotechnology
• Biomedical Engineering
• +6 more

Robert M. Westervelt is the Mallinckrodt Professor of Applied Physics and Physics at Harvard University, holding dual appointments in the Department of Applied Physics and the Department of Physics. He directs the NSF Science and Technology Center for Integrated Quantum Materials and the Center for Nanoscale Systems. His research focuses on quantum materials, nanoelectronics, and biomedical microfluidics. Education: PhD in Physics from University of California, Berkeley (1977), followed by a postdoctoral appointment at Berkeley before joining Harvard. Research Interests: His work includes scanning probe microscopy of nanostructures, programmable microfluidic chips for cell manipulation, and quantum engineering using atomic-layer materials and topological insulators. Current projects aim to develop atomic-scale electronics and photonic devices using quantum materials like diamond nitrogen vacancy centers. Grants/Recognition: NSF grants support his quantum engineering and AI initiatives. The Center for Nanoscale Systems provides advanced nanofabrication facilities under his leadership. Labs/Teams: Directs the Westervelt Research Group and oversees shared facilities at the Center for Nanoscale Systems, fostering interdisciplinary collaboration in nanotechnology and quantum science.

• Optical Spectroscopy
• Biomedical Imaging
• Chemical Imaging
• +3 more

Chi (Jesse) Zhang is a Research Professor at Purdue University's Department of Chemistry, leading the Zhang Research Group. His work focuses on developing novel optical spectroscopy, imaging, and opto-control technologies to study chemical processes in living systems. He has pioneered techniques like Real-Time Precision Opto-Control (RPOC) and applies them to biomedical problems, including cancer metabolism and neurodegenerative diseases. His lab collaborates with institutions like Merck and has been recognized with awards such as the Astronaut Scholarship and Alice Watson Kramer Award. Education details are not explicitly provided, but his postdoctoral research at the Beckman Institute (2018–2020) indicates prior training in advanced scientific technology. His research integrates optical engineering with biological systems, emphasizing label-free imaging and real-time manipulation of cellular components. Key achievements include over 50 peer-reviewed publications and the development of the photokinesis technology platform (http://www.photokinesis.tech). His group hosts an active wet lab with projects ranging from lipid metabolism studies to optical device innovation. Recent milestones include successful student defenses, conference presentations, and impactful publications in ACS Photonics , Anal. Chem , and npj Imaging .

Tayfun GünelView profile

Professor

• Microwave Circuits
• Radar Systems
• Antennas
• +12 more

Tayfun Günel is a Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University (ITU) , Faculty of Electrical and Electronics Engineering. He holds a PhD (1993), MSc (1988), and BSc (1986), all from ITU. His research spans microwave circuits, radar systems, antennas, and optimization using genetic algorithms and soft computing. His research interests include Microwave Circuits , Radar and Antennas , Optimization , and Genetic Algorithms . His work focuses on impedance matching, microstrip antennas, noise modeling, and metamaterial-based microwave components. He has taught courses such as Electromagnetic Fields, Radar Systems, and Satellite Communication Systems. The recent publications reflect a strong trend in microwave circuit design , antenna miniaturization , and the application of evolutionary algorithms (genetic algorithms, PSO) and machine learning (neural networks, SVR) in electromagnetic design and optimization. There is a consistent focus on practical microwave components like transmission lines, patches, and amplifiers, often using nanomaterials (e.g., carbon nanotubes) and metamaterials . His work bridges theoretical modeling with computational optimization for real-world RF and radar applications. Email: gunelmur@itu.edu.tr Professor Günel has supervised 2 completed PhD theses, 2 ongoing PhD theses, 23 completed master's theses, and 1 ongoing master's thesis, demonstrating a significant contribution to student mentoring. There are no specific grants or funding sources mentioned in the provided text. He is affiliated with research in microwave systems and antenna design , likely operating within the broader research ecosystem of the Electronics and Communication Engineering Department at ITU, which includes labs such as the Microwave Systems and Antennas Laboratory and the Radar and Microwave Technologies Research Laboratory.

Keith DeckerView profile

Associate Professor

• Multi-Agent Systems
• Artificial Intelligence
• Distributed Artificial Intelligence
• +9 more

Keith Decker is an Associate Professor and JPMorgan Chase Fellow in the Department of Computer and Information Sciences at the University of Delaware's College of Engineering. He holds multiple affiliated faculty positions at the Artificial Intelligence Center of Excellence, Data Science Institute, Center for Bioinformatics and Computational Biology, and Institute for Financial Service Analytics. His research spans several key areas of computer science with a focus on Multi-Agent Systems , Distributed Artificial Intelligence , Computational Organization Design , and Bioinformatics . His work bridges theoretical foundations with practical applications in finance, healthcare, and information systems. Dr. Decker's publications reflect trends in distributed AI with emphasis on coordination technologies, agent communication, and information gathering systems. His work has evolved from foundational multi-agent coordination theory to applications in bioinformatics, financial services, and health informatics. DARPA special recognition award for foundational research in coordination technologies Dr. Decker has advised numerous graduate students and led significant research projects including automated genetic annotation, coalition management for electric vehicle-to-grid power systems, and machine learning for automated health coaching. His interdisciplinary work demonstrates strong connections between theoretical AI research and practical applications across multiple domains. He maintains active leadership roles in the academic community, having served as program co-chair for the International Conference on Autonomous Agents and Multi-Agent Systems and other major AI workshops.

• Biomedical Signal Processing
• Digital Health
• Machine Learning in Healthcare
• +3 more

Koushik Maharatna is a Professor in the Digital Health and Biomedical Engineering department at the University of Southampton. His research spans biomedical signal processing, digital health, and embedded systems, with a focus on neurological and cardiovascular disorders. Active in EU Horizon Europe and FP7 projects Member of the Institute for Life Sciences and Centre for Internet of Things and Pervasive Systems Specializes in EEG analysis, arrhythmia detection, and autism spectrum disorder diagnostics His recent publications highlight applications of phase-space reconstruction, machine learning, and wavelet transforms in medical diagnostics. Collaborations include researchers across Europe and Malaysia, with emphasis on interdisciplinary digital health solutions. Current research projects funded by UKRI, EPSRC, and European Union grants include PUREMIND and ETHEREAL, focusing on mental health prevention and energy-harvesting electronics. He supervises PhD students in Human Development & Health and Electronics & Electrical Engineering.

Yan HuangView profile

Associate Professor

• Machine Learning
• Cybersecurity Education
• Extended Reality (XR)
• +5 more

Yan Huang is an Associate Professor in the Department of Software Engineering and Game Development at Kennesaw State University (KSU). His work bridges Federated Learning (FL) and Cybersecurity Education , with a focus on personalization and privacy in distributed systems. Research spans Machine Learning , Extended Reality (XR) , and Data Privacy . He has served as Editor of WCMC and Program Co-Chair for CyberSciTech 2020-2024. Research Trends: Recent publications emphasize Federated Learning for non-IID data, VR-based Cybersecurity Education , and Privacy-Preserving Algorithms in IoT and social media analytics. Key subfields include personalized learning architectures, graph learning, and game-theoretic privacy frameworks. Scientific Awards: Excellent Paper Award (Tsinghua Science and Technology, 2021) Best Paper Award (Future Generation Computer Systems, 2019) Best Paper Awards at IEEE SmartWorld 2021, COCOA 2019, and WASA 2019 Grants: Led over $600,000 in NSF and NSA-funded projects, including VR cybersecurity education for K-12 and XR engineering curricula. His lab recruits VR/AR Research Assistants via industry partnerships.