جست‌وجوی استاد و پژوهشگر

• Closed-loop neurotechnology
• Neuromodulation
• Machine learning
• +۴ مورد دیگر

Dr. Eric Meyers is an Assistant Professor in the Department of Bioengineering at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. He holds a Ph.D. in Biomedical Engineering and dual Bachelor's/Master's degrees in Electrical Engineering from the same institution. His research focuses on closed-loop neurotechnology, neuromodulation, and bioelectronic medicine to enhance recovery from nervous system injuries. Key projects include developing wearable EMG sleeves for stroke rehabilitation and closed-loop neuromodulation systems to restore motor function. Education: B.S. (2012), M.S. (2018), Electrical Engineering; Ph.D. (2017), Biomedical Engineering – all from UTD His research interests span machine learning applications in neurorehabilitation, biomarker discovery for neurological conditions, and clinical translation of bioelectronic therapies. Recent work emphasizes wearable devices for real-time motor function assessment and neuromodulation-driven recovery strategies. Publications highlight advancements in EMG-based neural interfaces, closed-loop algorithms for stroke therapy, and innovative FES systems. His lab actively collaborates on projects funded by NIH and industry partnerships, with a focus on translating technologies to clinical settings.

Erik Schemeمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Machine Learning
• Neuroprosthetics
• +۵ مورد دیگر

Erik Scheme is an Associate Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick (UNB), and serves as Associate Director of the Institute of Biomedical Engineering (IBME). He holds a PhD and is a Professional Engineer (PEng). His roles include advising the Dr. J. Herbert Smith Centre for Technology Management and Entrepreneurship, emphasizing innovation in biomedical technologies and healthcare systems. His research focuses on advanced human-machine interaction through biomedical engineering, with a strong emphasis on myoelectric prosthetics, wearable sensors, and machine learning applications. Key areas include improving neuroprosthetic control via incremental learning, gait analysis using underfoot pressure sensors, and developing robust EMG-based gesture recognition systems. His work bridges clinical needs with technological innovation, addressing challenges in rehabilitation, activity monitoring, and user-centric design. Recent publications highlight advancements in adaptive control systems, sensor fusion, and ethical data practices in healthcare. His contributions span both theoretical frameworks (e.g., self-supervised learning models) and applied technologies (e.g., gold-plated 3D-printed electrodes). Dr. Scheme collaborates across disciplines, integrating robotics, signal processing, and clinical validation to create impactful solutions. His lab, affiliated with IBME, actively explores emerging areas like exhaled breath analysis for disease detection and federated learning in healthcare data analytics.

Mohammad Samie Tootooniمشاهده پروفایل

استادیار

• Health Informatics
• Artificial Intelligence in Healthcare
• Predictive Analytics
• +۵ مورد دیگر

Mohammad Samie Tootooni is an Assistant Professor in the Department of Health Informatics and Data Science at Loyola University Chicago, with a secondary appointment in the Center for Health Outcomes and Informatics Research. He holds a PhD in Industrial and Systems Engineering from Binghamton University (2016) and completed a postdoctoral fellowship at Mayo Clinic's Department of Health Sciences Research (2016-2018). His research focuses on applying artificial intelligence, machine learning, and systems engineering principles to improve healthcare outcomes. Core areas include clinical decision support systems, predictive analytics for complex healthcare systems, and natural language processing (NLP). He also explores quality assurance, optimization, and systems thinking to address challenges in healthcare delivery and patient care. Recent work emphasizes AI-driven solutions for medication management in ICUs, ECG-based disease prediction (e.g., coronary heart disease, preeclampsia), and addressing therapeutic inertia in hypertension treatment. His methodologies combine machine learning with clinical data analysis to bridge gaps between engineering and medical practice. Teaching responsibilities include courses on health informatics ontologies and NLP applications in healthcare. His interdisciplinary collaborations span clinicians, data scientists, and engineers to tackle real-world healthcare problems.

Paul Leonardمشاهده پروفایل

دانشیار

• Biomolecular Interaction Analysis
• Single-Cell Analysis
• Biologics Discovery
• +۶ مورد دیگر

Assoc. Prof. Paul Leonard is an Associate Professor in Biotherapeutics at Dublin City University (DCU), leading the Biomedical Innovation Group (BIG) within the School of Biotechnology. His research focuses on biomolecular interaction analysis, single-cell technologies, and biologics discovery, addressing challenges in oncology, cardiovascular disease, and infectious disease diagnostics. He has 20+ years of academic and industry experience, co-founding Remedy Biologics Ltd and securing over €15M in funding. His entrepreneurial roles include CSO/CTO, Lean Six Sigma process improvements, and advisory work for life sciences companies. Research interests span high-throughput antibody discovery, immunoassay development, and environmental sensing. He collaborates with academia and industry, including projects like AquaBioSens for aquatic pollutant detection. His lab employs multidisciplinary teams and holds patents in biotechnology. Paul also serves as an external examiner for Technical University Dublin’s Biomedical Diagnostics program. Key achievements include technology spin-outs, patent filings, and leadership in EU-funded projects. His work bridges academic innovation with commercial applications, emphasizing rapid diagnostic tools and therapeutic advancements.

Paola Calzaمشاهده پروفایل

استاد

• Environmental Chemistry
• Analytical Chemistry
• Photocatalysis
• +۳ مورد دیگر

Paola Calza is a Full Professor in the Department of Chemistry at the University of Turin. Her research focuses on environmental chemistry, analytical chemistry, and advanced photocatalytic technologies for water purification. Her work addresses the degradation of emerging contaminants, transformation product analysis, and the development of novel materials for pollutant removal. She has contributed significantly to advancing photocatalysis, nanomaterial synthesis, and sustainable water treatment strategies. Her research spans diverse applications, including aquaculture water treatment, pharmaceutical pollution mitigation, and soil bioremediation. Key areas: Photocatalytic degradation, MXene-based nanocomposites, HPLC-HRMS analysis, and bio-inspired materials. Collaborations involve interdisciplinary approaches combining environmental science, materials engineering, and analytical techniques. Publications emphasize practical solutions for real-world water and soil contamination challenges.

Yang Chengمشاهده پروفایل

دانشیار

• Supply Chain Management
• Manufacturing Strategy
• Manufacturing Network
• +۵ مورد دیگر

Yang Cheng is an Associate Professor at the Department of Materials and Production, Aalborg University, Denmark. He holds a PhD in Mechanical Engineering from the same institution (2011), focusing on manufacturing strategy and network dynamics. His research spans supply chain management, sustainability, and global operations, with a focus on integrating technology and environmental policies into manufacturing systems. He leads or participates in high-impact projects like MAASive (2024–2026) and the Sino-Danish Center Research Project (2011–present), addressing resilience in value networks and global operations innovation. Research Interests: Supply Chain Management & Integration Sustainability & Green Technologies Manufacturing Strategy & Networks Technology Policy & Digitalization Global Operations & Cross-Border Collaboration Recent Work Trends: Prof. Cheng's 2025 articles emphasize blockchain in sustainable supply chains, green technology investments under carbon policies, and digitalization's ethical implications. His 2024 research explores smart factories, EU battery regulations, and robotization in manufacturing. These studies blend quantitative models with case-based analysis to address real-world challenges. Awards: 2024 Emerald Literati Awards – Outstanding Reviewer Advising & Grants: As PI for multiple Global Operations Management PhD programs (2019–2025), he guides research on digital transformation and university-industry collaboration. His projects receive funding from Danish and international grants, focusing on innovation and resilience in manufacturing networks. Labs/Teams: Collaborates with the Center for Industrial Production at Aalborg University and engages in international partnerships through the Sino-Danish Center. Active editorial roles include Production Planning & Control and Journal of Manufacturing Technology Management .

Possu Huangمشاهده پروفایل

استادیار

• Protein Design
• Computational Biology
• Structural Biology
• +۴ مورد دیگر

Possu Huang serves as Assistant Professor of Bioengineering in the Department of Bioengineering at Stanford University's School of Engineering. His research group operates from the Shriram Center for Bioengineering, sharing laboratory space with the Bintu Lab while maintaining an active interdisciplinary program bridging computational and experimental protein engineering. His educational journey includes: B.A. in Molecular and Cell Biology (Biochemistry) from UC Berkeley Ph.D. in Biochemistry and Molecular Biophysics from Caltech Postdoctoral training as Senior Fellow at University of Washington Dr. Huang's research focuses on atomic-precision protein design through integrated computational-experimental approaches. His lab has pioneered breakthroughs including the first computationally designed protein-protein interface, TIM barrel fold design principles, and the eOD HIV immunogen. Current work leverages machine learning , structural biology , and library optimization to develop therapeutic proteins and nanotechnology platforms, with particular emphasis on achieving natural-level complexity in engineered systems. Analysis of his 2023-2025 publications reveals three dominant trends: (1) generative AI for all-atom protein design (e.g., Protpardelle, SHAPES), (2) immunology applications targeting MHC complexes for HIV vaccine development, and (3) optogenetic tools through engineered fluorescent proteins. These works consistently integrate deep learning with wet-lab validation to solve biomedical challenges. Dr. Huang has mentored nine graduate students to completion, including PhD candidates Carla (defended June 2025), Christian (defended May 2025), and master's students Shankara and Kirsten. His lab maintains active social media presence (@possuhuanglab) and regularly publishes high-impact research while training the next generation of protein engineers. The Huang Lab operates as a dynamic interdisciplinary hub where computational biologists collaborate with experimentalists to push the boundaries of protein design. Current projects include developing tetravalent nanobody platforms, photoswitchable binders for temporal protein control, and AI-driven solutions for HIV immunogen design, all conducted within Stanford's state-of-the-art bioengineering facilities.

Jeremy Baumbergمشاهده پروفایل

استاد

• Nanoscience
• Nanotechnology
• Nanophotonics
• +۶ مورد دیگر

Jeremy Baumberg is a Professor at the Cavendish Laboratory, University of Cambridge, leading research in nanoscience and nanotechnology. He specializes in designing nano-materials with unique optical properties, including plasmonic cavities and polymer opals, with applications in catalysis, sensing, and energy. His work bridges academia and industry through collaborations with Hitachi, IBM, and his spin-offs Mesophotonics and Base4. Research interests focus on light-matter interaction in nanoscale systems, quantum plasmonics, surface-enhanced Raman spectroscopy (SERS), and nanocavity engineering. Recent projects include developing plasmonic nanogap reactors, high-energy-density battery materials, and the open-source WaterScope platform for water quality monitoring. Awards : Faraday Medal (2017) Rumford Medal (2014) Young Medal (2013) Royal Society Fellowship (2011) Mullard Prize (2005) His lab, the Ray Dolby Centre, explores optomechanical systems, plasmonic sensors, and nanostructured materials. Baumberg advises ARIA and serves on the EPSRC Council, emphasizing interdisciplinary innovation and scalable nanotechnology solutions.

Philippe Dixonمشاهده پروفایل

استادیار

• Biomechanics
• Neuroscience
• Machine Learning
• +۳ مورد دیگر

Dr. Philippe Dixon is an Assistant Professor in the Department of Kinesiology & Physical Education at McGill University, with a division in Biomechanics and Neuroscience. He holds adjunct professor roles at the University of Montreal (School of Kinesiology and Physical Activity Sciences) and the University of Laval (Department of Kinesiology). His research focuses on human movement biomechanics using motion capture systems and wearable sensors, combined with machine learning for health and athletic performance optimization. He has expertise in gait analysis, muscle coactivation patterns in cerebral palsy, and predictive modeling of physiological states. Dr. Dixon earned a Post-doctoral fellowship in Public Health at Harvard University, a PhD in Engineering Science from the University of Oxford, and dual degrees in Biomechanics and Physics from McGill University. His education includes a Bachelor of Education in Mathematics and Physics (McGill), a Master of Science in Biomechanics (McGill), and a PhD in Engineering Science (Oxford). He has received grants such as the NSERC Discovery Grant (2022–2027) and the FRQSC AUDACE Grant (2022). His work emphasizes wearable sensor integration, with contributions to datasets like NACOB and tools like OpenOFM. He currently supervises Master’s and PhD students in biomechanics and machine learning applications. Key research themes include gait adaptations on uneven surfaces, machine learning for cough detection via smart garments, and musculoskeletal coordination in clinical populations. His articles span biomechanical modeling, wearable sensor validation, and neuro-musculoskeletal analysis, reflecting interdisciplinary innovation in human movement science.

Alexander Budzierمشاهده پروفایل

پژوهشگر ارشد

• Project Management
• IT-enabled Change
• Risk Management
• +۵ مورد دیگر

Alexander Budzier is a Research Fellow in the Department of Technology and Operations Management at Saïd Business School, University of Oxford. He specializes in managing projects across IT, infrastructure, energy, and mega-events, with a focus on risk mitigation and systems thinking. His roles include teaching on the MSc for Major Programme Management, MBA, and the Major Project Leadership Academy. Education: PhD from Saïd Business School (2014). Prior experience includes roles at T-Mobile International and McKinsey's Business Technology Office in Düsseldorf and Chicago, advising on IT and operations strategy. Research interests center on IT-enabled change, project setups, and risk analysis. Notable contributions include work on cost overruns in IT projects, the uniqueness trap in project management, and sustainable development via mega-events like the Olympics. Publications span journals like Harvard Business Review , iScience , and Event Management , with a focus on megaprojects, risk, and digital transformation. He has advised governments and corporations on infrastructure investments and project governance, emphasizing evidence-based decision-making.

• Ultra-low power systems
• Microelectronics
• Integrated Circuits
• +۱۱ مورد دیگر

Professor Aniruddha Desai is a Research Professor and Director of the Centre for Technology Infusion (CTI) at La Trobe University. He holds a Bachelor’s in Industrial Electronics, a Master’s in Micro-electronics, and a PhD in Computer Science. His expertise spans microelectronics, AI, IoT, and sensor networks, with a focus on socially impactful applications like transportation, healthcare, and precision agriculture. Research Interests: Ultra-low power systems Micro-nano electronics AI/ML and edge computing IoT and sensor networks Transportation and logistics Major Projects: Led multi-million-dollar R&D programs in areas such as smart cities, energy management, and smart farming. Notable collaborations include the IIT Kanpur - La Trobe University Research Academy and the Asian Smart Cities Research and Innovation Network. Awards: Recipient of the 2016 Vice-Chancellor’s Award for Research Excellence and the 2020 Victorian Tall Poppy Award for Science. Served on advisory panels for the Australian Research Council and provided expert testimony in parliamentary inquiries. Labs/Teams: Directs the CTI, which delivers technology-based innovations to industry and government. Co-founded the Asian Smart Cities network to advance urban technology solutions.

Ediz Cetinمشاهده پروفایل

دانشیار

• Radio Frequency Interference Detection
• Fault-Tolerant Reconfigurable Circuits
• Machine Learning Applications
• +۴ مورد دیگر

Ediz Cetin is an Associate Professor in Digital Electronics Engineering at Macquarie University's School of Engineering and a member of the Astrophysics and Space Technologies Research Centre. He serves as Course Director for the MEng Electronics Engineering program and Chair of the School's Postgraduate Coursework Committee. His research focuses on radio frequency interference mitigation, fault-tolerant reconfigurable circuits for space applications, machine learning in RF signal analysis, and low-power digital circuit design. Education: PhD in Signal Processing (Unsupervised Adaptive Signal Processing Techniques for Wireless Receivers) B.Eng. (Hons.) in Control and Computer Engineering Research Interests: RF interference detection and localization GNSS anti-jamming and spoofing detection FPGA-based reconfigurable systems Space instrumentation and CubeSat technologies Machine learning for signal processing Awards: Excellence in Learning Innovation (FSE Teaching Award, 2022) Highly Commended Finalist – Vice-Chancellor’s Award for Learning Innovation (2022) Innovative Approaches – Highly Commended (FSE Teaching Award, 2020) Key Projects: SmartSat CRC (2020–2026): Smart Satellite Technologies and Analytics Spacecraft Innovation Lab (2021–2022) CubeSat Biological Payload (2019–2022) Teaching Contributions: Led the 'Improving Student Engagement with Anywhere and Any-time Laboratory Access' initiative (2019–2020), enhancing remote lab accessibility for students.

Lisa Giegمشاهده پروفایل

استاد

• Petroleum Microbiology
• Anaerobic Biodegradation
• Microbial Corrosion
• +۲ مورد دیگر

Lisa Gieg is a Professor in the Department of Biological Sciences at the University of Calgary, where she leads research in environmental microbiology. She holds a B.S. in Microbiology from the University of Alberta (1991) and Ph.D. in Microbiology from the same institution (1996). Her laboratory investigates microbial processes in energy environments, focusing on anaerobic hydrocarbon biodegradation pathways and applications in bioremediation and energy recovery. Dr. Gieg's research examines how anaerobic microorganisms metabolize hydrocarbons and related compounds in contaminated environments and natural reservoirs. Her work elucidates novel biodegradation pathways under sulfate-reducing and methanogenic conditions through cultivation, analytical chemistry, and molecular biology approaches. Current applications include anaerobic bioremediation, enhanced methane recovery from marginal oilfields, biocorrosion mitigation, paraffin treatment, heavy oil recovery, oil sands tailings reclamation, and souring control. Her recent publications demonstrate advances in understanding microbiologically influenced corrosion mechanisms, naphthenic acid biodegradation, piezophile microbiology, and enzyme biotechnology for oilfield applications. This research bridges fundamental microbial ecology with practical solutions for energy industry challenges. Gieg teaches Microbial Physiology (CMMB 443) and Petroleum Microbiology (CMMB 545), training students in environmental microbiology concepts and techniques.

Hyejin Kuمشاهده پروفایل

استاد

• Mathematical Finance
• Machine Learning
• Risk Management
• +۴ مورد دیگر

Hyejin Ku is a Full Professor in the Department of Mathematics and Statistics at York University's Faculty of Science. Her research focuses on the intersection of Mathematical Finance and Machine Learning, addressing challenges in risk measurement, portfolio optimization, and quantitative finance. She develops advanced mathematical models to enhance decision-making through reinforcement learning and data analytics. Notable projects include novel algorithms for credit rating prediction using neural networks and sequence-based clustering for credit risk assessment. Her work integrates applied mathematics with real-world financial applications, such as systemic risk reduction in multi-layer networks and option pricing under liquidity constraints. She holds a prominent position in mathematical finance, contributing to both theoretical advancements and practical solutions for financial markets. Her research trends emphasize interdisciplinary approaches, combining machine learning techniques with financial modeling to solve complex problems in risk management and asset valuation. Her publications span over two decades, showcasing contributions to portfolio optimization, derivatives pricing, and computational finance. Dr. Ku is affiliated with York University’s Department of Mathematics and Statistics, where she contributes to academic leadership and research mentorship. Her office is located in DB 2025, and she can be reached at hku@yorku.ca.

Amir Asadiمشاهده پروفایل

دانشیار

• Scalable Manufacturing
• Multifunctional Composites
• Additive Manufacturing
• +۵ مورد دیگر

Amir Asadi is an Associate Professor in the Department of Engineering Technology and Industrial Distribution at Texas A&M University, holding the Corrie & Jim Furber '64 Faculty Fellow position. His research focuses on scalable manufacturing of multifunctional composites, structural energy systems, and advanced materials design. He leads the Polymer Composites Advanced Manufacturing (PCAM) Lab, which explores bottom-up fabrication techniques and additive manufacturing processes. Asadi holds a Ph.D. in Mechanical and Manufacturing Engineering from the University of Manitoba (2013), an M.S. in Mechanical Engineering from Iran University of Science & Technology (2006), and a B.S. in Mechanical Engineering from the same institution (2004). His work bridges molecular-level interactions with macroscale material performance, targeting applications in aerospace, e-mobility, and energy storage. Key research interests include structural battery/supercapacitor composites, additive manufacturing of polymer composites, and fast-rate manufacturing of thermoplastics. He has pioneered methods like supercritical CO₂-assisted atomization and cellulose nanocrystal-enabled interface tailoring to enhance composite performance. Asadi has received the NSF CAREER Award (2022) and has been an invited speaker at major conferences such as the Brazilian Conference on Composite Materials (2021) and Chalmers University’s “Materials for Tomorrow” event (2020). His lab’s innovations aim to revolutionize lightweight, multifunctional materials for industrial sectors. His research outputs include over 50 peer-reviewed articles, covering topics from nanocomposite interfaces to 3D-printed structural batteries. He collaborates with industry partners like the Air Force Research Lab and focuses on translating lab-scale innovations into scalable manufacturing solutions.