جستجوی استاد راهنمای دانشگاهی

• Advanced Materials
• Composite Materials
• Smart Materials
• +۸ مورد دیگر

Prof. Raul Fangueiro is a Full Professor and Vice-Dean at the School of Engineering, University of Minho, Portugal. As a Senior Researcher, he leads FIBRENAMICS – Institute of Innovation on Fiber-Based Materials and Composites. His work spans advanced materials (nano, smart, composites) and structures (3D, auxetic, multiscale) with applications in defense, healthcare, construction, and automotive sectors. Supervised over 20 PhD and Post-Doc researchers Scientific coordinator of 20+ national/international research projects Author of 200+ journal papers (H-index: 47), 500+ conference publications, 36 books, 40 patents Research focuses on nanotechnology , electrospinning , and sustainable material systems : Auxetic composites for personal protection Biodegradable nanofibers for medical use Smart textiles for biological/chemical resistance Recycled mineral/wood-based composites Graphene-reinforced green materials Multiscale fiber architectures Scientific recognition includes: Top 2% most influential scientist (Elsevier/Stanford 2020) Founder of AUXDEFENSE and ICNF conferences Editorial board member of leading composite journals Advisor to European Defense Agency/NATO working groups Active in industry-academia partnerships through spin-offs (Sciencentris, B4Logic, Beyond Composites, Givaware, Pixartidea) and collaborative projects with institutions like Instituto Superior Técnico, University of Aveiro, and international universities.

Daniel Roxburyمشاهده پروفایل

دانشیار

• Nanoscience
• Carbon Nanotubes
• Nanomaterials
• +۴ مورد دیگر

Dr. Daniel Roxbury is an Associate Professor and Graduate Director at the Department of Chemical, Biomolecular and Materials Engineering within the University of Rhode Island's College of Engineering. With expertise in nanoscience and carbon nanomaterials, his research focuses on nano-bio interactions, developing functionalized nanotubes for biomedical applications and environmental monitoring through his NanoBio Engineering Laboratory. His work spans multiple disciplines including: Biomedical nanosensors Smart wearable biomaterials Targeted drug delivery systems Environmental nanotechnology Single-molecule imaging Nanotoxicology Recent publications emphasize machine learning-enhanced spectral analysis, coral reef conservation nanotechnology, and wearable stress monitoring textiles. His 2024 ACS Nano study introduces AI-driven macrophage phenotyping, while 2023 Nature Nanotechnology work explores coral reef restoration strategies using nanomaterials. Awarded the 2019 NSF CAREER grant for cellular nanometrology, he leads multiple NIH-funded projects including: $820,000 NSF CAREER: Spectral Imaging for Sub-Cellular Nanometrology $140,000 Miriam Hospital COBRE: Cortisol Detection Textiles $700,000 NSF EAGER: Multiplexed Wound Biomarker Detection His laboratory houses state-of-the-art equipment including: Near Infrared Hyperspectral Microscope Custom NIR Fluorescence Spectrometer Jasco UV/VIS/NIR Spectrophotometer Biosafety Cabinet Cell Culture Incubator Cryo-Storage System

Bruno Felisberto Martins Ribeiroمشاهده پروفایل

دانشیار

• Networking and Operating Systems
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Bruno Felisberto Martins Ribeiro is an Associate Professor of Computer Science at Purdue University, joining the department in Fall 2015. His research focuses on endowing machine learning algorithms with robust invariant representations for relational and temporal data, emphasizing causal and associational tasks. Key research areas include Networking and Operating Systems, Artificial Intelligence, Machine Learning, and Natural Language Processing. He holds a Ph.D. in Computer Science from the University of Massachusetts Amherst (2010). Education: Ph.D., Computer Science, University of Massachusetts Amherst, 2010 Research Interests: Explores invariances in mathematics and machine learning to improve model robustness. Key topics include graph and tensor invariances, causal relationships, adversarial robustness, and applications in recommendation systems, robotics, and drug discovery. His lab’s work has advanced counterfactual task frameworks and causal reasoning in machine learning. Recent Contributions: Recent publications address zero-shot generalization in graph neural networks, causal discovery methods, and defenses against adversarial attacks. His work spans conferences like ICML, NeurIPS, and SIGCOMM. Awards: Best Paper Award at ACM CODASPY 2021 Best Paper Award at SIGMETRICS 2016 Best Paper Award at IEEE NetSciCom 2014 Advising & Students: Supervises current PhD students Beatrice Bevilacqua, Jincheng Zhou, and Yucheng Zhang, along with MSc student Ipsit Mantri. Notable former students include S Chandra Mouli (Meta), Yangze Zhou (Spotify), and Jianfei Gao (Vector Institute). Labs & Teams: Leads research in invariant representations and causal ML, collaborating with institutions like Stanford during his sabbatical. His work bridges theory and practice, impacting areas like network analysis and AI-driven healthcare.

Arthur Schaferمشاهده پروفایل

استاد

• Professional Ethics
• Bioethics
• Applied Ethics
• +۸ مورد دیگر

Arthur Schafer is a Full Professor in the Department of Philosophy at the University of Manitoba's Faculty of Arts and Founding Director of the Centre for Professional and Applied Ethics. He serves as a National Research Associate of the Canadian Centre for Policy Alternatives and previously held roles as ethics consultant for the Winnipeg Regional Health Authority and Head of the Section of Bio-Medical Ethics in the Faculty of Medicine. His academic credentials include a BLitt in Philosophy from the University of Oxford (1967) and a BA Honours from the University of Manitoba. His distinguished career spans over five decades of ethical scholarship and public engagement. Professor Schafer specializes in professional and applied ethics with intensive focus on bioethics , research ethics , and biomedical conflicts of interest . His work critically examines medical assistance in dying , informed consent , clinical trial ethics , and human rights frameworks , establishing him as a leading voice in Canadian ethical discourse. His philosophical approach bridges theoretical rigor with practical policy applications across multiple professional domains. Analysis of his 13 most recent publications reveals enduring engagement with evolving ethical challenges, particularly the tension between institutional interests and professional integrity. His scholarship demonstrates consistent progression from foundational ethical theory toward contemporary policy applications, with recent work heavily concentrated on medical assistance in dying and pharmaceutical industry influence in healthcare systems. His scientific recognition includes: D. R. Campbell Outreach Award (1984) Olive Beatrice Stanton Award for Excellence in Teaching (1976) Canadian Commonwealth Scholarship (1964) Woodrow Wilson Fellowship (1964) Canada Council Fellow As an active supervisor for Master's and PhD students, Schafer extends his mentorship through ethics consulting for professional associations in Medicine, Engineering, Architecture, Nursing, and Pharmacy. His policy impact is evidenced by service on the Provincial-Territorial Expert Panel on Medical Assistance in Dying and two published reports for the Canadian Centre for Policy Alternatives. His extensive media contributions—including hundreds of CBC appearances and newspaper columns—demonstrate exceptional public scholarship. The Centre for Professional and Applied Ethics, which he founded, functions as a vital interdisciplinary hub connecting academic philosophy with real-world ethical challenges across healthcare, law, and public policy sectors, facilitating ongoing dialogue between scholars, practitioners, and community stakeholders.

Chao Wangمشاهده پروفایل

دانشیار

• CO2 Capture and Conversion
• Electrocatalysis
• Thermocatalysis
• +۳ مورد دیگر

Chao Wang is an Associate Professor at the Department of Chemical and Biomolecular Engineering within the Whiting School of Engineering at Johns Hopkins University. He also serves as the Director of the Nano Energy Laboratory and the department’s Master’s Admissions Director. His research focuses on sustainable energy systems and nanomaterials for CO2 capture and conversion, electrocatalysis, thermocatalysis, and green chemical engineering. Education: Bachelor’s degree, University of Science and Technology of China (2004) Doctorate, Brown University (2009) Wang’s research targets efficient energy conversion and storage via nanomaterials with tailored atomic structures, emphasizing catalytic activity, selectivity, and stability. His group explores electrochemical and thermochemical processes for reduced carbon footprints, including CO2 and methane conversion, ammonia recovery, and phosphorus/nitrogen nutrient recycling using zeolite-based systems. Recent publications (2021–2024) highlight his work in high-entropy alloys, solid-state battery materials, CO2 electroreduction, and biomedical nanotechnologies. Collaborative efforts span catalysis, nanoparticle dynamics, and environmental applications. Grants include a $1M DOE award for multi-university research, a $625K DOE grant for electrified transportation systems, and $3M in startup funding for carbon-removal technology commercialization. Alumni under his mentorship include Ph.D. graduates like Michael J. Manto (2018) and Master’s students like Mitchell Keller (2018), with notable achievements in catalyst development for ammonia/phosphorus recovery and industry placements at Grace & Co. and GEA Engineering.

Michael Baymمشاهده پروفایل

دانشیار

• Microbial Evolutionary Genomics
• Antibiotic Resistance
• Computational Biology
• +۷ مورد دیگر

Dr. Michael Baym is an Associate Professor of Biomedical Informatics at Harvard Medical School with affiliate appointments in Microbiology and the Laboratory of Systems Pharmacology, and as an Associate Member of the Broad Institute. He leads the Baym Lab, which studies microbial evolutionary genomics and antibiotic resistance through a hybrid of experimental, computational, and theoretical approaches. His research focuses on: Antibiotic Resistance Evolution and practical interventions Mobile Genetic Elements (plasmids, phages, transposons) Computational Genomic Algorithms for big data analysis Synthetic Biology tools and technologies Key recent publications explore phage discovery systems , phylogenetic compression of microbial genomes, and RNA-guided gene drives in plasmids. His work is supported by multiple NIH/NIGMS and NSF grants including a MIRA award. Scientific honors include: Packard Fellowship (2018) Pew Biomedical Scholarship (2020) Sloan Research Fellowship (2020) A. Clifford Barger Excellence in Mentoring Award (2021) SSQBio Mentorship Award (2022) The lab actively trains PhD students and postdoctoral fellows with alumni occupying academic and industry positions globally. Current team members include researchers from interdisciplinary backgrounds working at the intersection of experiment, computation, and theory .

• Quantum Computation
• Quantum Algorithms
• Computational Complexity
• +۳ مورد دیگر

Ashley M R Montanaro is a Professor of Quantum Computation at the School of Mathematics, University of Bristol . Active in quantum computing research since at least 2014, they lead projects at the intersection of quantum algorithms , computational complexity , and quantum information theory , affiliated with the Bristol Quantum Information Institute. Research interests focus on quantum algorithm design , computational complexity analysis , and quantum simulation . Key work includes developing variational quantum algorithms for phase transition detection, Hamiltonian simulation techniques, and quantum-classical hybrid methods for solving complex problems in physics and optimization. Recent publications demonstrate expertise in: Quantum phase diagram simulation with low-depth circuits Quantum speedups for constraint satisfaction problems Quantum communication complexity of machine learning tasks Quantum-enhanced optimization heuristics Hamiltonian simulation with time-dependent product formulas Quantum algorithm complexity analysis Scientific awards include: EPSRC Fellowship (2014-2019) - "New insights in quantum algorithms and complexity" Active in quantum software development through projects like: "Quantum Algorithms from Foundations to Applications" (ERC-2018-COG) "Quantum Computing and Simulation Hub" (2019-2024) "Prosperity Partnership in Quantum Software" (2019-2023)

Jeff Schoreyمشاهده پروفایل

استاد

• Microbiology
• Immunology
• Infectious Diseases
• +۹ مورد دیگر

Jeff Schorey is the George B. Craig Jr. Professor and a full Professor in the Department of Biological Sciences at the University of Notre Dame, where he has been a faculty member since 2004. He currently serves as Director of the Integrated Biomedical Sciences (IBMS) graduate program and previously held leadership roles including Chair of the Institutional Animal Care and Use Committee (IACUC) and Associate Director of the Eck Institute for Global Health. His research focuses on the pathobiology of mycobacterial diseases, particularly Mycobacterium tuberculosis and M. avium . His work investigates the molecular interactions between mycobacteria and host macrophages, with a special emphasis on the role of exosomes in immune modulation, diagnostics, and vaccine development. He also explores novel antibiotic development in collaboration with chemists at Notre Dame and global partners. His recent publications reveal a strong trend in extracellular vesicle biology, host-pathogen signaling, and translational applications in TB diagnostics and treatment. The articles span immunology, microbiology, and molecular biology, with recurring themes in exosome function, RNA sensing, and antimicrobial development. George B. Craig Jr. Collegiate Professor Dr. Schorey has advised graduate students and leads an active research lab focused on mycobacterial pathogenesis. His work is supported by collaborations across disciplines and institutions, particularly in drug development and clinical translation. He has contributed significantly to understanding how exosomes can serve as both biomarkers and therapeutic tools. His lab employs cellular immunology, animal models, and clinical sample analysis to study mycobacterial infections. He leads the IBMS program, shaping graduate education in biomedical sciences at Notre Dame.

Stephen Bachمشاهده پروفایل

استادیار

• Machine Learning
• Weak Supervision
• Probabilistic Soft Logic
• +۷ مورد دیگر

Stephen Bach is an Assistant Professor in the Computer Science Department at Brown University, where he leads the BATS (Bach's Awesome Team of Students) research group. His research focuses on improving how humans teach computers through programmatic weak supervision and methods for learning from fewer examples like zero-shot and few-shot learning. His primary research interests include weak supervision, data programming, probabilistic soft logic (PSL), statistical relational learning (SRL), information extraction, zero-shot learning, and few-shot learning. Bach's work often focuses on exploiting high-level, symbolic or semantically meaningful domain knowledge, with applications in information extraction, image understanding, scientific discovery, and data science. Bach's recent publications show a strong focus on language models, weak supervision techniques, and multimodal learning, particularly examining the capabilities and limitations of models like CLIP. His research has increasingly emphasized practical applications in low-resource settings and cross-lingual scenarios. Best Paper Award at NeurIPS Workshop on Socially Responsible Language Modelling Research (SoLaR) 2023 Larry S. Davis Doctoral Dissertation Award Selected for oral presentation at ICLR 2024 Best of VLDB 2018 paper selection Bach advises numerous Ph.D., Master's, and undergraduate students, many of whom have gone on to positions at leading tech companies, research institutions, and graduate programs. His research group has developed several influential frameworks including Snorkel (for weak supervision), PSL (Probabilistic Soft Logic), T0 (for zero-shot task generalization), ZSL-KG (for zero-shot learning with knowledge graphs), TAGLETS (for semi-supervised learning with auxiliary data), and WISER (for programmatic weak supervision in sequence tagging).

Matthias Barzمشاهده پروفایل

استاد

• Polymer Science
• Biotherapeutic Delivery
• Nanoparticle Synthesis
• +۷ مورد دیگر

Matthias Barz is a Professor of Biotherapeutic Delivery at the Leiden Academic Centre for Drug Research (LACDR) , Faculty of Science , Leiden University . He leads the Barz Lab , focusing on polymer science and biomedical applications of functional nanoparticles. Professor of Biotherapeutic Delivery (Leiden University) Head of the Division of BioTherapeutics Researcher in reactive polymer systems and nanocarrier design His research bridges polymer chemistry with biomedical applications, emphasizing polypept(o)ide-based nanocarriers for targeted drug delivery in cancer, inflammation, and neurodegenerative diseases. Key areas include: Stimuli-responsive polymer architectures Secondary structure-driven self-assembly Core-crosslinked micelles for controlled cargo release Redox-sensitive disulfide bonds for intracellular delivery Protein-repellent nanoparticle shells Riboflavin-functionalized nanocarriers for tumor targeting The lab's publications highlight advancements in polysarcosine-containing copolymers , orthogonal functional group utilization , and modular nanoparticle platforms with precise control over morphology and function. Current projects explore the clinical translation of these systems for immunotherapy and diagnostics. Scientific recognition includes: Dozentenpreis des Fonds der Chemischen Industrie (2018) PMSE Young Investigator Award (2018) Nachwuchswissenschaftlerstipendium der GDCh (2017) His team trains graduate students in polymer synthesis, nanoparticle characterization, and biomedical application testing. Collaborations span institutions like the University of Tokyo and Johannes Gutenberg University Mainz , with ongoing projects under the SFB 1066 initiative for malignant melanoma immunotherapy.

Jennifer Lewisمشاهده پروفایل

استاد

• Bioengineering
• Materials Science
• Soft Matter
• +۷ مورد دیگر

Jennifer Lewis is the Hansjorg Wyss Professor of Biologically Inspired Engineering and Jianming Yu Professor of Arts and Sciences at Harvard University's Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). Her research focuses on bioengineering, materials science, and advanced manufacturing, with emphasis on 3D-printed functional materials, organoids, and soft robotics. She leads the Lewis Research Group, which develops biomimetic technologies for regenerative medicine, energy systems, and robotics. Lewis holds appointments in SEAS, the Department of Chemistry and Chemical Biology, and the Wyss Institute for Biologically Inspired Engineering. Her research areas include applied mathematics, fluid mechanics, soft matter physics, and bioengineering applications such as kidney organoid models, vascularized tissues, and programmable materials. Notable innovations include kidney organoid-on-chip systems for drug testing, 3D-printed liquid crystal elastomers, and bioprinted cardiac tissues. Lewis was awarded the 2025 James Prize in Science and Technology Integration for pioneering interdisciplinary research. Her lab's projects span organ building blocks, immune-response modeling in transplanted tissues, and acoustophoretic printing techniques for high-resolution bioprinting. Collaborations include the NIH Somatic Cell Genome Editing Program and industry partnerships for bioprosthetic valve research. She advises on grants totaling over $20M and mentors a multidisciplinary team of postdocs and graduate students in materials science, biomedical engineering, and mechanical engineering. Lewis' lab facilities include the Pierce Hall lab (Cambridge) and Allston SEAS campus, with state-of-the-art 3D printing systems, microfluidics platforms, and bioreactors for organoid culture. Current projects aim to engineer functional human tissues for therapeutic applications and develop smart materials with programmable mechanical/chemical responses.

David N. Kuمشاهده پروفایل

استاد

• Bioengineering
• Biofluid Mechanics
• Medical Devices
• +۳ مورد دیگر

David N. Ku is the Lawrence P. Huang Endowed Chair for Engineering Entrepreneurship and Regents' Professor at Georgia Institute of Technology. He holds appointments in the School of Mechanical Engineering (Woodruff School) within the College of Engineering. His research focuses on biofluid mechanics, medical device innovation, and translational technology, with emphasis on thrombosis mechanisms and vascular diseases. Education: M.D. from Emory University (1984); Ph.D. and M.S. from Georgia Tech (1983, 1982); B.A. from Harvard University (1978). Research interests include unsteady fluid dynamics in vascular systems, nanoparticle medical devices for thrombosis prevention, and porous thrombus applications for hemostasis. His work bridges bioengineering with entrepreneurship, teaching product development at the Business School and collaborating with Emory University, Paris Tech-Mines, and ETH Zurich. Key awards include the American Institute for Medical and Biological Engineering Fellowship, DLA Piper Inventor of the Year, and NSF Presidential Young Investigator Award. His research is funded by NIH, NSF, and industry partners. Labs/Teams: Leads a lab using microfluidics and computational mechanics for vascular disease solutions. Collaborates on technologies to address post-partum hemorrhage and traumatic bleeding.

Thomas Winklerمشاهده پروفایل

دانشیار

• Microsystems Technology
• Organ-on-Chip
• Neuropsychiatric Disorders
• +۳ مورد دیگر

Thomas Winkler is an Associate Professor at the Division of Micro and Nanosystems, KTH Royal Institute of Technology, Sweden, and collaborates with TU Braunschweig, Germany. His research focuses on solving life science challenges using microsystems tools, particularly in neuropsychiatric disorders like schizophrenia. He develops organ-on-chip models, engineered microfluidic platforms, and biosensors for point-of-care diagnostics. Winkler leads an interdisciplinary ERC-funded team addressing metabolic coupling in neurovascular units and oxidative stress biomarkers. Key achievements include the ERC Starting Grant (2023) and work on electrochemical sensors for clozapine monitoring. He teaches courses such as Microsystem Technology (EK2350) and supervises PhD and postdoctoral researchers. Current projects include machine learning-guided robotic organoid maturation and electrochemical technology development for the CHIPzophrenia initiative. His lab actively seeks talent through open positions in Stockholm and Braunschweig. Scientific awards include the ERC Starting Grant and Marie Skłodowska-Curie Actions Fellowship. Research spans sensor development, microfabrication, and biomaterials, with a focus on translating lab technologies to clinical applications. Collaborations bridge engineering and life sciences, emphasizing personalized mental healthcare solutions.

Carla Vilelaمشاهده پروفایل

استادیار

• Sustainable Materials
• Cellulose Nanocomposites
• Biopolymers
• +۲ مورد دیگر

Dr. Carla Vilela is an Assistant Professor in the Department of Chemistry at the University of Aveiro and Principal Researcher at CICECO. She coordinates the Sustainable Materials research line and leads projects on cellulose-based materials and circular economy. Her research focuses on sustainable materials from cellulose and renewable resources for applications in water remediation, food packaging, and textiles. Education includes a PhD in Chemistry from the University of Aveiro and postdoctoral work at CICECO and ISIS Neutron and Muon Source (UK). Research interests include: Development of cellulose-based functional materials Nanocomposites for biomedical applications Sustainable packaging solutions Biopolymer modification and characterization Publications demonstrate strong focus on cellulose nanocomposites, bioprinting bioinks, and active packaging. Recent articles frequently involve nanocellulose modifications, drug delivery systems, and sustainable material design. Awards include being named among World's Top 2% Scientists annually since 2020. Funding includes national projects (Cell4Janus) and EU collaborations (PRIMA Im-Pack). Leads the BioPol4Fun research group and supervises 6 PhD students. Current projects explore cellulose-based microrobots, resin valorization, and marine biopolymers.

Pengtao Xieمشاهده پروفایل

دانشیار

• Machine Learning
• Natural Language Processing
• Machine Learning for Healthcare
• +۴ مورد دیگر

Pengtao Xie is an Associate Professor (tenured) in the Department of Electrical and Computer Engineering at UC San Diego, with cross-appointments in the Division of Biomedical Informatics and affiliations across multiple schools and institutes including the Halıcıoğlu Data Science Institute, School of Biological Sciences, and Skaggs School of Pharmacy. His research bridges human-inspired machine learning and healthcare applications. Education: PhD in Machine Learning, Carnegie Mellon University (2018) MS from Tsinghua University BS from Sichuan University Research Interests: His work focuses on machine learning inspired by human learning strategies , including learning by testing, interleaving, self-explanation, and teaching. These techniques are applied to large language models , foundation models , healthcare , and biomedicine . Recent efforts emphasize generative AI for medical image segmentation and protein function prediction. Scientific Awards: NIH MIRA Award (2025) NSF Career Award (2024) Best Graduate Teacher Award, ECE UCSD (2023) ICLR Notable-Top-5% Paper (2023) Global Top-100 Chinese Young Scholars in AI (2022) Tencent Faculty Award (2021) AMIA Doctoral Dissertation Award Finalist (2020) Siebel Scholarship (2014) Teaching & Mentorship: He has developed and taught courses such as Deep Generative Models , Probabilistic Graphical Models , and Linear Algebra and Applications . He actively mentors PhD, master's, and undergraduate students, with alumni now at CMU, Stanford, Mila, and industry roles. Labs & Teams: He leads a research group within the Center for Machine-Intelligence, Computing and Security and collaborates with the Institute for Genomic Medicine and Institute of Engineering in Medicine at UC San Diego.