جستجوی استاد راهنمای دانشگاهی

Huiyan Liمشاهده پروفایل

دانشیار

• Biosensors
• Lab-on-a-chip Technologies
• Cancer Diagnostics
• +۴ مورد دیگر

Huiyan Li, PhD, P.Eng., is an Associate Professor in the Department of Biomedical Engineering at the University of Guelph. Her research focuses on developing micro/nanoscale biosensors and lab-on-a-chip technologies for cancer diagnostics and personalized medicine. Dr. Li holds a Ph.D. in Biomedical Engineering from McGill University and completed postdoctoral training at Harvard Medical School/Massachusetts General Hospital. Her multidisciplinary research integrates biosensing, micro/nanofabrication, bio-optics/electronics, and computational tools to study cancer molecular complexity. Current openings exist for M.A.Sc. students interested in biosensing research. Key research areas include extracellular vesicle analysis, multiplexed immunoassays, magnetic/nanoparticle-enhanced bioassays, and graphene-based biomedical sensors. Recent work emphasizes point-of-care diagnostics and enhanced protein detection via novel material integration. Teaching responsibilities include ENGG 6301 (Advanced Micro/Nano Biotechnology) and undergraduate courses in bio-instrumentation and biomedical signal processing. Her work spans biomaterials classification, microfluidic systems, and antimicrobial nanocomposite development. Research outputs emphasize scalable microarray formats, EV-based biomarker discovery, and sensor sensitivity enhancement through nanomaterial innovations. Current projects address EV concentration measurement, 3D antibody microarrays, and magnetic-responsive hydrogel discs for bioassay improvements.

Stephan Staudacherمشاهده پروفایل

استاد

• Aircraft Propulsion
• Gas Turbine Engineering
• Thermodynamics
• +۳ مورد دیگر

Prof. Dr.-Ing. Stephan Staudacher is the Director of the Institute of Aircraft Propulsion at the University of Stuttgart. His work focuses on aircraft propulsion systems, gas turbine performance, and turbomachinery design. He holds a professorship in the Faculty of Mechanical Engineering and Aerospace, leading research in advanced engine technologies, erosion effects, and fault detection algorithms. Research interests include engine reliability, computational fluid dynamics (CFD), and experimental validation of propulsion systems. His publications emphasize topics like neural network applications for fault detection, ice crystal icing simulations, and particle transport in additive manufacturing processes. Recent studies highlight the optimization of composite-cycle engines and assessment of mission severity caused by erosion. Key contributions include advancements in engine condition monitoring, transient performance analysis, and the development of Stuttgart University’s Altitude Test Facility (ATF). His work bridges theoretical models with industrial applications, addressing challenges in both civil and military aviation propulsion systems.

Inseok Hwangمشاهده پروفایل

استاد

• Hybrid Systems
• Nonlinear Systems
• Unmanned Aircraft/Spacecraft Control
• +۵ مورد دیگر

Inseok Hwang is the Paul Stanley Professor of Aeronautics and Astronautics at Purdue University's School of Aeronautics and Astronautics. He earned his Ph.D. from Stanford University, specializing in multiple-vehicle control systems. His research focuses on hybrid systems, air traffic control, unmanned systems, and cybersecurity of cyber-physical systems. He leads the Flight Dynamics and Control/Hybrid Systems Laboratory and has received numerous awards, including the NSF CAREER Award and AIAA Associate Fellow designation. His work spans theoretical advancements in control theory and practical applications in aerospace systems. He has over 150 peer-reviewed publications and actively collaborates with industry and government agencies like NASA and the FAA. Education: B.S. (Seoul National University, 1992), M.S. (KAIST, 1994), Ph.D. (Stanford, 2004). Professional memberships include AIAA and IEEE. Research Interests: Hybrid systems analysis, air traffic surveillance and control, fault detection and isolation, spacecraft control, and cybersecurity for autonomous systems. His lab develops algorithms for safe and efficient operation of networked systems, including UAS traffic management and resilient control protocols against cyberattacks. Awards: NSF CAREER (2008), AIAA Associate Fellow (2012), University Faculty Scholar (2017), C.T. Sun Award (2019), multiple Seed for Success Awards (2020–2024), and Paul Stanley Professorship (2024). Grants and Collaborations: Active projects funded by NSF, NASA, FAA, and industry partners. Focus areas include resilient navigation, anomaly detection in air traffic systems, and cyberattack mitigation for autonomous vehicles.

Maxim Sinitsynمشاهده پروفایل

دانشیار

• Product Pricing
• Price Promotions
• Technology Licensing
• +۳ مورد دیگر

Maxim Sinitsyn is an Associate Professor of Instruction in the Department of Economics at Northwestern University, where he has held his PhD since 2005. His research focuses on product pricing strategies, particularly examining price promotions, coordination of promotions for related products, and the impact of technology licensing mechanisms on market outcomes. He has explored topics such as prescheduled sales, anti-stacking royalty clauses, and the effects of horizontal mergers in promotional contexts. Education: PhD in Economics from Northwestern University (2005). Research Interests: Dr. Sinitsyn's work concentrates on strategic pricing, including how firms optimize promotions for complementary products, the role of advance planning in promotional strategies, and the implications of different licensing payment structures for market dynamics. His studies also extend to broader economic phenomena such as price dispersion in duopolies and governance trade-offs in institutional design. Advising/Grants: No specific advising or grant information is listed in the provided texts. His contributions are primarily through research publications and teaching. Labs/Teams: No affiliated labs or research teams are mentioned.

• Machine Learning & Artificial Intelligence
• Probabilistic Modelling
• Neuro-Symbolic Modelling
• +۷ مورد دیگر

Dr. Robert Lieck is an Assistant Professor in the Department of Computer Science at Durham University. His research focuses on interdisciplinary applications of machine learning (ML) and artificial intelligence (AI), emphasizing interpretability, robustness, and ethical considerations. He explores computational models in music cognition, communication dynamics, and medical image analysis, aiming to bridge theory and practical tools for domain experts. Before Durham, he was a postdoctoral researcher at EPFL's Digital and Cognitive Musicology Lab (2018–2021) and earned his PhD from the Learning and Intelligent Systems Lab in Stuttgart/Berlin (2012–2017). His work combines probabilistic modelling, neuro-symbolic systems, and reinforcement learning to address challenges in music analysis, autonomous decision-making, and medical robotics. Key research themes include: Music structure and perception modelling Symbol emergence in multi-agent communication Ethical AI and autonomous systems governance Medical imaging applications (CT/MRI analysis) Recent projects involve developing patient-agnostic diabetes management systems using deep reinforcement learning and surgical workflow anticipation through graph learning algorithms. He actively contributes to conferences such as NeurIPS, ISMIR, and AAAI, with publications spanning music informatics, robotics, and biomedical engineering. Current supervision includes four postgraduate students focusing on AI applications in healthcare, music technology, and autonomous systems. His work bridges technical innovation with societal impact, addressing challenges in policy, legislation, and interdisciplinary collaboration.

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +۵ مورد دیگر

João F. Mano is a Full Professor at the Department of Chemistry, University of Aveiro, and Director of the Doctoral Program on Biotechnology. He leads the COMPASS Research Group and serves as Vice-Director at CICECO - Aveiro Institute of Materials. His academic appointments include Invited Professor at University of Lorraine (France), Visiting Professor at KAIST (South Korea), and Adjunct Professor at Ajou University (South Korea). Education: PhD in Chemistry (1996, Technical University of Lisbon); D.Sc. in Tissue Engineering, Regenerative Medicine and Stem Cells (2012, University of Minho) Research Interests focus on Biomaterials for Regenerative Medicine , integrating Nanotechnology , Microtechnology , and Biofabrication . His group develops Bioinspired Materials using polymer chemistry, Decellularized Extracellular Matrix , and 3D Bioprinting to engineer Cell Microenvironments for therapeutic applications. Recent Publications highlight advancements in Human-Derived Hydrogels , Photopolymerizable Scaffolds , Magneto-Responsive Biomaterials , and Programmable Bioinks . Trends show emphasis on Organ-on-a-Chip integration, Smart Living Materials , and Green Bioprinting methodologies. Scientific Awards include: European Research Council Advanced Grants (2015, 2020) Fellow at IUPAC, European Academy of Sciences, and American Institute of Medical and Biological Engineering ERC Proof of Concept Grants Doctor Honoris Causa from University of Lorraine and Utrecht UNESCO Chair on Biomaterials George Winter Award (European Society for Biomaterials) Supervisions & Collaborations encompass 74+ MSc, 26+ PhD students, and 40+ postdocs. He co-founded METATISSUE and CELLULARIS Biomodels , and serves as Editor-in-Chief of Materials Today Bio .

Forest Agostinelliمشاهده پروفایل

استادیار

• Deep Learning
• Reinforcement Learning
• Search Algorithms
• +۷ مورد دیگر

Forest Agostinelli is an Assistant Professor in the Department of Computer Science and Engineering at the Molinaroli College of Engineering and Computing, University of South Carolina, where he is also affiliated with the AI Institute. His research focuses on designing AI algorithms for pathfinding problems, integrating deep learning, reinforcement learning, heuristic search, and formal logic. He holds a Ph.D. in Computer Science from the University of California, Irvine, an M.S. from the University of Michigan, and a B.S. in Electrical and Computer Engineering from The Ohio State University. Research Overview : Agostinelli’s work emphasizes solving pathfinding problems in domains like robotics, theorem proving, and molecular optimization. His group develops explainable AI methods to enable collaboration between humans and machines. Key projects include DeepCubeA (solving the Rubik’s Cube via deep reinforcement learning) and neural activation function research. Funding & Awards : He has secured grants from NSF, NASA EPSCoR, and South Carolina’s ASPIRE and MADE programs. Notable awards include the NSF Graduate Research Fellowship and the Graduate Education for Minority Students Fellowship. Teaching : He teaches courses in Artificial Intelligence (CSCE 580) and Deep Reinforcement Learning and Search (CSCE 790), mentoring over 15 students at undergraduate and graduate levels. Labs & Collaborations : Active in AI-driven education and interdisciplinary projects, his lab contributes to tools like ALLURE for children’s learning and Bioinformatics platforms like CircadiOmics.

Daria Camilla Boffitoمشاهده پروفایل

استاد

• Process Intensification
• Catalysis
• Photocatalysis
• +۱۱ مورد دیگر

Daria Camilla Boffito is a Full Professor in the Department of Chemical Engineering at Polytechnique Montréal , holding the Tier-2 Canada Research Chair in Intensified Mechano-chemical Processes for Sustainable Biomass Conversion. Her research spans process intensification , catalysis , sonochemistry , photocatalysis , and metal extraction , with a focus on sustainability. Education: B.Sc. and Ph.D. in Industrial Chemistry from the University of Milan, M.Sc. in Industrial Chemistry and Management Current Research: Developing ultrasound-assisted extraction , CO2 conversion , and floating photocatalysts for wastewater treatment Collaborations: Works with Canadian and international companies on sustainable chemical processes Scientific Awards include the Canada Research Chair Tier-2 (2016-2021), NSERC Banting Postdoctoral Fellowship (2013-2016), and FRQNT PBEEE Postdoctoral Fellowship (2013-2016). Advising has seen 5 Ph.D. and 9 Master's students graduate. She leads the Engineering Process Intensification and Catalysis (EPIC) Laboratory and is a member of the Institut de génie biomédical .

Christopher Piechمشاهده پروفایل

استادیار

• Computer Science Education
• Educational Data Science
• Artificial Intelligence in Education
• +۳ مورد دیگر

Christopher Piech is an Assistant Professor (Teaching) in the Department of Computer Science at Stanford University, with a courtesy appointment in the Graduate School of Education. He serves as a Faculty Affiliate at the Institute for Human-Centered Artificial Intelligence (HAI) and is affiliated with the Symbolic Systems Program. Current courses: AI for Social Good (CS 21SI), Introduction to Probability for Computer Scientists (CS 109), Researching Presenting and Publishing Work in AI & Education (CS 220/EDUC 481) Advises 11 Master's students and co-advises 3 Doctoral students His research focuses on computational education, leveraging artificial intelligence to enhance learning analytics, student collaboration detection, and knowledge tracing in programming education. Publications span ACM Technical Symposium on Computer Science Education (SIGCSE) and NeurIPS conferences. Key article trends include: (1) AI-driven educational tools for code analysis, (2) collaboration monitoring in large classes, and (3) probabilistic models for student learning trajectories.

Harish Krishnanمشاهده پروفایل

استاد

• Supply Chain Management
• Operations Research
• Business Strategy
• +۳ مورد دیگر

Harish Krishnan is a Professor in the Operations and Logistics Division at the UBC Sauder School of Business. He holds degrees from Delhi, Alabama, Michigan (MA and PhD). His research focuses on incentive distortions in supply chains, contracts for supply chain coordination, and broader supply chain management strategies. He teaches courses such as Process Fundamentals and Supply Chain Management in the 2024-2025 academic year. Education: BEng from Delhi MS from University of Alabama MA from University of Michigan PhD from University of Michigan Research Interests: Incentive distortions in supply chains Contracts and supply chain coordination Supply chain management with a focus on sustainability and operational risk Recent Work Trends: Blockchain applications in sustainable global value chains Climate policy analysis, particularly international carbon mitigation frameworks Strategic collaboration between competitors in operational contexts Affiliations: Member of the Entrepreneurship and Innovation Group Part of the Operations and Logistics Division leadership

Danial Chitnisمشاهده پروفایل

مدرس

• Microelectronics
• Biomedical Engineering
• Quantum Technology
• +۳ مورد دیگر

Dr. Danial Chitnis is a Chancellor's Fellow and Lecturer in Electronics at the School of Engineering, University of Edinburgh. He holds a DPhil in Engineering Science from the University of Oxford (2013) and has expertise in microelectronics, biomedical engineering, and quantum imaging. His research focuses on SPAD arrays, time-of-flight sensors, and wearable optical systems for biomedical applications. Education: BSc in Electronics Engineering, Chamran University of Ahvaz (2002–2007) MSc in Advanced Microelectronics Systems Engineering, University of Bristol (2007–2008) DPhil in Engineering Science, University of Oxford (2009–2013) Research Interests: Single-Photon Avalanche Diode (SPAD) arrays for optical communications and biomedical imaging Quantum-enhanced imaging via QuantIC Hub Wearable sensors for near-infrared spectroscopy (NIRS) AI-driven automation in test and measurement systems Articles Trends: Recent work emphasizes AI integration in electronics design, photon-counting receivers for 6G networks, and portable biomedical devices. Notable contributions include SYCL-based acceleration of circuit simulations and FPGA-driven time-to-digital converters. Grants & Collaborations: Principal Investigator of multiple grants, including EPSRC-funded projects on AI-enhanced human-machine interfaces and quantum technology applications. Collaborates with UCL, QuantIC, and industry partners like Keysight Technologies. Labs/Teams: Co-investigator at QuantIC, the UK Quantum Technology Hub in Quantum Enhanced Imaging. Leads interdisciplinary research on detector arrays and systems for quantum physics and consumer cameras.

• Computer Vision
• 3D Reconstruction
• Unsupervised Learning
• +۳ مورد دیگر

Iro Laina is a Departmental Lecturer in Computer Vision at the University of Oxford's Visual Geometry Group. She holds a PhD (Dr. rer. nat.) from the Technical University of Munich (TUM), where her dissertation earned the ECVA PhD Award. Her research focuses on unsupervised and language-supervised learning for 3D scene understanding, image/video perception systems, and geometric reconstruction. Education: PhD in Computer Science (TUM), MSc in Biomedical Computing (TUM), Diploma in Electrical & Computer Engineering (NTUA). Research Interests: 3D Reconstruction and Generation Unsupervised Learning Multi-View and Video Analysis Generative Diffusion Models Geometry-Aware Networks Her recent work emphasizes scalable 3D scene synthesis, training-free methods, and cross-modal fusion with LLMs. Over 15+ publications since 2021 reflect her leadership in geometric deep learning. Awards: ECVA PhD Award (2020), Recognized in multiple international conferences. Advising: Mentors DPhil students in creative AI applications (e.g., gameplay design). Active in Oxford's Robotics and Biomedical Engineering networks. Labs/Tech: Core member of the Visual Geometry Group, collaborating on projects like IMAD2025 with the ZERO Institute.

• Decarbonization of Built Environments
• Bio-Based Materials Engineering
• Structural Systems Optimization
• +۳ مورد دیگر

Dr. Bhavna Sharma is an Associate Professor and Director of the Chase L. Leavitt Master of Building Science Program at the USC School of Architecture. Her work focuses on decarbonization, bio-based materials innovation, and sustainable healthcare infrastructure. She leads the Keck USC Sustainable Healthcare Initiative (KUSHI) to advance environmentally conscious healthcare systems. Dr. Sharma holds a Ph.D. in Civil and Environmental Engineering from the University of Pittsburgh, with additional degrees in Art History and Architecture. Her research spans structural systems optimization from material harvesting to building-scale applications, emphasizing bio-composites like bamboo and timber. She co-chairs USC's Presidential Working Group on Sustainability, contributing to Assignment: Earth climate goals. Courses taught include seismic design, structural systems, and building science integration. Key research areas include lifecycle assessment in healthcare, seismic-resistant designs, and interdisciplinary standards for non-conventional materials. Her work bridges material science, architectural practice, and policy to address global sustainability challenges.

G. Kane Jenningsمشاهده پروفایل

استاد

• Smart Surfaces
• Biohybrid Materials
• Solar Energy Conversion
• +۵ مورد دیگر

G. Kane Jennings is a Professor of Chemical and Biomolecular Engineering at Vanderbilt University's School of Engineering, where he also serves as Director of Graduate Recruiting. His research focuses on molecular design of smart surfaces and biohybrid materials for applications in solar energy conversion, responsive coatings, and nanoscale lubrication. He leads the Jennings Lab, training students in bioinspired materials science. Jennings holds a Ph.D. from MIT and specializes in self-assembly techniques and surface-initiated polymerizations. Education: Ph.D., Chemical Engineering, Massachusetts Institute of Technology M.S., Chemical Engineering, Massachusetts Institute of Technology B.S., Chemical Engineering, Auburn University Research Interests: Jennings develops adaptive materials such as anionic chameleon coatings, biohybrid solar systems using Photosystem I proteins, and high-throughput membrane fabrication via spin coating-ROP integration. His group explores nanoscale defect detection in 3D-printed materials and corrosion-resistant surface treatments. Lab Innovations: Highlights include the mMSIP micromolding technique for customizable superhydrophobic coatings and the scROMP method enabling rapid polymer film synthesis. Collaborations with civil engineering and chemistry departments advance energy-minimizing surfaces and bioelectrochemical systems. Awards: No explicit awards listed, though his work has been funded through interdisciplinary initiatives at Vanderbilt's VINSE and Process Innovation Center.

Brendan Dolan-Gavittمشاهده پروفایل

دانشیار

• Cybersecurity
• Program Analysis
• Virtualization Security
• +۵ مورد دیگر

Brendan Dolan-Gavitt is an Associate Professor in the Computer Science and Engineering Department at NYU Tandon School of Engineering and part of the NYU Center for Cybersecurity (CCS). He holds a Ph.D. in Computer Science from Georgia Tech (2014) and a BA in Math and Computer Science from Wesleyan University (2006). His research spans cybersecurity, program analysis, virtualization security, memory forensics, and embedded/cyber-physical systems, focusing on automating the understanding of large software systems to develop novel defenses. Research interests include developing techniques for static and dynamic analyses of real-world software to reveal hidden design assumptions. His work has been presented at top security conferences like USENIX Security, ACM CCS, and IEEE Security & Privacy. He led the development of the open-source PANDA platform for dynamic analysis. His publications primarily focus on AI-driven security solutions, vulnerability discovery, and automated testing tools. Recent work explores LLMs in offensive security, fuzzing enhancements, and secure code generation, emphasizing practical applications in cybersecurity. Scientific Awards: NSF CAREER Award for improving software vulnerability testing and education He leads the OSIRIS Lab, a student-run cybersecurity group, and collaborates on interdisciplinary projects addressing emerging security challenges through grants and industry partnerships.