جست‌وجوی استاد و پژوهشگر

Minh Q. Phanمشاهده پروفایل

دانشیار

• System Identification
• Control Theory
• Robotics
• +۴ مورد دیگر

Minh Q. Phan is an Associate Professor of Engineering at Dartmouth College's Thayer School of Engineering. His expertise spans system identification, iterative learning control, model predictive control, robotic swarm control, and intelligent control systems. He holds a BS from the University of California, Berkeley, and MS/M.Phil/PhD degrees from Columbia University in Mechanical Engineering. Dr. Phan has contributed to over 50 peer-reviewed publications and serves as an Associate Editor for the Journal of Guidance, Control, and Dynamics. His research focuses on advancing control theory applications in robotics, structural health monitoring, and sustainable construction materials. Key contributions include the development of OKID (Observer/Kalman Filter Identification) methods and bilinear system identification frameworks. Education History: Bachelor of Science in Mechanical Engineering, UC Berkeley, 1985 Master of Science in Mechanical Engineering, Columbia University, 1986 Master of Philosophy in Mechanical Engineering, Columbia University, 1988 Doctor of Philosophy in Mechanical Engineering, Columbia University, 1989 Research Interests: Advanced control methodologies for dynamic systems Model-based predictive control strategies Applications in robotics and aerospace engineering Structural health monitoring via system identification Machine learning for materials science Teaching Responsibilities include courses like ENGG 149 (Systems Identification), ENGS 145 (Modern Control Theory), and ENGG 148 (Structural Mechanics). His work bridges theoretical control systems with practical industrial applications, including automation in food processing and sustainable construction practices. Dr. Phan has collaborated on projects addressing viral epidemiology in Vietnam and coastal erosion mitigation strategies.

• Environmental Health Engineering
• Wastewater-Based Epidemiology
• Bioremediation
• +۷ مورد دیگر

Rolf Halden is a Professor and Center Director at Arizona State University, holding appointments in the School of Sustainable Engineering and the Built Environment, the Biodesign Center for Environmental Health Engineering, and the Global Futures Scientists and Scholars program. He is a leading expert in environmental health engineering, wastewater-based epidemiology, and bioremediation. Education: Ph.D. in Civil (Environmental) Engineering, University of Minnesota (1997) M.S. in Civil (Environmental) Engineering, University of Minnesota (1994) M.S. in Biology, Technical University of Braunschweig, Germany (1992) Postdoctoral Fellow, Environmental Science, Lawrence Livermore National Laboratory (1998) Research Focus: Halden’s research integrates environmental chemistry, public health, and sustainability to understand how anthropogenic chemicals affect ecological and human health. His lab uses advanced mass spectrometry (LC-MS/MS, MALDI-TOF) to track pollutants such as PPCPs, microplastics, pesticides, and dioxins across air, water, soil, and biological systems. He pioneered the use of wastewater treatment plants as public health observatories, enabling real-time tracking of disease, drug use, and environmental exposures. Scientific Awards & Recognition: Leadership Award, Arizona State University (2018) Rocky Mountain Emmy Award (2018) Leroy E. Burney Lecturer, Johns Hopkins School of Public Health (2011) ACS Expert Program Member (2014–present) NIEHS Superfund R01 Working Group National Leader (2012–2014) Labs & Teams: Halden is the Founding Director of the Biodesign Center for Environmental Health Engineering at ASU, where he leads a multidisciplinary team focused on environmental proteomics, bioremediation, and diagnostic tool development. He also co-leads the Human Health Observatory , a national wastewater monitoring network. Grants & Funding: Halden has secured major funding from NSF, NIH, EPA, DoD, and private industry. Notable projects include the development of in-situ groundwater monitoring devices, national wastewater surveillance of SARS-CoV-2, and studies on microplastics and neurodegenerative disease.

Sarah Billingtonمشاهده پروفایل

استاد

• Sustainable Building Design
• Human Wellbeing in Built Environments
• Affordable Housing
• +۳ مورد دیگر

Sarah Billington is the UPS Foundation Professor of Civil and Environmental Engineering at Stanford University and a Senior Fellow at the Woods Institute for the Environment. Her research program focuses on sustainable building design, human wellbeing, and ethical supply chain practices. Education: PhD, University of Texas at Austin, Structural Engineering (1997) MSE, University of Texas at Austin, Structural Engineering (1994) BSE, Princeton University, Civil Engineering & Operations Research (1990) Her lab employs interdisciplinary methods to study how built environments impact human physical, psychological, and social wellbeing. Current projects include developing tools to quantify nature exposure in buildings, exploring affordable housing's role in wellbeing, and using AI to assess forced labor risks in material supply chains. While no longer active in this area, her group previously pioneered research on sustainable construction materials like bio-based composites and ductile cement-based composites. Her recent publications address topics such as nature integration in architecture, workplace design optimization, and health impacts of building materials. The Billington Lab at Stanford fosters collaborative team science, welcoming partnerships to advance occupant-centric engineering solutions.

• Mechanical Engineering
• Autonomous Vehicles
• Artificial Intelligence
• +۳ مورد دیگر

Professor Mohammad FARD is a faculty member at RMIT University's School of Engineering, specializing in Mechanical Engineering and Intelligent Systems. He leads research in autonomous vehicles, crash safety, and driver monitoring using AI. His industry experience includes six years at Nissan Technical Centre, focusing on vehicle body design. He holds a PhD from Tohoku University and has collaborated across Engineering, Health, and Science disciplines, achieving international media coverage for work on driver drowsiness and road safety. Research Interests: Autonomous Vehicles Advanced Crash Safety Driver State Monitoring AI in Noise/Vibration Human Factors/Ergonomics Teaching & Projects: Teaches Advanced CAE, Vehicle NVH, and research supervision in areas like crash simulation and vibration control. Current projects include Formula One safety barriers and driver education for autonomous vehicles. Awards & Labs: No awards listed. Active in cross-disciplinary teams and labs addressing automotive innovation and safety.

Catherine Laiمشاهده پروفایل

دانشیار

• Speech and Language Processing
• Computational Linguistics
• Prosody
• +۱۷ مورد دیگر

Catherine Lai is a Reader (~Associate Professor) in the Department of Linguistics and English Language at the University of Edinburgh, with strong affiliations to the Centre for Speech Technology Research (CSTR) and the Institute for Language, Cognition and Computation (ILCC) in the School of Informatics. She is based in the School of Philosophy, Psychology and Language Sciences and is actively involved in research, teaching, and academic service. Department: Department of Linguistics and English Language School: School of Philosophy, Psychology and Language Sciences Research Institutes: Centre for Speech Technology Research, Institute for Language, Cognition and Computation Email: C.Lai@ed.ac.uk Her research centers on the role of prosody—non-lexical aspects of speech—in spoken communication. She investigates how prosody contributes to discourse structure, information structure, and affect in dialogue, using interdisciplinary methods from linguistics and machine learning. Her work bridges theoretical linguistics and practical speech technology, aiming to improve spoken language understanding and synthesis systems. She is particularly interested in how prosody shapes listener expectations and how affect and topic are expressed and perceived in conversation. Her recent publications reflect a strong focus on self-supervised learning in speech models, emotion recognition, ASR error correction using large language models, cognitive state classification, and ethical considerations in language technology. She explores topics such as the uncanny valley in synthetic speech, gender expression through voice, and community-centered development of language technologies. Prize from Scopus Profile Catherine Lai has supervised several PhD students, including Leimin Tian and Yuanchao Li, and has been involved in significant research projects, such as a Toyota-funded initiative on spoken dialogue for robot companions. She has secured multiple grants and leads a research agenda that integrates theoretical inquiry with real-world applications in assistive technologies and social science. Her academic service includes organizing major conferences like Interspeech and UK and Ireland Speech. She is a key member of research teams at CSTR and ILCC, collaborating across disciplines to advance the understanding of spoken communication and the development of robust, ethical speech technologies.

Vesna Terzicمشاهده پروفایل

استاد

• Seismic Performance Assessment
• Infrastructure Resilience
• Structural Dynamics
• +۲ مورد دیگر

Vesna Terzic is a Professor in the Department of Civil Engineering and Construction Engineering Management at California State University Long Beach's College of Engineering. Her research specializes in seismic performance assessment, infrastructure resilience, and probabilistic risk analysis of structures. Education includes a PhD in Structural Engineering from UC Berkeley, MS in Earthquake Engineering from Ss. Cyril and Methodius University, and BS in Structural Engineering from University of Belgrade. Research focuses on developing advanced computational frameworks for evaluating post-earthquake functionality of buildings and bridges. Her work integrates performance-based engineering with resilience quantification, emphasizing practical applications for seismic design and retrofitting. Recent publications demonstrate consistent focus on functional recovery modeling, structural health monitoring, and optimization of protective systems. Research trends show progression from component-level analysis to regional recovery simulation frameworks. Major awards: ACI Chester Paul Siess Award for Excellence in Structural Research (2017) Popert Fellowship, UC Berkeley (2009) Professional service includes membership on FEMA P-58 project committees and contributions to OpenSees development. Current projects investigate soil-structure interaction effects on tall buildings and recovery-based design methodologies.

Martin T. Wellsمشاهده پروفایل

استاد

• Applied Statistics
• Theoretical Statistics
• Bayesian Statistics
• +۷ مورد دیگر

Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.

Srijan Kumarمشاهده پروفایل

استادیار

• Data Science
• Applied Machine Learning
• Network Analysis
• +۷ مورد دیگر

Srijan Kumar is an Assistant Professor in the School of Computational Science and Engineering at Georgia Institute of Technology's College of Computing. His research focuses on data science, AI for security, and online safety, addressing challenges in detecting malicious users, misinformation, and enhancing AI robustness. His work has been deployed in platforms like Flipkart and Wikipedia, and recognized through awards such as the NSF CAREER and Forbes 30 Under 30. Education: B.Tech from Indian Institute of Technology, Kharagpur Ph.D. in Computer Science from University of Maryland, College Park Postdoctoral training at Stanford University Research Interests: Multi-modal/multi-lingual detection of harmful content and users Adversarial robustness of AI models Graph and network analysis for early detection Responsible recommender systems Awards & Grants: NSF CAREER Award (2023) Kavli Fellow (2022) Facebook/Adobe Faculty Awards NSF Convergence Accelerator Phase II grant ($5M) Advising & Labs: Leads the CLAWS Lab, advising over 20 students. Active in mentoring through conferences and NSF-funded projects.

Mario Bergesمشاهده پروفایل

دانشیار

• Smart Infrastructure
• Structural Health Monitoring
• Non-Intrusive Load Monitoring (NILM)
• +۴ مورد دیگر

Mario Berges is an Associate Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Electrical and Computer Engineering. He holds leadership roles as Co-Director of the IBM Smart Infrastructure Analytics Lab and Director of the Intelligent Infrastructure Research Lab (INFERLab). His work focuses on applying information/communication technologies to enhance the operational efficiency and resilience of built environments amid evolving resource constraints and climate changes. Education: PhD in Civil & Environmental Engineering from CMU (2010). Research Interests: Berges' research integrates smart infrastructure systems, energy efficiency, and machine learning. Key areas include non-intrusive load monitoring (NILM), structural health monitoring of pipelines, building automation systems, and urban heat risk modeling. He develops data-driven frameworks for energy disaggregation, sensor placement optimization, and real-time infrastructure diagnostics. Awards: Recognized with the 2010 FIATECH Outstanding Early Career Researcher Award and 2015 Dean’s Early Career Fellowship from CMU. Grants & Labs: Leads INFERLab, collaborating with IBM on smart infrastructure projects. His work spans academic-industry partnerships focused on building analytics, smart grid technologies, and sensor networks. Future Directions: Expanding research into AI-driven energy systems, resilient urban infrastructure, and cross-disciplinary solutions for climate adaptation.

Liang Chengمشاهده پروفایل

استاد

• Cyber-Physical Systems (CPS)
• Internet of Things (IoT)
• AI/ML Applications
• +۷ مورد دیگر

Dr. Liang Cheng is the Department Chair and Professor in the Department of Electrical Engineering and Computer Science at the University of Toledo. He leads a department with ~700 students across CS, CSE, and EE programs. His research focuses on Cyber-Physical Systems (CPS), IoT, AI/ML, and intelligent infrastructure, supported by over $30M in funding from NSF, DOE, DOT, and industry. Notable projects include CPS Breakthrough initiatives and underground sensing systems. He co-edited a multidisciplinary book on Underground Sensing and contributed to smart grid cybersecurity. Dr. Cheng has held leadership roles at Lehigh University, shaping faculty governance and equity policies. His 100+ publications span networking, real-time systems, and sensor networks. He advises on funded projects totaling $30M+ and has pioneered pedagogical approaches in computer science education. Research Interests: Cyber-Physical Systems (CPS): Focuses on autonomous drones, energy systems, and real-time infrastructure Networking: Expertise in TSN, DTN, and wireless protocols Cybersecurity: SCADA systems, PLC attack detection, and blockchain energy modeling Underground Sensing: Geo-sensing via wireless signals and subsurface tomography Grants & Projects: Over 20 sponsored projects including NSF CPS Breakthrough (2018-2023), ABB smart grid projects, and DARPA-funded EDIFY systems. Key contributions include reconfigurable wireless architectures and network calculus tools for real-time systems. Teaching: Courses span senior design, compiler design, parallel computing, and wireless sensor networks. Developed pedagogical patterns for non-CS programming education. Awards: Recognized for leadership in academic governance and interdisciplinary research collaboration.

Raffaello D'Andreaمشاهده پروفایل

استاد

• Robotics
• Control Systems
• Aerospace Engineering
• +۵ مورد دیگر

Prof. Raffaello D'Andrea is a Full Professor at ETH Zürich's Department of Mechanical and Process Engineering, affiliated with the Institute for Dynamic Systems and Control. His research focuses on bridging digital and physical worlds through robotics, control systems, and autonomous systems. He has pioneered work in aerial robotics, swarm systems, tactile sensing, and soft robotics. His philosophy emphasizes solving 'easy' problems with scalable, robust solutions, prioritizing simplicity and replicability. Key research areas include UAV navigation, distributed control, tactile sensor design, and fault-tolerant systems. He has founded multiple organizations and led roles as CTO/CEO, emphasizing cross-disciplinary innovation. His work has commercial applications in logistics, healthcare, and automation, driven by a belief in technology's role in improving human life. Notable projects include the Cubli robotic cube, aerial vehicle swarms, and optical tactile sensors for robotics. His lab emphasizes collaboration and team leadership, aiming to translate theoretical insights into practical, scalable technologies. Scientific awards: None explicitly listed in the provided texts. Advising and grants: No students listed in the provided texts; grants information not detailed. Labs/Teams: Leads research at ETH Zurich's Institute for Dynamic Systems and Control, collaborating with industry and academic partners globally.

Supratik Guhaمشاهده پروفایل

استاد

• Quantum Computing
• Semiconductor Materials
• Sensor Networks
• +۴ مورد دیگر

Supratik Guha is a Professor at the Pritzker School of Molecular Engineering and Senior Advisor to Argonne National Laboratory's Physical Sciences and Engineering directorate. His work bridges industrial R&D with academic and national lab research, focusing on quantum computing , semiconductor materials , and sensor networks for water and soil monitoring. Guha leads Argonne’s quantum information science strategy and serves as Faculty Director for the University of Chicago Center in Delhi. Education: PhD in Materials Science (USC, 1991), BTech in Engineering Physics (IIT Kharagpur, 1985) Research interests span multiple domains: Quantum technologies focusing on erbium-doped oxides for quantum memory and quantum interconnects Sensor networks for soil and water quality monitoring using cyberphysical systems Nanofabrication techniques including controlled spalling for heterogeneous material integration Advanced memory technologies exploring ferroelectric and optically addressable memory at atomic scales Scientific awards include: Election to National Academy of Engineering (2015) APS Prize for Industrial Applications of Physics (2015) Vannevar Bush Faculty Fellow (2018) Fellow of Materials Research Society and American Physical Society IBM Corporate Award (2013) Advising notable students like Manish Kumar Singh (co-founder memQ ), Cheng Ji (now at Intel), and Vamsi Nittala (now at Micron Technology). His group contributes to major DOE , NSF , and USDA funded projects including: Q-NEXT - DOE National Quantum Information Center AIFARMS - NSF/USDA AI for Agriculture Institute Thoreau Project - Geospatial sensor networks Labs and teams operate across University of Chicago and Argonne National Lab , with facilities for molecular beam epitaxy , nanofabrication , and optical/electrical characterization . The group has spawned startups like memQ (quantum networking) and K1 Semiconductors (wide-bandgap material transfer).

• Mechanical Engineering
• Additive Manufacturing
• 3D-Printing
• +۲ مورد دیگر

Jouni Partanen is a Professor at Aalto University's Department of Energy and Mechanical Engineering within the College of Engineering. His research focuses on advanced production technologies including Additive Manufacturing (3D-Printing), modern laser processing, and micromachining. Research Group: Materiaaleista tuotteiksi Specialization: Integration of AI in manufacturing processes Sustainability emphasis: Biochar-reinforced materials and carbon footprint reduction His work spans from fundamental material behavior analysis to industrial applications, particularly in metal additive manufacturing and composite fabrication. Recent research explores corrosion resistance in lattice structures and multiscale photopolymerization techniques. Publications highlight interdisciplinary approaches combining mechanical engineering with biomedical applications (e.g., patient-specific implants) and environmental health studies on industrial 3D printing emissions.

Michael McAlpineمشاهده پروفایل

استاد

• 3D Printing
• Nanotechnology
• Biomedical Engineering
• +۴ مورد دیگر

Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award

Ankit Saxenaمشاهده پروفایل

استادیار

• Adaptive materials and structures
• Meta-materials
• Additive manufacturing
• +۴ مورد دیگر

Ankit Saxena serves as Assistant Professor in the Department of Mechanical Engineering at the University of Wyoming since 2024, focusing on innovative applications of additive manufacturing in structural engineering and materials science. His work bridges theoretical design with practical implementations in energy, aerospace, and robotics systems. Education: Ph.D. in Mechanical Engineering, Penn State University (2024) M.S. in Mechanical Engineering, Penn State University (2020) B.S. in Mechanical and Automotive Engineering, Delhi Technological University (2016) Dr. Saxena's research centers on developing adaptive stiffness structures , meta-materials , and functionally graded systems through advanced additive manufacturing techniques. His work specifically targets energy applications (nuclear, wind, hydrogen, oil/gas) and aerospace challenges, with emphasis on structural health monitoring and vibration damping. The SUMMIT Lab under his direction creates multi-functional materials enabling shape morphing and self-strengthening properties for next-generation engineering solutions. His publication record (2020-2024) reveals a consistent trajectory toward multi-physics meta-material design , with dominant themes in TPMS lattice optimization, fluid-structure interaction systems, and medical robotics applications. Key methodological contributions include novel fluid accumulator integration, laser powder bed fusion parameterization, and non-pneumatic tire architectures. Scientific Recognition: ASME Graduate Teaching Fellow (2022-2024) Harold F. Martin Graduate Assistant Outstanding Teaching Assistant Award (Penn State, 2023) Dr. Saxena teaches core materials courses (ME 3450: Properties of Materials; ME 4150: Mechanical Behavior of Materials) while expanding his research group through active recruitment of PhD candidates for 2026. His teaching philosophy emphasizes practical applications of theoretical concepts, recognized through multiple Penn State teaching fellowships. The SUMMIT Lab operates at the intersection of Wyoming's energy priorities and cutting-edge manufacturing research, maintaining strategic focus on renewable energy infrastructure and aerospace applications through metal additive manufacturing innovations.