جست‌وجوی استاد و پژوهشگر

Albert S. Berahasمشاهده پروفایل

استادیار

• Nonlinear Optimization
• Machine Learning Optimization
• Stochastic Optimization
• +۵ مورد دیگر

Albert S. Berahas is an Assistant Professor in the Department of Industrial and Operations Engineering at the University of Michigan's College of Engineering. He joined the university in 2020 after completing postdoctoral positions at Lehigh University (2018-2020) and Northwestern University (2018). He holds a PhD in Engineering Sciences and Applied Mathematics from Northwestern University (2018), an MS in Applied Mathematics from Northwestern (2012), and a BSE in Operations Research and Industrial Engineering from Cornell University (2009). His research focuses on designing, developing, analyzing, and implementing algorithms for solving large-scale nonlinear optimization problems. His work spans multiple sub-fields including constrained optimization, optimization for machine learning, stochastic optimization, derivative-free optimization, and decentralized optimization. He is affiliated with the Michigan Institute for Data Science (MIDAS), the Michigan Institute for Computational Discovery and Engineering (MICDE), and the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM). Berahas has received numerous honors including the Charles Broyden Prize (2025), the Air Force Office of Scientific Research Young Investigator Program award (2025), the IISE Operations Research Division Teaching Award (2024), and the North Campus Dean's MLK Spirit Award for Community Building & Impact (2024). His recent publications demonstrate strong activity in developing novel optimization frameworks with theoretical guarantees for challenging problem settings. His research has been supported by significant grants including from the Office of Naval Research (ONR) and the Air Force Office of Scientific Research. He actively mentors PhD students and has successfully advised Jiahao Shi, who defended his dissertation in March 2025 and joined Amazon. Berahas is also engaged in community outreach, particularly through initiatives like Engage Detroit that aim to empower Detroit's next generation of engineers.

Mary-Louise Timmermansمشاهده پروفایل

استاد

• Arctic climate
• Physical oceanography
• Arctic Ocean heat storage
• +۶ مورد دیگر

Mary-Louise Timmermans serves as the Damon Wells Professor of Earth and Planetary Sciences and Director of Graduate Studies at Yale University's Faculty of Arts and Sciences. Her research focuses on Arctic climate dynamics and physical oceanography, where she has established herself as a leading expert in Arctic Ocean processes. Dr. Timmermans' research interests center on Arctic climate systems, particularly physical oceanography of the Arctic Ocean, heat and freshwater storage and transport mechanisms, ocean mixing processes, and eddy and wave dynamics. Her work examines how these processes interact with and respond to climate change, with particular attention to the Canada Basin and Beaufort Gyre regions. She employs both observational data from projects like the Ice-Tethered Profilers and theoretical modeling approaches to understand complex Arctic oceanographic phenomena. Her recent publications reveal a strong focus on Arctic Ocean dynamics under climate change, with particular attention to sea ice volume changes, freshwater content increases, and biogeochemical processes. Her work frequently appears in high-impact journals including Journal of Geophysical Research and Geophysical Research Letters, and she regularly contributes to major climate assessment reports such as the NOAA Arctic Report Card and the American Meteorological Society's State of the Climate reports. Her research demonstrates increasing attention to carbon cycle dynamics and potential climate engineering applications in polar regions. Dr. Timmermans actively mentors a large research group consisting of PhD students, postdoctoral associates, and undergraduate researchers working on diverse aspects of Arctic climate science. Her students pursue projects ranging from sea ice dynamics to ocean biogeochemistry and fluid dynamics modeling. She also serves on the Geophysical Fluid Dynamics Summer Program, providing training opportunities for the next generation of oceanographers. She leads and participates in several major Arctic research initiatives including the Sea-Ice MURI, Ice-Tethered Profilers program, Beaufort Gyre Exploration Project, and contributes to the NOAA Arctic Report Card. Her laboratory utilizes data from ice-tethered profilers, satellite observations, and numerical models to investigate Arctic Ocean processes across multiple spatial and temporal scales.

Saud Alhusainiمشاهده پروفایل

استادیار

• Neurology
• Movement Disorders
• Parkinson's Disease
• +۴ مورد دیگر

Saud Alhusaini MD PhD is an Assistant Professor of Neurology at the Warren Alpert Medical School of Brown University and serves as a Neurologist/Movement Disorders Specialist at Rhode Island Hospital. His research integrates imaging genomics and multimodal brain imaging approaches to investigate neurological disorders including Parkinson's disease, essential tremor, and epilepsy. He is affiliated with the Carney Institute for Brain Science and collaborates extensively with clinicians, geneticists, electrophysiologists, MRI specialists, neuropsychologists, and data scientists. Education: PhD from the Royal College of Surgeons in Ireland (RCSI) MSc in Neuroscience from Trinity College Dublin MD from University of Dublin, School of Medicine Adult neurology residency at McGill University/Montreal Neurological Institute Clinical research fellowship at Yale School of Medicine Clinical fellowship at Stanford University Medical Center Dr. Alhusaini's research focuses on identifying key endophenotypes and subclinical biomarkers to elucidate the underlying mechanisms of complex neurological conditions. His work spans multiple areas including movement disorders, epilepsy, and brain structure genetics. He has made significant contributions to understanding the genetic architecture of brain structures through his involvement with the ENIGMA consortium, which conducts large-scale collaborative analyses of neuroimaging and genetic data across institutions worldwide. An analysis of his publication record reveals a consistent pattern of high-impact research at the intersection of neurology, genetics, and advanced imaging techniques. His recent work demonstrates particular expertise in Parkinson's disease genetics, epilepsy network analysis, and movement disorder diagnostics. The breadth of his research, spanning from basic genetic mechanisms to clinical applications, highlights his comprehensive approach to understanding neurological disorders. Dr. Alhusaini has received funding from the Rhode Island Research Foundation, Brown Physicians, Inc., and Advance RI-CTR to support his research initiatives. His collaborative approach is evident through his numerous multi-institutional projects and extensive co-author network across Brown University departments including Neurology, Neurosurgery, and Pathology and Laboratory Medicine.

• Medical Imaging
• Deep Learning Applications
• Ultrasound Imaging
• +۳ مورد دیگر

Mehrdad Salehi is a researcher at the Chair of Computer Science Applications in Medicine at the Technical University of Munich (TUM) . His work focuses on the intersection of computer science and medical imaging, with expertise in ultrasound technology, deep learning, and surgical navigation systems. Key research areas include sonification of medical data, 3D ultrasound reconstruction, and machine learning-based segmentation. He has contributed to innovative projects like PRO-TIP calibration phantoms and ColibriDoc autonomous docking systems. His publications highlight trends in acoustic feedback mechanisms, neural radiance fields for medical imaging, and real-time image analysis. He can be reached at mehrdad.salehi@tum.de .

John Z. Ayanianمشاهده پروفایل

استاد

• Health Equity
• Health Care Disparities
• Access to Care
• +۴ مورد دیگر

John Z. Ayanian serves as the Alice Hamilton Distinguished University Professor of Medicine and Healthcare Policy at the University of Michigan, holding joint appointments as Professor of Internal Medicine in the Medical School, Professor of Health Management and Policy in the School of Public Health, and Professor of Public Policy in the Gerald R Ford School of Public Policy. As inaugural Director of the Institute for Healthcare Policy and Innovation (IHPI), he leads a consortium of 700 faculty members across 15 schools and maintains clinical practice as a general internist at Michigan Medicine. His academic foundation includes a Bachelor of Arts in history and political science from Duke University (1982), medical degree from Harvard Medical School (1987), and master's in public policy from Harvard Kennedy School (1987), followed by residency and fellowship at Brigham and Women’s Hospital and post-doctoral training in health services research at Harvard School of Public Health. Dr. Ayanian's research program investigates health equity, access to care, and quality of care with particular attention to social determinants including race/ethnicity, gender, socioeconomic status, and insurance coverage. His work critically examines Medicaid expansion impacts, Medicare Advantage disparities, and policy responses to health inequities, often utilizing large-scale claims databases and cross-institutional collaborations. Current projects include the federally-authorized evaluation of Michigan's Medicaid expansion program serving over 700,000 adults. Analysis of his 15 most recent publications (2025) reveals three dominant research thrusts: (1) Medicare Advantage vs Traditional Medicare comparisons across diverse clinical conditions, (2) Medicaid policy evaluation including unwinding impacts and expansion effects, and (3) innovative measurement of health equity through new indices and AI applications. His work consistently emphasizes methodological rigor in health services research while maintaining strong policy relevance. His scientific honors include: Election to the National Academy of Medicine Master status in the American College of Physicians John Eisenberg National Award for Career Achievement in Research Distinguished Investigator Award from AcademyHealth Election to Alpha Omega Alpha and Association of American Physicians Dr. Ayanian leads the federally-funded Healthy Michigan Plan evaluation team of 15 faculty members and serves as founding Editor-in-Chief of JAMA Health Forum, previously holding editorial positions at the New England Journal of Medicine. His research receives substantial federal support focused on health policy evaluation, with particular emphasis on vulnerable populations. He actively mentors students and junior faculty across multiple disciplines. As Director of IHPI, he fosters interdisciplinary collaboration across 15 schools at the University of Michigan. His leadership extends to center memberships in AI and Digital Health Innovation, Caswell Diabetes Institute, and Center for Global Health Equity, where he promotes data-driven solutions to health disparities through cross-campus partnerships and innovative research methodologies.

• Optical fiber communication
• Space-division multiplexing (SDM)
• Wavelength-division multiplexing (WDM)
• +۵ مورد دیگر

Itsuro Morita is Professor in the School of Fundamental Science and Engineering, Faculty of Science and Engineering, Waseda University, Tokyo. Before joining Waseda in 2022 he spent 23 years at KDDI R&D Laboratories, advancing from researcher to executive research fellow, and has been a visiting researcher at Stanford University. He is an IEEE Fellow and IEICE Fellow recognized for pioneering large-capacity, long-haul optical transmission systems. Education: 2004 – 2005 Tokyo Institute of Technology, Graduate School of Science & Engineering, Department of Electrical and Electronic Engineering (Doctoral coursework) 1990 – 1992 Tokyo Institute of Technology, Graduate School of Science & Engineering, Department of Physical Electronics (M.E.) 1986 – 1990 Tokyo Institute of Technology, School of Engineering (B.E.) Research Interests: Morita’s work sits at the intersection of optical fiber communication and software-defined networking. He explores ultra-high-capacity transmission via space-division multiplexing (multi-core/few-mode fibers), real-time MIMO digital signal processing for modal crosstalk mitigation, and SDN/NFV orchestration of disaggregated optical networks. Additional interests include quality-of-transmission estimation using machine learning, telemetry-enabled control planes (gRPC/gNMI), and metro-embedded edge/cloud architectures for IoT services. Publication Trends: Recent articles emphasize two converging themes: (i) petabit-per-second SDM/WDM experiments using novel fiber geometries and real-time DSP, and (ii) cloud-native SDN control frameworks that integrate machine-learning-based QoT prediction, YANG/NETCONF modeling, and open APIs (TAPI/OpenConfig) for multi-domain, partially disaggregated networks. These works collectively push both the physical capacity frontier and the agility of next-generation optical infrastructure. Scientific Awards: C&C Prize 2024 (NEC C&C Foundation) – contributions to WDM optical submarine cable systems IEICE Achievement Award 2021 – pioneering research on 10-Pbit/s ultra-large-capacity SDM transmission Telecom System Technology Award 2021 – 10.16-Pbit/s dense SDM/WDM transmission record IEEE Fellow (2021) – contributions to large-capacity high-speed transmission systems IEICE Fellow (2020) – research on trans-oceanic high-speed optical signal transmission Ichimura Industrial Award – Contribution Prize 2018 – development of terabit-class submarine cable systems Maejima Hisoka Award 2012 – proposal and demonstration of distributed-control soliton communication Minister of Economy, Trade and Industry Award for Advanced Technology 2006 – 160 Gbit/s ultra-high-speed optical transmission technology Advising & Grants: At Waseda University Morita advises graduate students on experimental photonic networking and leads externally funded projects on petabit SDM transmission and SDN orchestration. While specific grant numbers are not disclosed, his continuous industry-university collaborative testbeds (with KDDI, CTTC, and others) indicate substantial competitive funding. Labs & Teams: He heads the Optical Space-Division-Multiplexing Laboratory at Waseda, maintaining joint experimental facilities with KDDI Research and international partners (e.g., CTTC, Spain). The group operates real-time coherent MIMO testbeds, multi-domain SDN controllers, and fiber-level SDM prototypes capable of petabit-per-second demonstrations.

Charles Gomezمشاهده پروفایل

دانشیار

• Computational Sociology
• Mathematical Sociology
• Global Science
• +۷ مورد دیگر

Charles Gomez is an Associate Professor in the School of Sociology at the University of Arizona. He is affiliated with the College of Information Science and the Applied Math Graduate Interdisciplinary Program (GIDP), reflecting his interdisciplinary focus. His work centers on computational and mathematical sociology, particularly the study of inequality in global scientific knowledge production, diffusion, and diversity. Dr. Gomez received his Ph.D. from Stanford University, master’s degrees from Harvard Kennedy School and Columbia University, and a B.Sc.Eng. from Duke University. Ph.D., Stanford University M.A., Harvard Kennedy School M.S., Columbia University B.Sc.Eng., Duke University His research integrates natural language processing, social network analysis, survey experiments, simulations, and interviews to explore hierarchies, complexity, and diversity in science. He is particularly interested in how political and institutional forces shape AI research and global knowledge systems. The recent publications reflect a strong focus on global science, AI, knowledge diffusion, and inequality. His work employs both computational and qualitative methods to analyze large-scale scientific networks, epistemic diversity, and the structural biases in research collaboration and dissemination. Themes include international politics in AI, peer review bias, simulation of knowledge spread, and the role of elite institutions in shaping scientific agendas. His scientific recognition includes the prestigious National Science Foundation (NSF) CAREER Award (2024–2029). He has secured over $1 million in research funding as PI or co-PI. National Science Foundation (NSF) CAREER Award (2024–2029) Dr. Gomez leads the Global Knowledge Lab and Observatory ("The Global Lab"), an interdisciplinary research group dedicated to studying science, knowledge, and innovation at a global scale. He is actively involved in mentoring and welcomes Ph.D. students and collaborators. He has published in top journals including Nature Human Behaviour , Nature Communications , Research Policy , Social Networks , and Sociological Science .

• Nanobiosensors
• Nanomaterials
• Biosensors
• +۳ مورد دیگر

Arben Merkoçi is an ICREA Research Professor and leader of the NanoBioelectronics and Biosensors Group at the Catalan Institute of Nanoscience and Nanotechnology (ICN2). He holds a PhD in ion-selective electrodes from the University of Tirana (Albania) and has held research positions at institutions including the Polytechnic University of Budapest, University of Ioannina, and New Mexico State University. His research focuses on integrating biological molecules with micro/nanostructures to design advanced biosensors, with applications in healthcare and environmental monitoring. Education: PhD in Analytical Chemistry (University of Tirana, 1992) Roles: Co-Editor-in-Chief of Biosensors and Bioelectronics , member of the Academy of Sciences of Albania Research interests include nanomaterial-based biosensors (e.g., graphene, MXenes, quantum dots), point-of-care diagnostics, and sensor fabrication technologies. He has pioneered innovations in inkjet-printed sensors, wearable devices, and CRISPR-integrated biosensing. His group collaborates globally to advance nanobiosensor applications in clinical and environmental settings. Over 350 publications (H-index 91) and 40 supervised PhD theses highlight his contributions. He co-founded GraphenicaLab (graphene patterning) and PaperDrop (clinical diagnostics). Active in grant acquisition and policy, he shaped Spain’s first nanoscience undergraduate program at the Universitat Autònoma de Barcelona.

Radu Jianuمشاهده پروفایل

مدرس

• Data Visualisation
• Visual Analytics
• Human Computer Interaction
• +۷ مورد دیگر

Dr. Radu Jianu is a Lecturer in the Department of Computer Science at City, University of London , where he has been a faculty member since 2016. He is affiliated with the giCentre , a leading research group in information visualization. He earned his PhD and MSc in Computer Science from Brown University, USA, and a Diploma in Engineering from the Polytechnic University of Timisoara, Romania. His academic career includes a previous role as Assistant Professor at Florida International University (2012–2016). His research focuses on Data Visualisation, Visual Analytics, and Human-Computer Interaction . He conducts interdisciplinary collaborations with domains such as biology, food policy, and energy decarbonisation, aiming to develop interactive visual tools that enhance data understanding and decision-making. His methodological approach includes user studies, eye-tracking, and the design of novel visualization techniques. Dr. Jianu teaches Programming in Java and Cognition and Technologies , and he coordinates the Programming Bootcamp. He also holds administrative responsibilities as the Progression and Support Director in the Computer Science Department and is a member of its Executive Committee (ExCo). His recent publications reflect a growing interest in LLM-assisted visual analytics, gaze-aware systems, and collaborative human-AI analytical frameworks . He has published in top venues such as IEEE TVCG, CHI, EuroVis, and Nature Immunology, with several best paper awards. His work on the RAMPVIS project highlights his contributions to visualization in public health emergencies. Scientific Awards: Best Paper Award, Symposium on Graph Drawing (2018) Best Short Paper Award, EuroVis (2020) Advising and Grants: Dr. Jianu supervises multiple PhD and MSc students, including Dany Laksono (Energy Decarbonisation) and Maeve Hutchinson (NLP-mediated Visualization). His students have co-authored high-impact, award-winning papers. He has been involved in funded research initiatives such as RAMPVIS, which received support from UKRI/EPSRC for developing visual analytics infrastructure during the COVID-19 pandemic. Labs and Teams: He is an active member of the giCentre at City, University of London, a hub for visualization research. He also collaborates with interdisciplinary teams in epidemiology, immunology, and computer science, contributing to large-scale projects like the Immunological Genome Project and RAMPVIS.

Oliver Gasserمشاهده پروفایل

پژوهشگر

• Internet Measurement
• IPv6
• BGP
• +۹ مورد دیگر

Oliver Gasser is a researcher at the Max Planck Institute for Informatics (MPI-INF) and the Technical University of Munich (TUM), where he has co-lectured courses such as Advanced Computer Networking and Master Course Computer Networks. His research focuses on Internet measurement, security, and privacy, with a strong emphasis on IPv6, DNS, BGP, and web tracking technologies. His research interests include Internet measurement, IPv6 deployment, BGP security, DNS infrastructure, web tracking, privacy technologies, and network resilience. He has made significant contributions to understanding IPv6 hitlists, router fingerprinting, hypergiant content delivery networks, and consent banner manipulation on the web. His work combines large-scale active measurements with data analysis to uncover systemic issues in Internet infrastructure and privacy practices. The recent publications highlight a consistent focus on measurement-driven research across networking, security, and privacy. Trends include analyzing IPv6 adoption patterns, detecting covert tracking mechanisms in web cookies, evaluating security of Internet protocols like DNS and BGP, and improving measurement methodologies for large-scale network studies. His work often involves developing open tools and datasets that advance reproducibility in networking research. PAM 2023 Best Paper Award TMA 2023 Best Paper Award TMA 2023 Fast Track Award PAM 2018 Best Paper Award IRTF Applied Networking Research Prize 2018 IMC 2017 Community Contribution Award TMA 2017 Best Dataset Award CoNEXT 2023 Community Contribution Award Oliver Gasser has advised or co-advised over 40 master’s and bachelor’s theses at MPI-INF and TUM, demonstrating strong mentorship in academic research. He has led several measurement projects that have received external funding, including development of the IPv6 Hitlist Service and tools for analyzing web tracking. His community service includes extensive participation in program committees for major networking conferences such as IMC, CoNEXT, PAM, and TMA. He leads and contributes to several open research initiatives including the IPv6 Hitlist Service, SNMPv3 Measurement Service, MPTCP Measurement Service, DNS Observatory, and the BannerClick tool for automated cookie banner interaction. These platforms provide valuable resources for the global networking research community and support reproducible science.

Keith D. Koperمشاهده پروفایل

استاد

• Geophysics
• Seismology
• Array Seismology
• +۱۲ مورد دیگر

Keith D. Koper is a Professor in the Department of Geology & Geophysics at the University of Utah and serves as Director of the University of Utah Seismograph Stations (UUSS). He is also the editor-in-chief of The Seismic Record . His work integrates academic research with operational seismic monitoring and public safety initiatives across Utah and the Intermountain West. Education: PhD in Geophysics, Washington University, 1998 BA in Math, Geology, and ISP, Northwestern University, 1993 Dr. Koper's research focuses on array seismology, forensic seismology, deep Earth structure (especially the inner core), earthquake rupture imaging, ambient seismic noise, and seismic hazards in the Intermountain West, including mining-induced and urban earthquakes. His work combines observational seismology with advanced signal processing and machine learning techniques to improve detection, discrimination, and imaging capabilities. He has led or contributed to major projects involving the Wasatch Front, Yellowstone, and regional seismic networks. His recent research emphasizes machine learning for earthquake detection, high-resolution relocation of aftershock sequences (e.g., Magna 2020, Bluffdale 2019), microseism generation in lakes, and fine-scale imaging of the Earth's inner core using seismic reflections. His studies often involve interdisciplinary collaboration, particularly with mining engineering and geodesy. Dr. Koper's research has been consistently funded by federal and state agencies, including the National Science Foundation (NSF), U.S. Geological Survey (USGS), Department of Energy (DOE), Air Force Research Laboratory (AFRL), and the Utah Department of Public Safety. His publications reflect a strong trend toward integrating computational methods with traditional seismological analysis to tackle complex problems in both natural and induced seismicity. Scientific Service and Leadership: Editor-in-Chief, The Seismic Record Director, University of Utah Seismograph Stations Secretary, U.S. Air Force Seismic Review Panel Former Chair and Vice-Chair, Utah Seismic Safety Commission Dr. Koper mentors graduate students in seismology and geophysics, including recent advisees Sean Hutchings and Alysha Armstrong. His research group actively engages in both fundamental and applied seismological research, with strong ties to national labs such as Sandia. The group is involved in deploying portable seismic arrays, analyzing large datasets, and developing new algorithms for event detection and classification. The University of Utah Seismograph Stations, under his leadership, plays a critical role in monitoring seismicity in Utah and Yellowstone, producing real-time earthquake information, ShakeMaps, and public outreach materials. The station also contributes to national and international efforts in nuclear test monitoring and volcanic hazard assessment.

Sriram Subramanianمشاهده پروفایل

استادیار

• Multi-agent Systems
• Reinforcement Learning
• Game Theory
• +۵ مورد دیگر

Sriram Subramanian is an Assistant Professor at the School of Computer Science in Carleton University since July 2025. He holds affiliations with the Vector Institute for Artificial Intelligence and the Schwartz Reisman Institute for Technology and Society in Toronto, and serves as a mentor in the Indigenous Black Engineering and Technology (IBET) PhD Project . Ph.D. in Electrical and Computer Engineering, University of Waterloo (2022) MASc in Electrical and Computer Engineering, University of Waterloo (2018) BE in Geomatics Engineering, Anna University (2016) His research focuses on advancing Multi-agent Systems and Reinforcement Learning through intersections with Game Theory , with applications in generative AI , robotics, finance, and autonomous driving. Recent work emphasizes cooperation mechanisms, constraint learning, and theoretical robustness in large-scale environments. Articles demonstrate cross-disciplinary impacts in chemistry (ChemGymRL) and societal systems. Notable awards include the MITACS Globalink Research Award , Pasupalak Fellowship in AI , and the CAIAC Best Doctoral Dissertation Award (2023) . Publications span top venues like AISTATS, ICML, AAAI, IJCAI, JAIR , and TMLR . He has collaborated with Microsoft, Royal Bank of Canada, Denso, ESRI, and Borealis AI. As a Distinguished Postdoctoral Fellow at the Vector Institute (2022-2025), he advanced algorithmic frameworks while maintaining active roles in conference reviewing and committee work. His advocacy for equity and diversity drives mentorship initiatives in Canadian institutions.

James S. Nobleمشاهده پروفایل

استاد

• Logistics and Distribution
• Supply Chain System Design
• Integrated Production Systems
• +۷ مورد دیگر

James S. Noble is a Professor and Chair of the Department of Industrial and Systems Engineering at the University of Missouri, where he also serves as the MU Site Director for the NSF I/UCRC Center for Excellence in Logistics and Distribution (CELDi). His work bridges academia and industry through applied research in logistics, supply chain, and integrated production systems. PhD, Purdue University MS, Purdue University BS, University of Oklahoma Dr. Noble's research focuses on logistics and distribution , supply chain system design , and integrated production systems , with applications ranging from humanitarian logistics to intelligent warehouse systems. His work emphasizes modeling, analysis, and optimization of material flow and transportation systems. The 15 most recent articles reflect a consistent trajectory in logistics systems analysis , supply chain modeling , and material flow improvement . These publications demonstrate a strong integration of operations research, systems engineering, and real-world problem-solving, with applications in energy, transportation, humanitarian aid, and industrial logistics. Keywords span Operations Research , Supply Chain Management , and Industrial Engineering , while sub-fields include Bayesian forecasting, reverse logistics, winter road maintenance, and intelligent systems. Dr. Noble has been recognized with several prestigious awards: Society of Manufacturing Engineers Outstanding Young Manufacturing Engineering Award (1997) William T. Kemper Fellowship for Teaching Excellence (2022) Win Horner Award for Innovative Writing Intensive Teaching (2014) Elected Fellow of the Institute for Industrial and Systems Engineering (IISE) (2019) His research has been generously funded by the National Science Foundation , Bayer , Boeing , Hallmark Cards , Honeywell FMT , Medline , Ameren , UMB Financial , the U.S. Economic Development Administration , the Midwest Transportation Consortium , and the Missouri Department of Transportation . While specific advisees are not listed, his leadership in CELDi and role as department chair suggest extensive mentorship of graduate and undergraduate students in real-world logistics projects. He is also a registered Professional Engineer in Missouri. As MU Site Director for CELDi, Dr. Noble leads a multidisciplinary team of faculty from Industrial Engineering, Civil Engineering, Geography, and Biological Engineering, collaborating with over 30 industry, military, and government partners to solve real-world logistics challenges and develop implementable, cutting-edge solutions.

Chen Liuمشاهده پروفایل

استادیار

• Machine Learning
• Adversarial Robustness
• Privacy-Preserving Machine Learning
• +۹ مورد دیگر

Chen Liu is an Assistant Professor in the Department of Computer Science at City University of Hong Kong and the Principal Investigator (PI) of the Machine Learning and Optimization (MLO) group. His research focuses on building reliable machine learning models, particularly studying robustness and privacy properties of deep neural networks from an optimization perspective. University: City University of Hong Kong Academic Rank: Assistant Professor Students: Supervises multiple PhD, MPhil, and postdoctoral researchers. Education: Holds a Ph.D. (2022) and MSc (2017) in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), and a BSc (2015) in Computer Science from Tsinghua University. Research Interests: Adversarial robustness, privacy-preserving machine learning, optimization algorithms, dataset distillation, generative models, and theoretical analysis of loss landscapes. His work addresses challenges like catastrophic overfitting, architecture overfitting in distilled data, and stable adversarial training methods. Article Trends: Recent publications explore adversarial robustness under l0/l1 norms, gradient inversion for data reconstruction, evolutionary factor searching in finance, and meta-tuning for out-of-domain few-shot learning. These works emphasize optimization techniques to enhance model reliability and generalization. Scientific Awards: Microsoft Research Ph.D. Scholarship Programme (2017–2019) Advising and Grants: Supervises a diverse team of current and former students, with collaborations across institutions like George Mason University and Zhejiang University. Research supported by academic and industry grants. Labs and Teams: Leads the MLO group, which investigates fundamental ML theory and algorithms to improve system reliability. The group's work spans adversarial training, dataset distillation, and generative model optimization.

Dongsheng Yangمشاهده پروفایل

استادیار

• Power Electronics
• Renewable Energy Systems
• Power Conversion
• +۳ مورد دیگر

Dongsheng Yang is an Assistant Professor with the Electrical Energy Systems Group at the Department of Electrical Engineering of Eindhoven University of Technology (TU/e). He has been working at TU/e since 2019, focusing on power electronics and renewable energy integration, and previously served as Assistant Professor at Aalborg University's Department of Energy Technology (2018-2019). Dr. Yang received his B.S., M.S., and Ph.D. degrees in electrical engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2008, 2011, and 2016, respectively. His academic journey progressed from postdoctoral researcher at Aalborg University (2016) to faculty positions at both institutions. Dr. Yang's research focuses on the modeling, analysis, control, and design of power electronics dominated power systems , with the goal of safely accommodating high-penetrations of renewable energy sources and energy-efficient end-uses. His work spans several critical areas in modern power systems: Power electronics dominated grid stability and control Renewable energy integration and grid synchronization EV fast-charging infrastructure development Hydrogen production systems Medium-frequency transformer design and modeling AI applications in power electronics Analysis of Dr. Yang's recent publications reveals a strategic research trajectory toward developing advanced control strategies for power converters, improving modeling techniques through AI approaches, and addressing practical implementation challenges for renewable energy systems. His work spans both theoretical developments and practical applications, with increasing emphasis on neural network frameworks for magnetic modeling, safety boundaries for EV charging architectures, and enhanced fault ride-through capabilities for grid-connected systems. This progression demonstrates his commitment to solving real-world engineering challenges in the transition to renewable energy. Dr. Yang has received professional recognition including: Senior Member of IEEE Corresponding Member of CIGRE Working Group C4.56 Topic chair, technical committee member, and reviewer for top-level conferences and journals in power electronics Dr. Yang actively supervises doctoral candidates and postdoctoral researchers, including Xiao Yang (working on AI for power electronics), Saizhao Yang (postdoc), and L.A. Vlaar. He serves as project manager for multiple significant research initiatives totaling over €5 million in funding: REDCON (2023-2028) - Reconfigurable power electronics testbench Flexible Offshore Wind Hydrogen Power Plant Module (2022-2026) Sectorplan-DCES-Y.D.inv.: Reconfigurable power electronics testbench (2021-2029) E2GO-RDC Cost-reduction of EV fast-charging station (2021-2026) CW620863 System impact analysis for large scale renewable hydrogen production (2022-2023) Dr. Yang leads research within the Electrical Energy Systems group at TU/e's High Tech Systems Center, focusing on power conversion technologies. His work connects with multiple research teams across Europe through collaborative projects focused on renewable energy integration, EV infrastructure, and hydrogen production systems. He also teaches the course 'Dynamic control of power conversion in renewable energy systems' and contributes to the UN Sustainable Development Goals related to affordable and clean energy.