جست‌وجوی استاد و پژوهشگر

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

Daniel Abadiمشاهده پروفایل

استاد

• Database System Architecture
• Distributed Database Systems
• Scalable Transaction Processing
• +۳ مورد دیگر

Daniel Abadi is the Darnell-Kanal Professor of Computer Science at the University of Maryland, College Park, with an appointment in the University of Maryland Institute for Advanced Computer Studies. He leads the Data Systems Lab at Maryland (DSLAM) and has made significant contributions to database system architecture and implementation, particularly in scalable and distributed systems. Prof. Abadi's research focuses on database system architecture, especially at the intersection with scalable and distributed systems. He is best-known for the development of the storage and query execution engines of the C-Store (column-oriented database) prototype, which was commercialized by Vertica and eventually acquired by Hewlett-Packard, and for his HadoopDB research on fault tolerant scalable analytical database systems which was commercialized by Hadapt and acquired by Teradata. His current work includes deterministic distributed systems like Calvin and SLOG, which provide strictly serializable, low-latency, geographically replicated database transactions. Analysis of his recent publications reveals a strong focus on modern database challenges including transaction processing, distributed systems architecture, data mesh concepts, schema evolution, and IoT data management. His work consistently addresses the tension between consistency, availability, and performance in distributed database systems, with recent emphasis on moving beyond traditional two-phase commit protocols and exploring novel approaches to data architecture like data mesh. ACM Fellow Sloan Research Fellowship Churchill Scholarship NSF CAREER Award VLDB Best Paper Award Two VLDB Test of Time Awards (for C-Store and HadoopDB) 2008 SIGMOD Jim Gray Doctoral Dissertation Award 2013-2014 Yale Provost's Teaching Prize 2013 VLDB Early Career Researcher Award PhD dissertation advisor for Alexander Thomson and Jose Falerio, whose dissertations won SIGMOD Jim Gray Doctoral Dissertation Awards in 2015 and 2020 respectively Prof. Abadi has advised multiple PhD students, including Alexander Thomson and Jose Falerio, both of whom received the prestigious SIGMOD Jim Gray Doctoral Dissertation Award. His research has been supported by numerous grants including NSF funding for projects like SLOG. He maintains an active presence in the database community through his widely-read blog DBMS Musings and through service on program committees for major conferences including SIGMOD, VLDB, and CIDR. He leads the DSLAM research group at the University of Maryland, which focuses on cutting-edge database system research with strong industry connections and practical impact.

• Computer Architecture
• Datacenter Systems
• Cloud-Native Server Architecture
• +۷ مورد دیگر

Babak Falsafi is a Full Professor at the School of Computer and Communication Sciences (IC) at EPFL, leading the Parallel Systems Architecture Laboratory (PARSA). He is a renowned expert in computer architecture, datacenter systems, and cloud-native server design. His research focuses on post-Moore era computing, emphasizing heterogeneous architectures, energy efficiency, and scalable IT infrastructure. Falsafi is the founder of EcoCloud, an EC-sponsored industrial-academic consortium investigating sustainable information technology. He holds ACM and IEEE fellowships, a Sloan Research Fellowship, and has contributed to major projects like Optimus Prime (data transformation acceleration), AstriFlash (flash-based online service systems), and Midgard (virtual memory re-design). His work spans hardware-software co-design, memory systems, and security. Falsafi advises numerous PhD students and collaborates with industry partners such as Google and Cavium. Key achievements include pioneering scalable multiprocessor architectures, snoop filters in IBM BlueGene, and spatial memory streaming in ARM cores. His lab develops open-source tools like QFlex for server simulation. He frequently presents at top conferences (HPCA, ISCA, MICRO) and chairs workshops on post-Moore infrastructure. Teaching roles include leading courses in computer architecture and parallel systems across multiple EPFL departments (SIN, EDIC, SSC, SMA). His work addresses datacenter challenges like the 'data tax' and mitigating latency through specialized accelerators.

Ian Frigaardمشاهده پروفایل

استاد

• Non-Newtonian Fluid Mechanics
• Visco-plastic Fluids
• Petroleum Engineering
• +۳ مورد دیگر

Ian Frigaard is a Professor in the Department of Mechanical Engineering at the University of British Columbia (UBC), affiliated with the Faculty of Applied Science. He also holds an appointment in the Department of Mathematics. His research group operates in UBC's Complex Fluids Lab, focusing on interdisciplinary studies combining mathematical, experimental, and computational approaches. Education: B.Sc. (University of Wales) M.Sc. (University of Oxford) D.Phil. (University of Oxford) C.Math. (Certificate in Mathematics) Research Interests: Professor Frigaard specializes in non-Newtonian fluid mechanics, particularly the mechanics of visco-plastic (yield stress) fluids. His work addresses industrial challenges in petroleum engineering, including well cementing, leakage prevention, and abandonment techniques related to GHG emission control and environmental protection. Research methodologies span theoretical modeling, experimental validation, and computational simulations. Publication Trends: Recent work (2021–2023) emphasizes bubble dynamics in complex fluids, displacement flows in annular geometries, wellbore integrity modeling, and stochastic risk assessment for oil/gas operations. Publications frequently appear in top-tier journals like the Journal of Fluid Mechanics and Journal of Non-Newtonian Fluid Mechanics . Awards & Honors: CSME Fluid Mechanics Medal (2024) Stanley G. Mason Award, Canadian Society of Rheology (2022) Killam Research Prize, UBC (2019) Academic Leadership: Leads a research group of 10+ graduate students and postdocs. Provides summer internships and collaborates extensively with the petroleum industry. Research is supported by industrial partnerships and institutional grants. Facilities: Conducts experiments in UBC's Complex Fluids Lab, equipped for advanced rheological measurements and flow visualization.

Joy Arulrajمشاهده پروفایل

دانشیار

• Data Systems
• Machine Learning
• Database Systems
• +۲ مورد دیگر

Joy Arulraj is an Associate Professor in the School of Computer Science within the College of Computing at Georgia Institute of Technology. His research focuses on data systems, machine learning, and database systems, with a particular emphasis on video analytics and adaptive query processing. He leads the Data Systems and Analytics Group and is developing the EVA AI-Relational Data System. Dr. Arulraj's research interests span data systems, machine learning, database systems, video analytics, and adaptive query processing. His work centers on developing systems that efficiently process complex queries, particularly for video analytics and machine learning workloads. He has made significant contributions to GPU database systems, non-volatile memory database management, and adaptive query processing techniques. His research often bridges the gap between theoretical database principles and practical implementations for modern hardware architectures. His recent publications show a strong trend toward video analytics systems, adaptive query processing for machine learning workloads, and GPU-accelerated database systems. The EVA system represents a major focus of his recent work, providing end-to-end exploratory video analytics capabilities. His research also addresses fundamental database concepts like buffer management, query optimization, and storage management, adapting these principles for modern hardware and application requirements. Dr. Arulraj has advised numerous graduate students including Pramod Chunduri, Gaurav Tarkok Kakkar, Jiashen Cao, and Sayan Sinha. His graduated students have gone on to work at companies like ServiceNow, Meta Research, and the Korean Army. He actively teaches database system courses at Georgia Tech, including Database System Implementation (CS 4420/6422) and Advanced Database System Implementation (CS 4423/6423), where students build database systems from scratch using C++ and the BuzzDB framework. He maintains an active research program with consistent publication output across top database and systems conferences. His work spans from theoretical database principles to practical system implementations, with a recent emphasis on video analytics, machine learning integration with database systems, and leveraging modern hardware like GPUs and non-volatile memory for database applications.

Peter Strasserمشاهده پروفایل

استاد

• Electrochemistry
• CO2 Electroreduction
• Electrocatalysis
• +۵ مورد دیگر

Peter Strasser is a Full Professor of Chemistry and Chemical Engineering at the Technical University Berlin, Germany. He holds a Diplom (MSc) in Physical Chemistry from Tübingen University (1995) and a PhD from the Fritz-Haber-Institute of the Max-Planck-Society (1999), supervised by Prof. Gerhard Ertl. His research focuses on electrocatalysis, CO₂ electroreduction, and materials science for energy storage/conversion. He has held roles at the University of Houston (2004–2007) and Symyx Technologies (2000–2004). Education : Tübingen University (1988–1995), Stanford University (1991), Università di Pisa (1992) Affiliations : German Chemical Society (GDCH) leadership roles, Electrochemical Society (ECS) committee memberships Research interests include structure-function relations in electrocatalysts, electrochemical oxygen evolution/reduction reactions, and in-situ spectroscopic techniques. He has organized major conferences such as the “Electrochemistry 2022” meeting and co-chairs symposia on fuel cells and electrolyzers. His entrepreneurial activities include mentoring startups like DexLeChem GmbH and LiquidLoop GmbH. Awards : Carl Wagner Memorial Award (2023), Faraday Medal (2021), Otto-Hahn Medal (2000) Grants/Advising : Extensive funding and mentorship in energy materials research He leads the Technische Chemie division at TU Berlin and collaborates internationally, including guest professorships in China. His work bridges fundamental electrochemistry with industrial applications in renewable energy systems.

José F. Martínezمشاهده پروفایل

استاد

• Computer Architecture
• Microprocessor Design
• Multiprocessor and Multicore Architectures
• +۵ مورد دیگر

José F. Martínez holds the Lee Teng-hui Professorship of Engineering at Cornell University's College of Engineering, where he leads research in computer architecture and systems. His roles include Vice Chair of ACM SIGARCH, IEEE Fellow, and past leadership roles in ISCA, MICRO, and IEEE Computer Society journals. He has received prestigious awards such as the NSF CAREER Award, IBM/Qualcomm Faculty Awards, and multiple teaching accolades including Tau Beta Pi Professor of the Year (2011). Education: Licenciado en Informática de Sistemas (1996), Universidad Politécnica de Valencia M.S. (1999) and Ph.D. (2002) in Computer Science, University of Illinois at Urbana-Champaign His research focuses on computer architecture , including microprocessors, multiprocessors, memory subsystems, embedded systems, and processing-in-memory (PIM) innovations. He co-leads the DARPA/SRC ACE Center for Evolvable Computing and NSF's CROPPS Center, and previously co-founded Cornell's Institute for Digital Agriculture (CIDA). His work bridges hardware-software co-design and sustainable computing. Key Contributions: Advancing energy-efficient multiprocessor architectures Developing PIM frameworks like PUMICE and Membrane Market-based resource allocation systems (e.g., XChange, ReBudget) His advising spans over 15 graduate students and has guided Merrill Presidential Scholars. Current research explores evolvable computing paradigms and AI hardware acceleration, reflecting his dual focus on foundational architecture and applied systems innovation.

Judith Driscollمشاهده پروفایل

استاد

• Functional Materials and Oxides
• Materials for Energy Applications
• Spintronic and Multiferroic Materials
• +۷ مورد دیگر

Judith Driscoll is Professor of Materials Science at the University of Cambridge in the Department of Materials Science & Metallurgy. She holds the prestigious Royal Academy of Engineering Chair in Emerging Technologies and serves as a Visiting Staff Member at Los Alamos National Laboratory. As the founding Editor-in-Chief of APL Materials, she has significantly contributed to the materials science community. Dr. Driscoll's research focuses on Energy Efficient Oxide Materials for Information and Communications Technologies and energy devices. Her work spans the development of non-volatile memory, resistive switching devices, and ferroelectric materials for neuromorphic computing applications. She investigates oxide thin films for applications ranging from data storage to energy generation and conversion, with particular emphasis on creating more energy-efficient device technologies to handle the exponential growth of data-centric applications. Her recent publications demonstrate strong trends in developing novel oxide-based memory devices with improved energy efficiency, particularly for AI applications. The work shows significant progress in hafnium-zirconium oxide ferroelectrics, resistive switching mechanisms, and vertically aligned nanocomposite structures for enhanced device performance. These innovations address critical challenges in reducing the unsustainable energy demands of modern computing, particularly for artificial intelligence systems. Fellow of the Royal Academy of Engineering Fellow of the Materials Research Society Fellow of the American Physical Society Fellow of IOM3, IOP, and Women Engineers Society Fellow of the American Academy of Arts and Sciences Recipient of ERC Advanced Grant Editor-in-Chief of APL Materials Dr. Driscoll leads a vibrant research group that has secured significant funding including her Royal Academy of Engineering Research Chair, an ERC Advanced Grant, and an ECCS-EPSRC grant in collaboration with researchers from the USA. She has founded the Cambridge Centre for Neuromorphic Computing (Neucam) in 2023. Her group operates world-leading growth equipment including pulsed laser deposition with RHEED control, high temperature oxide sputtering, and spatial ALD systems. She collaborates extensively across the University of Cambridge and with international partners to solve complex materials challenges, with her group's role often being to identify optimal materials for functional goals, predict fabrication methods, and then create and characterize these materials.

Manoj Sachdevمشاهده پروفایل

استاد

• Semiconductor Devices
• Low-Power Electronics
• VLSI Design
• +۷ مورد دیگر

Manoj Sachdev is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Faculty of Engineering. His research focuses on semiconductor devices, low-power electronics, and secure hardware systems. He leads projects in flexible electronics, nanotechnology, and radiation-hardened circuits, with applications in displays, memory technologies, and biomedical sensors. His work integrates advanced materials science with circuit design to address challenges in energy efficiency and security. Education: Not explicitly stated in provided text. Research interests span thin-film transistors (TFTs), resistive switching memories, neuromorphic computing, and physically unclonable functions (PUFs). Recent efforts include developing low-power circuits for flexible substrates and secure microprocessors. His contributions to semiconductor device physics and integration techniques have advanced applications in wearable electronics and medical diagnostics. Publications highlight innovations in low-power flip-flops, energy-efficient display drivers, and memristor-based systems. He collaborates on interdisciplinary projects combining photonics, nanoelectronics, and biomedical engineering. Awards: None explicitly listed in provided text. Grants and advising: Advises on semiconductor fabrication, secure hardware design, and radiation effects in electronics. Leads research groups focused on next-generation memory technologies and flexible integrated systems. Labs/Teams: Active in the University of Waterloo's semiconductor and flexible electronics research clusters, contributing to both academic and industry partnerships.

Julia R. Greerمشاهده پروفایل

استاد

• Mechanics of Hierarchical Architectures
• Nanomaterials
• Additive Manufacturing
• +۷ مورد دیگر

Julia R. Greer serves as the Ruben F. and Donna Mettler Professor of Materials Science, Mechanics and Medical Engineering at the California Institute of Technology (Caltech), where she also holds the position of Executive Officer for Applied Physics and Materials Science since 2025. She earned her B.S. from MIT (1997) and M.S./Ph.D. from Stanford University (2000/2005), joining Caltech as Assistant Professor in 2007, promoted to Professor in 2013, and appointed to her current named professorship in 2019. Her research spans mechanics of hierarchical architectures , nanomaterials , and additive manufacturing , with significant contributions to energy storage systems and biomedical materials . Key focus areas include nano-scale mechanical properties, in-situ deformation analysis, and development of novel fabrication techniques for micro-architected materials. Her group pioneered hydrogel infusion additive manufacturing for metals and multiphoton 3D lithography standards. Analysis of recent publications reveals strong emphasis on solid-state battery interfaces (2025), bioresorbable microrobots (2024), and AI-enabled material design (2024), demonstrating cross-disciplinary impact across energy, healthcare, and quantum technologies. Her work consistently bridges fundamental nanomechanics with practical applications in energy storage and medical devices. 2024 ASME Nadai Medal 2024 SES A.C. Eringen Medal Elected to National Academy of Sciences (2025) Fletcher Jones Foundation Director (2019-2025) Professor Greer has advised over 40 PhD students including Seola Lee (2025) and Wenxin Zhang (2025), with research funded by collaborations spanning MIT, UCSF, Purdue, and ETH Zurich. Her group maintains active projects in lightweight nanoarchitected materials for impact absorption, electroactive polymers for braille devices, and 3D interdigitated solid-state batteries. Current leadership includes Editor-in-Chief of the Journal of Applied Physics (2024-) and direction of Caltech's Materials Science department.

• Storage Systems
• Persistent Memory
• Key-Value Stores
• +۴ مورد دیگر

Oana Balmau is an Assistant Professor in the School of Computer Science at McGill University, where she leads the Data-Intensive Storage and Computer Systems Laboratory (DISCS Lab). She also holds a status-only appointment at the University of Toronto and serves as a working group chair for MLPerf Storage. Her research focuses on creating storage infrastructure that enables fast and energy-conscious insights from data, with particular emphasis on storage and persistent memory technologies for machine learning, data science, and edge computing workloads. Dr. Balmau's research interests span computer systems, with specific focus on: Design and implementation of efficient key-value stores Storage systems for machine learning workloads Edge computing infrastructure Persistent memory technologies Performance optimization of data-intensive systems Her recent work has led to significant contributions in storage benchmarking through the MLPerf Storage benchmark and in edge computing frameworks. The MLPerf Storage benchmark has become an industry standard for evaluating storage performance in machine learning environments, while her work on hierarchical edge computing addresses security and performance challenges in distributed edge environments. Her publications show consistent high-impact contributions to top systems venues, with recent work focusing on processing-in-memory virtualization, stream processing reconfiguration, and efficient data preprocessing pipelines. Dr. Balmau has received numerous awards for her research, including: SEC 2024 Best Paper Award for "Falcon: Live Reconfiguration for Stateful Stream Processing on the Edge" MLCommons Hero Award 2023 for leadership as MLPerf Storage working group chair ACM SIGOPS Dennis M. Ritchie Doctoral Dissertation Award 2021 Honorable Mention CORE John Makepeace Bennett Award 2021 for the best Computer Science doctoral dissertation in Australia and New Zealand USENIX ATC 2019 Best Paper Award for "SILK: Preventing Latency Spikes in Log-Structured Merge Key-Value Stores" As an educator, Dr. Balmau teaches courses on advanced computer systems, operating systems, and principles of computer systems design at McGill University. She has served on program committees for top systems conferences including SOSP, SIGMOD, FAST, and EuroSys, and has co-organized workshops on resource-efficient machine learning and edge computing. She leads the DISCS Lab, which focuses on two main research directions: Systems for ML (including the MLPerf Storage benchmark) and Edge computing (including frameworks for fast and secure edge computing in hierarchical edge environments).

Yannis Chronisمشاهده پروفایل

استادیار

• Database Systems
• Hardware-Software Co-design
• Data Processing Efficiency
• +۳ مورد دیگر

Yannis Chronis is an incoming Assistant Professor at the Department of Computer Science , ETH Zurich (starting August 2025), where he will join the ETH Systems Group . Prior to this, he spent 3 years as a Systems Researcher at Google's Systems Research Group in Sunnyvale, USA. He holds a Ph.D. in Computer Science from the University of Wisconsin-Madison (advised by Prof. Jignesh Patel) and a Bachelor's/Master's from the University of Athens, Greece (advised by Prof. Yannis Ioannidis). His research focuses on optimizing databases and data processing for modern hardware through software-hardware co-design. Key areas include database efficiency in memory-centric architectures, learned query optimizers, and cloud resource management. His work is supported by a Facebook Fellowship and has been recognized with the EDBT 2016 Medal for best paper. Teaching: Taught CS 564 - Database Management Systems at UW-Madison (Spring 2022). Service: Served on program committees for SIGMOD, VLDB, CIDR, and others, and chairs the CIDR Proceedings Committee. Key Publications: His recent work includes studies on memory-centric computing for databases, cardinality estimation benchmarks, and adaptive query processing techniques.

• Embedded Machine Learning
• High-Performance Computing
• Computer Architecture
• +۶ مورد دیگر

Holger Fröning is a full professor at Heidelberg University’s Institute of Computer Engineering (ZITI), where he leads the Hardware and Artificial Intelligence (HAWAII) Lab. His research focuses on embedded machine learning , high-performance computing , and hardware-software co-design , with emphasis on resource efficiency, power optimization, and emerging architectures like analog , photonic , and resistive memory systems. He has held leadership roles including Managing Director of ZITI (2023–present) and Dean of Studies for Computer Science (2019–2022) , and has collaborated with institutions such as NVIDIA Research, Chinese Academy of Sciences, and Graz University of Technology. Research Trends : His recent publications explore Bayesian neural networks , green machine learning , analog computing noise mitigation , and GPU/FPGA optimization . Articles highlight photonic computing for AI , memory-efficient training , and hardware-aware DNN compression . Scientific Awards : 2025 HiPEAC Paper Award (Nature Computational Science) 2014 Google Faculty Research Award Multiple Best Paper Awards (IPDPS, ICPP, ECML-PKDD workshops) Leadership & Service : Organized workshops (WEML, ITEM, F4HD), chaired tracks at EuroPar and ISC, and served on program committees for ICPR, ECAI, and FPL. Education & Affiliations : PhD and MSc from University of Mannheim (2007/2001). Sponsors include DFG, FWF, FFG, NVIDIA, SAP, and XILINX.

• Secure Decentralized Systems
• Blockchain Technology
• Systems Security
• +۳ مورد دیگر

Prof. Bryan Ford leads the Decentralized/Distributed Systems (DEDIS) lab at EPFL. He focuses on secure decentralized systems, including blockchain technology, privacy, and systems security. He earned his Ph.D. from MIT and held faculty positions at Yale University and EPFL. His work spans distributed consensus protocols, peer-to-peer networking, and privacy-preserving systems. Key projects include QuePaxa (timeout-free consensus), UIA (global connectivity for mobile devices), and MedCo (secure healthcare data sharing). He advises numerous PhD students and contributes to open-source projects like Bitcoin collective signing and privacy networks like Riffle. Education: Ph.D., MIT; Postdoctoral work at Yale Research interests include blockchain scalability, consensus algorithms, and cryptographic privacy. His lab develops systems like TRIP for coercion-resistant voting and F3B to mitigate blockchain front-running. His work on NAT traversal and peer-to-peer protocols (e.g., STUN/ICE) remains foundational in network architecture. He emphasizes practical, auditable security solutions such as CertiKOS and atomic cross-chain transactions (Atom). Notable contributions: CoSi (collective signing), OmniLedger (sharded blockchain), and privacy-preserving protocols like PURBs (Protected Unsealable Recursive Boxes). His lab collaborates with Swiss Post to audit e-voting systems and designs democratic cryptocurrencies like PoPCoin.

Paul D. Sclavounosمشاهده پروفایل

استاد

• Marine Hydrodynamics
• Stochastic Control
• Offshore Wind Energy
• +۸ مورد دیگر

Professor Paul D. Sclavounos is a faculty member in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). He earned his B.Sc. from the National Technical University of Athens in 1977 and Ph.D. from MIT in 1981. Research Interests : Marine hydrodynamics, stochastic control, offshore wind/wave/tidal/solar energy, machine learning applications, magnetohydrodynamic propulsion systems. Notable Contributions : Development of computational tools like SWAN and SML software suites; analysis of nonlinear wave dynamics; integration of AI/ML in marine hydrodynamics. Scientific Recognition : First Prize in National Mathematics Competition (1972), Georg Weinblum Memorial Lecturer (2010-2011), Best Paper Award at OMAE 2019, AEOLOS Scientific Award (2024). Leadership : Director of the Laboratory for Ship and Platform Flows since 1985; advisory roles for US Navy, US Department of Energy, and Det Norske Veritas (DNV). Teaching : Courses in Hydrodynamics (2.016), Advanced Fluid Mechanics (2.25), and Naval Architecture (2.701).