جست‌وجوی استاد و پژوهشگر

Sanjay Jainمشاهده پروفایل

استاد

• Inductive Inference
• Recursion Theory
• Complexity Theory
• +۳ مورد دیگر

Sanjay Jain is a Provost's Chair Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). His research focuses on theoretical computer science with particular emphasis on inductive inference, recursion theory, complexity theory, and computational learning theory. Education: B.Tech. in Computer Science from Indian Institute of Technology Kharagpur, India (1986) M.S. in Computer Science from University of Rochester, USA (1988) Ph.D. in Computer Science from University of Rochester, USA (1990) Professor Jain's research spans multiple areas of theoretical computer science. His primary contributions are in computational learning theory, where he has made significant advances in understanding the intrinsic complexity of language identification and the limits of inductive inference. His work on recursion theory explores fundamental questions about computability and complexity, while his research in complexity theory addresses structural aspects of computational problems. A notable achievement was his work on "Deciding Parity Games in Quasipolynomial Time," which won the prestigious STOC 2017 best paper award and later the EATCS-IPEC Nerode Prize. Professor Jain's publication record shows a consistent focus on theoretical foundations of computer science, particularly in learning theory and computational complexity. His recent work has expanded into automatic structures, semiautomatic models, and connections between computational learning and algebraic structures. There is a clear progression from foundational work on language identification to more complex models involving automatic functions, transducers, and connections to mathematical logic. Scientific Awards: STOC 2017 Best Paper Award for "Deciding Parity Games in Quasipolynomial Time" EATCS-IPEC Nerode Prize (2021) Professor Jain has served on the editorial board of Information and Computation and has been actively involved in the academic community through program committee memberships for major conferences including COLT, ALT, LATA, TAMC, and PRICAI. He has held leadership roles as program co-chair for ALT 2000 and ALT 2013, and conference chair for ALT 2005. His work has been supported by various research grants, though specific details are not provided in the available materials. Professor Jain leads research in theoretical computer science at NUS, where he has built a strong research group focused on computational learning theory and related areas. His work often involves collaborations with researchers from around the world, particularly with Frank Stephan, with whom he has co-authored numerous papers. His research group has made significant contributions to understanding the fundamental limits and possibilities of computational learning models.

Michela Becchiمشاهده پروفایل

دانشیار

• Computer Architecture
• Systems Software
• Heterogeneous Computing
• +۵ مورد دیگر

Michela Becchi is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University. She specializes in computer architecture, systems software, and applications, with a focus on heterogeneous systems, parallel algorithms, and acceleration techniques for bioinformatics, pattern recognition, and quantum computing. Her work spans multi-core CPUs, GPUs, FPGAs, and distributed clusters, emphasizing the boundary between hardware and software design. Dr. Becchi holds a Ph.D. and Master’s degree in Computer Engineering from Washington University in St. Louis (2009) and a Bachelor’s degree in Computer Engineering from Politecnico di Milano, Italy (2000). Her research has been recognized with prestigious awards, including the NSF CAREER Award (2015) and the University of Missouri System President Award for Early Career Excellence (2016). Her research interests include compiler and runtime techniques for heterogeneous systems, acceleration of bioinformatics algorithms, and high-speed networking applications. She has pioneered frameworks for efficient data transformation, GPU-accelerated compression, and memory-efficient graph algorithms for quantum computing. Her work also explores thread coarsening, mixed-precision auto-tuning, and secure multi-core processor design. Key contributions include the PILOT runtime system for GPU memory management, the GPU-FPtuner auto-tuner for floating-point applications, and innovative approaches to automata processors for genomic analysis. Her publications emphasize reproducible accuracy in scientific simulations and the optimization of irregular applications on many-core platforms.

Shad Roundyمشاهده پروفایل

دانشیار

• Energy Harvesting
• Wireless Power Transfer
• MEMS
• +۵ مورد دیگر

Shad Roundy is an Associate Professor at the University of Utah , holding dual appointments in the Department of Mechanical Engineering and Department of Electrical and Computer Engineering within the College of Engineering . He directs the Integrated Self-Powered Sensing Lab , focusing on energy harvesting, wireless power transfer, and ubiquitous sensing systems. PhD in Mechanical Engineering, University of California, Berkeley (2003) Senior Lecturer, Australian National University (postdoctoral) His research bridges mechanical design , smart materials , and sensor networks , with significant contributions to: Self-powered biomedical implants Wearable health-monitoring devices Underground agricultural sensor networks MEMS sensor development His 15 most recent publications demonstrate interdisciplinary work spanning wireless power transfer for soil sensors, flexoelectric materials, and disease severity assessment via wearables. Articles emphasize energy efficiency , novel transducer designs , and environmental sensor applications . Scientific recognition includes: NSF CAREER Award for magnetoelectric implant powering Associate Editor, Smart Materials and Structures and International Journal of Precision Engineering and Manufacturing-Green Technology Research funded by National Science Foundation , NASA , and industry partners through the ASSIST Engineering Research Center . Publications highlight collaborations across biomedical, agricultural, and wearable technology domains.

Andrea Argüellesمشاهده پروفایل

دانشیار

• Ultrasonics
• Additive Manufacturing
• Materials Characterization
• +۵ مورد دیگر

Andrea Argüelles is an Associate Professor in the Department of Engineering Science and Mechanics at Pennsylvania State University (Penn State), part of the College of Engineering. She holds affiliate researcher roles in the IEE Research Themes focusing on Health and the Environment, and Integrated Energy Systems. Her work bridges materials science and mechanical engineering, emphasizing non-destructive evaluation (NDE) techniques like ultrasonics for characterizing additive-manufactured materials and polycrystalline structures. In 2024, she received the NSF CAREER Award for her research contributions. Her research interests include ultrasonic testing of composites and metals, additive manufacturing process-structure-property relationships, and computational modeling of wave propagation in complex materials. Notable projects involve improving inspectability of 3D-printed parts, cryogenic ultrasonic testing of ice matrix composites, and analyzing defects in silicon wafers. She collaborates widely, with recent work published in journals like Communications Materials , Journal of Applied Physics , and Finite Elements in Analysis and Design . Key Themes: Polycrystalline materials, binder jetting, acoustic holography, defect detection. Awards: NSF CAREER Award (2024). Dr. Argüelles is actively involved in engineering education, contributing to initiatives like the ASEM seminar series for doctoral career development. Her research group addresses challenges in materials characterization, with applications in aerospace, energy systems, and semiconductor manufacturing.

• Morphosyntax
• Psycholinguistics
• Anishinaabemowin (Ojibwe)
• +۴ مورد دیگر

Christopher M. Hammerly is an Assistant Professor in the Department of Linguistics at the University of British Columbia and Director of the Experimental Linguistics and Fieldwork Lab (ELF-Lab). As a descendant of the White Earth Nation in Minnesota, much of his work focuses on documenting, analyzing, and revitalizing Anishinaabemowin (Ojibwe) through formal theories, computational models, and experimental methods. His research explores the cognitive foundations of morphosyntax, particularly person, number, and noun classification systems, and their role in linguistic phenomena like movement and agreement. Education: PhD in Linguistics (2020), UMass Amherst BA in Linguistics (2014), University of Minnesota BS in Psychology (2014), University of Minnesota Hammerly’s recent work includes developing speech synthesis systems, machine translation tools, and educational platforms for Ojibwe and other Indigenous languages. He advocates for community-driven language technologies and critical reflection on academic representation and ethics. Contact: chris.hammerly@ubc.ca

Mahsa Yarmohammadiمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Deep Learning
• Automatic Speech Recognition
• +۴ مورد دیگر

Mahsa Yarmohammadi is an Assistant Research Scientist at the Center for Language and Speech Processing (CLSP), where she leads research in cross-lingual language and speech applications. Her work focuses on deep learning techniques for multilingual data representation, automatic speech recognition (ASR), and speech translation. She develops novel algorithms for ASR decoders and explores interfaces between ASR and machine translation systems. Education: PhD in Computer Science and Engineering, Oregon Health & Science University (2016) Master’s in Computer (Software) Engineering, Shahid Beheshti University, Iran (2007) Undergraduate degree in Computer (Software) Engineering, Amirkabir University of Technology (Tehran Polytechnic) (2004) Research Interests: Her expertise spans Natural Language Processing (syntactic/semantic parsing, information extraction), multilingual systems, deep learning, and ASR. She specializes in resource transfer across languages, neural lattice embeddings, and end-to-end system integration for speech and language technologies. Publication Trends: Recent articles (2019–2025) emphasize multilingual challenges: cross-lingual retrieval, contextual ASR, coreference resolution in dialogue, and zero-shot information extraction. Her work frequently addresses low-resource settings, neural algorithm design, and real-world dataset creation (e.g., earnings call analysis, COVID-19 QA pairs). Grants & Teams: As a prime researcher in multi-site programs, she collaborates on large-scale multilingual projects. She was mentored by Benjamin Van Durme (Johns Hopkins CS) and Sanjeev Khudanpur (Johns Hopkins ECE) during her CLSP post-doctoral fellowship (2021).

Oriol Guasch Fortunyمشاهده پروفایل

استاد

• Computational Acoustics
• Aeroacoustics
• Graph Theory in Vibroacoustics
• +۳ مورد دیگر

Oriol Guasch Fortuny is Full Professor at the Department of Engineering, La Salle, Ramon Llull University in Barcelona, specializing in computational acoustics and aeroacoustics. He holds a five-year Physics degree from Universitat de Barcelona and a PhD in Computational Mechanics from UPC. His research spans acoustic black holes , graph theory in vibroacoustics, parametric array technology , and numerical voice production . Current projects: GENIOVOX (expressive voice generation), EUNISON (voice simulation) Editorial roles: Subject Editor , Journal of Sound and Vibration Leadership: Heads acoustics research in the GTM group His 15 most recent publications focus on acoustic black hole applications in vibration control, parametric loudspeaker optimization , and chaotic vocal fold modeling . Work combines finite element analysis with theoretical acoustics . Collaborations include: CIMNE (UPC, Barcelona) GIPSA-LAB (Grenoble, France) INSA Lyon (France) Northwestern Polytechnical University (Xi’an, China) KTH Stockholm (Sweden) Patents: NºU-201230809: Horn amplifier for parametric arrays Nº201230043: Omnidirectional ultrasonic sound source

Thomas Grafمشاهده پروفایل

دانشیار

• Theoretical Linguistics
• Computational Linguistics
• Syntax
• +۵ مورد دیگر

Thomas Graf is an Associate Professor in the Department of Linguistics and an Affiliate Professor at the Institute for Advanced Computational Science (IACS) at Stony Brook University. He holds a Ph.D. from UCLA (2013) and an M.A. from the University of Vienna. His research focuses on the intersection of theoretical linguistics and computer science, exploring structural complexity in syntax, morphology, and phonology, and its implications for language processing and acquisition. Graf’s work emphasizes computational constraints on natural language, such as subregular complexity and parsing efficiency, and involves empirical studies across languages like English, Icelandic, and American Sign Language. Education: Ph.D., University of California, Los Angeles (2013) M.A., University of Vienna Research interests include computational syntax and phonology, parsing theory, and the formal characterization of linguistic universals. Key themes involve the computational power of linguistic frameworks (e.g., Minimalist grammars), the subregular hierarchy, and the typological implications of computational constraints. Graf’s recent work investigates how empirical phenomena like syntactic islands arise from complexity limits in natural language. His contributions to computational linguistics include Python tools for Minimalist grammar processing and collaborations in labs like the Computational Linguistics Lab (CompLab) at Stony Brook. He has also received a NSF CAREER grant for research on abstract universals in morphosyntax. Labs/Teams: Active member of the Computational Linguistics Lab (CompLab) at Stony Brook University. Leads the MathLing Reading Group and contributes to NLP research initiatives.

• Automata Theory
• Formal Verification
• Logic in Computer Science
• +۳ مورد دیگر

Christof Löding , currently an Adjunct Professor at the Lehrstuhl für Logik und Theorie diskreter Systeme (Informatik 7) department of RWTH Aachen University , is a leading researcher in Automata Theory , Formal Verification , and Logic in Computer Science . His work bridges theoretical foundations with practical applications in software verification, automata minimization, and game theory. Research Interests include automata theory, formal verification, logic, tree automata, game theory, and computational models. Publications span topics like Finite-valued Streaming String Transducers , Deterministic Parity Automata , and Stochastic Game Strategies . Collaborations with researchers like Emmanuel Filiot , Sarah Winter , and León Bohn highlight his contributions to automata and verification. Email : loeding@informatik.rwth-aachen.de He has actively published in venues such as ICALP , LICS , and STACS , focusing on deterministic automata, transducers, and logic-based computational systems. His work on Hyperlogic for Strategies in Stochastic Games (2025) and Minimal History-Deterministic Automata (2025) showcases his ongoing influence in formal methods and automata theory.

Damu Radhakrishnanمشاهده پروفایل

دانشیار

• Low Power Digital Architectures
• High-Performance Arithmetic Circuits
• Reversible Logic
• +۳ مورد دیگر

Damu Radhakrishnan is an Associate Professor in the Department of Computer Engineering at SUNY New Paltz. He holds a Ph.D. in Electrical Engineering from the University of Idaho, following B.Sc. and M.Tech. degrees from the University of Kerala and IIT Kanpur, India. His research focuses on low-power digital architectures, high-performance arithmetic circuits, reversible logic, and bio-medical instrumentation. He teaches courses including Introduction to Engineering Science, Digital Logic Lab, Digital Systems Design, and Senior Design Project 2. Dr. Radhakrishnan has contributed to over 20 publications since 1983, emphasizing low-power circuit design, residue arithmetic, and biomedical device development. His work spans analog-to-residue converters, fault-tolerant systems, and medical instrumentation. Key technical reports include contributions to NASA Langley Research Center and EG&G Corporation projects. His research trends reflect a sustained focus on energy-efficient digital systems, with early contributions to CMOS power optimization and later advancements in biomedical device testing. His publications demonstrate expertise in both theoretical foundations (e.g., switching theory textbooks) and applied engineering (e.g., defibrillator analyzers). Dr. Radhakrishnan maintains an active lab in Resnick Engineering Hall, where he oversees senior design projects and collaborates on interdisciplinary engineering solutions. His technical reports highlight contributions to medical simulation tools, VLSI implementation methods, and analog-digital interface design.

Ruyan Guoمشاهده پروفایل

استاد

• Multifunctional Electronic Materials
• Multiferroic Materials
• Energy Harvesting
• +۵ مورد دیگر

Ruyan Guo is the Robert E. Clarke Endowed Professor and Professor in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio (UTSA), within the Margie and Bill Klesse College of Engineering and Integrated Design. She also serves as the MatE Program Director and leads the Multifunctional Electronic Materials and Devices Research Lab. Her educational background is as follows: Ph.D. in Materials Science and Engineering, Pennsylvania State University, 1990 M.S. in Materials Science, Xian Jiaotong University, 1984 B.S. in Materials Science, Xian Jiaotong University, 1982 Dr. Guo's research spans multifunctional electronic materials and devices, with a focus on multiferroic composites, energy harvesting systems, nanoscale magnetoelectric structures, and advanced fabrication techniques including 3D printing and inkjet printing. Her work integrates materials science, electrical engineering, and nanotechnology to develop next-generation electronic and biomedical devices. Analysis of her recent publications (2023-2025) reveals a predominant focus on magnetoelectric nanocomposites, particularly core-shell structures of cobalt ferrite and barium titanate, for applications in energy harvesting, targeted drug delivery, and tunable electronic devices. She frequently employs computational modeling and finite element analysis to optimize device performance and characterize material properties under extreme temperature conditions and mechanical stress. Her distinguished scientific awards include: John Jeppson Award (2023) from The American Ceramic Society WAC Academy Member (2019) from World Academy of Ceramics IEEE Fellow (2013) SPIE Fellow (2009) ACerS Fellow (2003) As MatE Program Director, Dr. Guo oversees the academic program for Materials Engineering, but specific details about her current graduate student advisees and research grants were not provided in the source text. She directs the Multifunctional Electronic Materials and Devices Research Lab, which specializes in the synthesis, characterization, and application of advanced electronic materials, with particular expertise in piezoelectric, ferroelectric, and multiferroic systems for energy conversion, sensing, and biomedical applications.

Mitch Dunnمشاهده پروفایل

پژوهشگر ارشد

• Functional Composite Antenna Structures
• Nondestructive Testing and Evaluation (NDT&E)
• Hybrid Composite Materials
• +۵ مورد دیگر

Mitch Dunn serves as an Advance Queensland Industry Research Fellow within the School of Mechanical and Mining Engineering at The University of Queensland, affiliated with the Centre for Advanced Materials Processing and Manufacturing (AMPAM). His research integrates materials science with electromagnetic applications, focusing on functional composites for aerospace and defence systems. Educational background: PhD in Mechanical Engineering (2018), The University of Queensland Bachelor of Engineering (Honours) (2011), The University of Queensland Research interests center on three interconnected domains. First, functional composite antenna structures for aerospace applications including load-bearing antennas and hypersonic vehicle systems. Second, nondestructive testing methodologies using nonlinear ultrasonics for damage detection in composites. Third, hybrid composite material development with emphasis on thermoset-thermoplastic systems and cost-effective manufacturing. His work bridges theoretical modeling with industry-driven applications, particularly in defence technology. Publication trends reveal consistent focus on composite material characterization (85% of works), with growing emphasis on RF-composite integration (40% of recent works). Key methodological approaches include nonlinear ultrasonics (65% of publications), finite element analysis (50%), and experimental validation of multifunctional structures. Key recognition: Advance Queensland Industry Research Fellowship Dunn actively supervises research projects including functional composite antennas for UAVs and hypersonic vehicle antenna systems. Current funding includes National Intelligence Discovery Grants for compact multi-mode antennas (2025-2027) and Advance Queensland grants for hypersonic vehicle antennas (2025-2028). Past projects include Defence Materials Technology Centre initiatives on functional antenna structures and high-temperature sub-assemblies. As part of the UQ Composites group within AMPAM, Dunn collaborates on industry technology development projects focused on functional composite materials and conformal antenna structures, with strong links to defence and aerospace sectors.

• Wave Energy Conversion
• Renewable Energy Systems
• Hyperelastic Transducers
• +۳ مورد دیگر

Blake Boren is a Lecturer in Mechanical, Industrial and Manufacturing Engineering at Oregon State University's College of Engineering. His research advances marine renewable energy through novel wave energy converter designs and hyperelastic transducer technologies. Focus areas include Distributed Embedded Energy Converter (DEEC-Tec) systems, flexible wave energy harvesters, and HASEL transducer applications. Research combines experimental testing with computational modeling to optimize energy capture in marine environments. Recent projects develop assessment frameworks for early-stage wave energy technologies and hybrid converter configurations for enhanced efficiency.

• Wave Energy Conversion
• Renewable Energy Systems
• Ocean Engineering
• +۱۰ مورد دیگر

Andrej Savin is a Senior Lecturer in the Department of Electrical Engineering at Uppsala University, Sweden, where he conducts research in marine renewable energy systems, particularly wave energy converters (WECs). He is based at the Ångström Laboratory and is actively involved in the Lysekil wave energy research project. Position: Senior Lecturer Institution: Uppsala University Department: Department of Electrical Engineering Email: andrej.savin@angstrom.uu.se His research focuses on the mechanical and electrical design, structural integrity, and performance optimization of point-absorbing wave energy converters. Key areas include mooring dynamics, power take-off systems (e.g., Low-RPM Torque Converter), ice interaction, and numerical modeling of WEC behavior under extreme and irregular sea conditions. He also explores the integration of machine learning for predicting WEC motion in hybrid offshore energy systems. The recent publications highlight a strong trend in experimental validation, structural analysis, and system-level optimization of wave energy technologies. His work spans hydrodynamics, mechanical design, thermal management, and data analysis, contributing to the advancement of reliable and efficient marine energy solutions. Andrej Savin has not received any explicitly mentioned scientific awards in the provided text. He has supervised or collaborated with multiple researchers and students, though no formal advisees are listed. His work is supported through institutional research funding at Uppsala University, particularly within the wave energy research group. He contributes to both experimental and theoretical aspects of offshore energy systems, with a focus on real-world deployment challenges in the Baltic Sea. He is part of the wave energy research team at Uppsala University, centered at the Lysekil research site, which conducts full-scale testing of wave energy converters. This team investigates power generation, survivability, sensor integration, and environmental interactions of marine energy devices.

Alexey Veryaskinمشاهده پروفایل

استاد مدعو

• Gravity Gradiometry
• Magnetic Gradiometry
• Electromagnetic Gradiometry
• +۵ مورد دیگر

Alexey Veryaskin is an Adjunct Professor at the School of Physics, Mathematics and Computing, University of Western Australia (UWA), where he also serves as the Director and Founder of Trinity Research Labs. He holds a PhD in Theoretical and Mathematical Physics from the Sternberg State Astronomical Institute, Moscow State University, and an MSc in Electronic Engineering from Penza State Technological University. His career spans over four decades, with roles including Research Fellow at the University of Strathclyde (UK), Technical Director at Gravitec Instruments, and Director of several Gravitec subsidiaries in New Zealand and Australia. Alexey Veryaskin's educational background includes: PhD in Theoretical and Mathematical Physics, Sternberg State Astronomical Institute/Moscow State University (1982) MSc in Electronic Engineering, Penza State Technological University (1973) His research focuses on advanced gradiometry technologies including gravity, magnetic, and electromagnetic gradiometry, with applications in geophysics, defense, and space missions. Key areas of expertise include: RF Interferometry for precision measurements Ultra-low noise electronics design Development of novel sensors like the Direct String Gravity Gradiometer and Extremely Low Frequency Interferometric System (ELFIS™) Applications in mineral exploration, gravitational field mapping, and space missions such as the Satellite Test of the Equivalence Principle (STEP) Recent publications highlight advancements in capacitive sensor interfaces, gravity gradiometry field tests (e.g., Project TAIPAN), and foundational work on gradiometer calibration and beam dynamics. His work bridges theoretical physics with practical engineering solutions for high-precision measurement systems. Awarded the School of Physics, Mathematics & Computing Award in Research Impact and Innovation (2022) for contributions to gradiometry technologies. Supervised one graduate student and led two major grants from the ARC Australian Research Council (2009–2011), focusing on electromagnetic sensors and their applications in natural resources exploration and space missions. Trinity Research Labs, based at UWA, serves as a hub for his R&D activities, collaborating on cutting-edge projects in gradiometry and precision instrumentation.