جست‌وجوی استاد و پژوهشگر

• Coding Theory
• Network Coding
• Information Theory
• +۴ مورد دیگر

Chih-Chun Wang is a Professor at the Elmore Family School of Electrical and Computer Engineering , Purdue University, with additional leadership roles as Associate Head for Facilities, Planning, and Staff. He earned his Ph.D. in Information Sciences and Systems from Princeton University in 2005, following an M.S. (2002) and B.S. (1999) in Electrical Engineering from Princeton and National Taiwan University, respectively. Research Interests: His work spans Network coding (graph-theoretic capacity, wireless network coding, feedback mechanisms) Coding theory (LDPC codes, Reed-Solomon decoding, iterative algorithms) Information theory (multi-user detection, network information theory) Signal processing (turbo equalization, space-time codes) Control theory (optimal stopping theory) Scientific Contributions: He has published extensively on Age-of-Information (AoI) minimization, low-latency coding, and multi-hop relay optimization. His research trends include Integrating machine learning with network coding Wireless security for Beyond-5G systems Distributed storage networks with intelligent helper selection Delay-constrained communication protocols Awards: Recognized as an IEEE Fellow in 2024 for contributions to network coding and information theory. Teaching: He teaches undergraduate courses like ECE301: Signals and Systems and graduate courses such as ECE639: Error Control Coding , with a focus on iterative decoding, LDPC codes, and network information theory. Advising: Supervised 15+ Ph.D. students, including current advisees Pin-Wen Su (delay-oriented coding), Wonjun Lee (cyber-physical systems), and Giles Bischoff (low-latency systems). Former students hold prominent roles at institutions like Google, Meta, and Intel.

Hermann Cuntzمشاهده پروفایل

پژوهشگر

• Neuroscience
• Computational Neuroscience
• Neuroinformatics
• +۴ مورد دیگر

Dr. Hermann Cuntz is an Independent Group Leader at the Ernst Strüngmann Institute (ESI) for Neuroscience in cooperation with the Max Planck Society. He is also a Research Fellow at the Frankfurt Institute for Advanced Studies (FIAS) since 2014 and affiliated with the Goethe University Frankfurt via the Institute of Clinical Neuroanatomy . His email address is hermann.neuro@gmail.com , and he is based in Frankfurt am Main, Germany. Research Focus: Dr. Cuntz investigates principles of neuronal wiring, aiming to decode the "connection code" of the brain. His work bridges morphology and function using computational tools, mathematical laws, and morphological modeling. Key areas include dendritic constancy , structural plasticity , connectomics , and neuroinformatics , with applications in understanding neurodegenerative diseases like Alzheimer’s. Education: PhD from the University of California at Berkeley and Max Planck Institute of Neurobiology (2000-2004). Diploma in biology from Eberhard Karls Universität Tübingen (1994-2000). Recent Publications highlight research trends in dendritic structure, pattern separation, synaptic spine distribution, and cortical folding. His lab develops the TREES Toolbox , a MATLAB-based framework for neuronal morphology analysis. Scientific Awards: Bernstein Award (2013-2019) DFG Eigene Stelle (2014-2016) Feodor Lynen Fellowship (Alexander von Humboldt, 2006-2008) Minerva Fellowship (2004-2005) Wellcome Image Award (2011) 1st Prize Poster Competition, UCL Neuroscience Symposium (2010) Advising and Grants: Dr. Cuntz mentors numerous PhD and Master’s students, including Marcel Beining , Mariuss Schneider , and Marvin Weigand . His lab receives funding from the DFG , Bernstein Award , and collaborations with institutions like the 3R-Center Giessen and Interdisciplinary Centre for 3Rs (ICAR3R) . Labs and Collaborations: The Cuntz Lab specializes in computational neuroanatomy, with alumni working globally in academia and industry. Key collaborators include Prof. Peter Jedlicka (Justus Liebig University), Prof. Gaia Tavosanis (DZNE Bonn), and Prof. Alexander Borst (MPI Neurobiology).

Víctor Adrián Brabermanمشاهده پروفایل

دانشیار

• Formal Verification
• Model Checking of Timed Systems
• Controller Synthesis
• +۷ مورد دیگر

Víctor Adrián Braberman is a Full-time Associate Professor at the Department of Computer Science, Faculty of Exact and Natural Sciences, University of Buenos Aires (UBA), and a CONICET researcher. He serves as Co-director of the LaFHIS (Tools and Foundations for Software Engineering) Research Lab at UBA, where he leads significant research in formal methods and software engineering. His academic career demonstrates sustained excellence in both teaching and research within Argentina's premier academic institution. Braberman's research focuses on Formal Verification , particularly Model Checking of Timed Systems, Controller Synthesis, Formal Specification of event-based properties, Aspect-oriented modeling, and Software Architectures. His work also extends to Software Analysis , including Memory Consumption Prediction and Static and Dynamic Program Analysis. These interests position him at the intersection of theoretical computer science and practical software engineering applications, addressing critical challenges in system reliability and performance. His recent publications (2022-2025) reveal a clear trajectory toward integrating artificial intelligence with formal methods , particularly through the application of reinforcement learning to controller synthesis problems and the exploration of Large Language Models for software verification and falsification. The research shows increasing attention to scalability challenges in formal methods and the integration of probabilistic approaches to handle uncertainty in system environments. Automated Reasoning Amazon Research Award (ARA) (2024) Braberman has successfully supervised numerous PhD and Licentiate students, establishing a strong academic lineage in formal methods research in Argentina. His research has been supported by substantial grants including European Community projects (MEALS), ANPCyT PICT grants, UBACyT projects, and Microsoft Research funding. His leadership extends to directing major research initiatives in formal software engineering. As Co-director of LaFHIS, Braberman oversees a vibrant research ecosystem that bridges theoretical computer science with practical software engineering challenges. The lab maintains strong international collaborations, particularly with European institutions, and has secured competitive funding from both national and international sources, demonstrating the global relevance of their work in formal methods and software engineering.

Blerim Rexhaمشاهده پروفایل

استاد

• Cybersecurity
• Blockchain Technology
• Machine Learning
• +۵ مورد دیگر

Prof. Blerim Rexha is a full professor at the University of Prishtina's Faculty of Electrical and Computer Engineering, Kosovo. With a Ph.D. in Computer Engineering from Vienna University of Technology (2004), he has led research in cybersecurity, blockchain, machine learning, and electronic voting systems. His teaching portfolio includes data, computer, and internet security courses. Education : Ph.D. in Computer Engineering (Vienna), Electrical Engineer MSc (Prishtina), specialized certifications in software engineering, biometrics, and .NET programming. His research spans cybersecurity (DDoS mitigation, face authentication attacks), blockchain applications (electronic voting bridges, transaction privacy), and machine learning integration (boosted trees for intrusion detection, LSTM for vulnerability scanning). He has contributed to cloud security through novel encryption methods and AI-driven attack detection. Recent publications focus on energy efficiency in cloud vs on-premises systems, XGBoost/CatBoost/LightGBM comparisons for network security, and blockchain bridges for e-voting. His work has addressed privacy preservation in video data, SMS encryption, and eID card pseudo-profiles. Awards include the 2024 Marin Barleti Prize for academic contributions and Best Paper Awards in election security (2015) and Kosovo website vulnerabilities (2013). Honors : Marin Barleti Prize (2024) Cyber Security Ambassador (2018) ICT Academician of the Year (2016) Best Paper Awards (2015, 2013) As academic advisor to the KosovaCyberTeam , he mentors students like Korab Keqekolla and Abian Morina. His leadership extends to Kosovo's Cyber Security State Training Center curriculum development and jury roles in Albanian ICT Awards .

Arto Anttilaمشاهده پروفایل

دانشیار

• Phonology
• Morphology
• Syntax
• +۲ مورد دیگر

Arto Anttila is an Associate Professor in the Department of Linguistics at Stanford University and holds an Adjunct Professor (dosentti) position in General Linguistics at the University of Helsinki. His research spans multiple linguistic subfields with particular focus on the interfaces between phonology, syntax, and prosody. Dr. Anttila's research interests include phonology, morphology, syntax, metrics, and language variation. His work often explores how phonological constraints interact with syntactic structures and how variation manifests across different linguistic domains. He has made significant contributions to Optimality Theory, MaxEnt grammar, and probabilistic approaches to phonology. His recent publications demonstrate a strong focus on metrical patterns, stress systems, syllable structure, and the relationship between prosody and syntax. Anttila frequently collaborates with researchers like Giorgio Magri, Adams Bodomo, and Ryan Heuser, examining phenomena across diverse languages including English, Finnish, and Dagaare (an African language). Anttila has developed several computational tools for linguistic research, including CoGeTo (Convex Geometry Tools for constraint-based phonology), MetricalTree (for English phrasal stress prediction), Prosodic (for automatic metrical scansion), T-Order Generator, and OTOrder. These tools reflect his interest in the mathematical and computational aspects of linguistic theory.

• Semiconductor Physics
• Microwave Engineering
• Cryogenic Electronics
• +۳ مورد دیگر

Niklas Rorsman is a Research Professor at the Microwave Electronics group, part of the Department of Microtechnology and Nanoscience at Chalmers University of Technology . His work focuses on advanced semiconductor devices, particularly gallium nitride (GaN) and silicon carbide (SiC) high-electron-mobility transistors (HEMTs) for microwave and cryogenic applications. Expertise : Semiconductor device physics, microwave electronics, cryogenic transistor characterization Key Technologies : GaN HEMTs, SiC MESFETs, graphene FETs Rorsman's research investigates trapping effects, thermal management, and material optimization in GaN/SiC devices. Recent studies explore field plates for cryogenic stability, recessed ohmic contacts, and high-κ dielectric interfaces. His publications demonstrate a focus on improving device linearity, noise performance, and reliability through structural and process innovations. Selected trends in his work include: Cryogenic GaN HEMTs with superconducting Nb gates Buffer-free AlGaN/GaN heterostructures for high breakdown voltage Graphene integration for millimeter-wave communication systems Advanced SiNx passivation and gate stack engineering Contact: niklas.rorsman@chalmers.se

Rasmus Paghمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Big Data
• +۷ مورد دیگر

Rasmus Pagh is a Professor at the Department of Computer Science, University of Copenhagen, specializing in algorithms and complexity. His career includes a 2002 PhD from Aarhus University under Peter Bro Miltersen and a tenure at IT University of Copenhagen until 2020. He leads theoretical research with practical applications in big data, databases, and modern computer architecture parallelism. His research interests span algorithms, data structures, and privacy-preserving computing. Recent work includes the ERC-funded project on Scalable Similarity Search and contributions to the BARC center for basic algorithms research. He has collaborated with Google Research (2019-2020) and focuses on theoretical foundations with real-world impact. Key research trends in his 2023-2024 publications include privacy-preserving data analysis probabilistic data structures distributed secure computation noise-robust coding hashing efficiency continual privacy mechanisms Scientific recognition includes 2024 ACM Fellowship ERC grant leadership multiple top-tier conference publications

Mohamed S. El-Genkمشاهده پروفایل

استاد

• Nuclear Engineering
• Thermal-Hydraulics
• Space Nuclear Power Systems
• +۱۲ مورد دیگر

Mohamed S. El-Genk is a Regents’ Professor and Distinguished Professor in the Department of Nuclear Engineering, Mechanical Engineering, and Chemical & Biological Engineering at the University of New Mexico (UNM). He also serves as Founding Director of the Institute for Space and Nuclear Power Studies (ISNPS) and is affiliated with the Configurable Space Microsystems Innovations & Applications Center (COSMIAC). Education: Ph.D. in Nuclear Engineering (UNM, 1978), M.S. in Nuclear Engineering (University of Alexandria, 1975), B.S. in Nuclear Engineering (University of Alexandria, 1968) His research spans nuclear reactor thermal-hydraulics, space nuclear power systems, energy conversion, heat pipes, boiling heat transfer, two-phase flow, radiation shielding, and molecular dynamics modeling of nuclear materials. He has pioneered thermal management solutions for terrestrial and space applications. The 15 most recent publications focus on reactor design optimization (e.g., SLIMM-1.2, VSLLIM), heat transfer correlations in microchannels and helically coiled tubes, radiation damage modeling, and thermal-hydraulics of modular and lunar reactor systems. These works reflect his expertise in nuclear materials, CFD simulations, and energy conversion technologies. Scientific Awards: 2017 ASME Heat Transfer Memorial Award, 2015 ANS Thermal-Hydraulics Technical Achievement Award, AIChE Donald Q. Kern Award (2009), ANS Fellow (1996), ASME/AIChE Max Jacob Award Committee Chair (2005-06) El-Genk has supervised over 60 graduate students (30 Masters, 32 Doctoral) and contributed to 380+ refereed papers. He leads the development of global standards for space nuclear reactors and serves on editorial boards for journals including Thermal Science and Engineering Progress and Energy Conversion and Management .

Kelly Bijankiمشاهده پروفایل

دانشیار

• Neuromodulation
• Affective neural circuits
• Electrophysiology
• +۹ مورد دیگر

Kelly Bijanki is an Associate Professor of Neurosurgery, Director of Intracranial Monitoring Research, and holds joint appointments in Psychiatry and Neuroscience at Baylor College of Medicine. Her work bridges clinical neurosurgery and neuroscience, focusing on understanding the neural basis of affective disorders and developing neuromodulation therapies. She directs the Translational Neuromodulation Lab, where she leverages stereotactic electroencephalography (sEEG) to study deep brain structures critical to emotional functioning. Dr. Bijanki's research explores the electrophysiological, neurobiological, and behavioral correlates of neuromodulation of affective neural circuits. Her lab primarily works with patients undergoing intracranial monitoring for epilepsy or depression, using this unique platform to conduct in-vivo studies of neural correlates to affective function. Her work has identified novel stimulation-based strategies for evoking positive affect and anxiolysis, including the discovery that stimulation to the cingulum bundle evokes changes in anxiolysis, mirth, and euphoria, which was featured as a cover article in the Journal of Clinical Investigation and highlighted in the NIH Director's Blog. Analysis of her recent publications reveals a consistent focus on mapping neural circuits involved in emotion processing, particularly using stereo-EEG informed deep brain stimulation approaches. Her work spans multiple psychiatric conditions including depression, obsessive-compulsive disorder, and anxiety disorders, with a strong emphasis on translating electrophysiological findings into therapeutic applications. The integration of computational approaches, particularly machine learning for decoding neural activity related to mood states, represents a growing trend in her research program. Her scientific achievements include: United States Patent (US:11,241,575) for a novel stimulation-based strategy for evoking positive affect and anxiolysis Journal of Clinical Investigation cover article (March 2019) on cingulum stimulation enhancing positive affect NIH Director's Blog feature highlighting her groundbreaking work Multiple NIH grants including R01, R21, and K01 awards Dr. Bijanki mentors a diverse team including graduate students, postdoctoral fellows, and undergraduate researchers. Her research program is generously funded by multiple NIH grants (R01-MH127006, R01-MH130597, K01MH116364, R21NS104953, UH3NS103549), as well as support from the ARCO Foundation, Caroline Wiess Law Fund, American Foundation for Suicide Prevention, and NARSAD. She maintains strong collaborations with researchers at institutions including UTSW, Iowa, Duke, UCLA, Brown, UPenn, and WashU. The Translational Neuromodulation Lab operates at the intersection of clinical neurosurgery, neuroscience, and engineering, utilizing stereo-EEG as a research platform to study deep brain structures involved in emotional processing. The lab employs multiple methodologies including advanced surgical neuroimaging, affective electrophysiology, autonomic surveillance, facial motor analysis, and pulse-evoked potentials to comprehensively characterize mood-relevant neural circuits. Their current flagship project involves using explainable artificial intelligence to map the relationship between mood and intracranial neural activity, with the goal of developing naturalistic patterns of intracranial stimulation for therapeutic applications.

• Algorithmic Databases
• Data Mining
• Computational Geometry
• +۵ مورد دیگر

Stavros Sintos is an Assistant Professor in the Department of Computer Science at the University of Illinois at Chicago (UIC). He joined UIC after a postdoctoral fellowship at the University of Chicago, where he was part of the ChiData group under Sanjay Krishnan. He earned his Ph.D. in Computer Science from Duke University in 2020, advised by Pankaj K. Agarwal. His research focuses on designing efficient algorithms for databases, data mining, and computational geometry . Key themes include: Theoretical guarantees for practical problems Compact indexing structures for query efficiency Geometric optimization combined with database systems Fairness in algorithmic design (e.g., Fair Set Cover, FairHash) Temporal data analysis and dynamic query processing Notable scientific contributions include a Best Paper Award at ICDT 2024 for work on range entropy queries. His publications span top venues like SIGMOD, PODS, VLDB, and SODA, covering areas such as clustering algorithms, synthetic query witnesses, and temporal join optimizations.

Sandy Iraniمشاهده پروفایل

استاد

• Quantum Computing
• Algorithm Design
• Computational Complexity Theory
• +۵ مورد دیگر

Sandy Irani is a Full Professor at the University of California, Irvine (UCI) in the Department of Computer Science within the Donald Bren School of Information and Computer Sciences. She received her Ph.D. from UC Berkeley in 1991 and has been at UCI since 1992. Her research focuses on algorithm design, computational complexity theory, and quantum computing, with notable contributions to online algorithms and quantum complexity theory. She currently serves as Associate Director of the Simons Institute for the Theory of Computing at UC Berkeley, a role she has held since 2022. This position allows her to collaborate with researchers across theoretical computer science and related disciplines. Irani’s teaching excellence is recognized through the UCI Distinguished Faculty Award for Teaching (2021), and she has contributed to education through her zyBook on Discrete Mathematics, used by over 94,000 students globally. Her work bridges foundational computer science with practical applications, including power management strategies and distributed computing algorithms. Notably, she has collaborated with industry leaders like Mike Luby on optimizing distributed systems. Her research in quantum computing explores computational problems inspired by condensed matter physics, aiming to understand quantum advantage over classical systems. She has also authored influential papers on topics like cache hierarchy design, scheduling algorithms, and the theoretical limits of electronic structure calculations. Awards: ACM Fellow (2022), UCI Distinguished Faculty Award for Teaching (2021). Key Roles: Associate Director, Simons Institute; Vice Chair, Computing Division at UCI. Recent Projects: Quantum algorithms for condensed matter systems, maximal independent set algorithms in distributed networks.

Antje Heinrichمشاهده پروفایل

مدرس ارشد

• Speech Perception
• Auditory Processing
• Hearing Loss
• +۴ مورد دیگر

Dr Antje Heinrich is a Senior Lecturer in Audiology/Hearing Science at the University of Manchester, affiliated with the Division of Psychology Communication and Human Neuroscience (L5). Her research focuses on understanding how different groups of listeners process speech, including younger/older native English speakers, non-native listeners, and those with hearing loss. Key research areas include listening effort, cognitive-auditory interactions, and translating findings into clinical diagnostics/training. Education: PhD (University of Toronto, 2005), MSc (Technische Universität Dresden, 2001), MA (University of Toronto, 2000). Previous roles include positions at the MRC Institute of Hearing Research (2011–2017), University of Cambridge (2008–2010), and the MRC Cognition and Brain Sciences Unit (2005–2007). Research emphasizes speech perception mechanisms, auditory processing, and hearing loss impacts. Recent work explores data standards in audiology and health informatics applications. Collaborations span international teams and interdisciplinary fields like cognitive science and public health. Advising: Supervised 3 research projects. Part of the Manchester Centre for Audiology and Deafness (ManCAD), contributing to hearing impairment research and clinical translation.

Ed Pickeringمشاهده پروفایل

مدرس ارشد

• Metallurgy
• Materials Science
• Nuclear Engineering
• +۹ مورد دیگر

Ed Pickering is a Senior Lecturer in Metallurgy and Materials Engineering at the University of Manchester. He has held roles since 2015, advancing to Reader in 2023. His affiliations include the Henry Royce Institute (Research Area Lead for Advanced Metals Processing), the Advanced Metallics System CDT and Fusion CDT Management Boards, and industrial technical advisory panels. Ed’s work bridges academic and industrial collaboration with Rolls-Royce, UKAEA, Airbus, EDF, and Sheffield Forgemasters. Ed completed his undergraduate studies (2011) and PhD (2014) in Materials Science at the University of Cambridge, followed by a Research Associate role in Cambridge’s Rolls-Royce UTC. His academic trajectory includes: Senior Lecturer (2019–present) Reader (2023–present) Ed’s research focuses on phase transformations, microstructural characterization, and alloy development for nuclear (fission/fusion) and aerospace applications. Key themes include optimizing processing routes to enhance material properties while minimizing waste and environmental impact. His studies frequently address steel, high-entropy alloys, and novel refractory alloys, emphasizing their service performance under extreme conditions. His scientific contributions span structural integrity assessment of welded joints, machine learning applications in metallurgy, and material flow uncertainties in forging. He has also advanced heat treatment optimization for reactor steels and explored cobalt-free hardfacing alloys. Frank Fitzgerald Medal (2017) Grunfeld Memorial Medal (2021) In advising and grants, Ed leads the Materials Performance Centre (MPC) and co-leads the NEWAM project on wire-additive manufacturing. He supervises research across these initiatives and collaborates with over 30 PGR students in interdisciplinary teams. His work also involves managing technical facilities like the Advanced Metal Processing platform. Ed’s laboratory affiliations include the MPC and WAAM-based Engineering and Process Metallurgy groups, where he explores sustainable materials solutions for energy and aerospace industries.

Soufiene Djahelمشاهده پروفایل

استاد

• Connected and Autonomous Vehicles (CAVs)
• Unmanned Aerial Vehicles (UAVs)
• Cyber Security
• +۷ مورد دیگر

Soufiene Djahel is a Professor at the Centre for Future Transport and Cities (CFTC) at Coventry University, UK. His research focuses on connected and autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), cyber security, and smart cities. He holds a PhD in Secure Routing and Medium Access Protocols from Université des Sciences et Technologies de Lille (2010), and has held academic positions including Senior Lecturer at the University of Huddersfield and Manchester Metropolitan University. His research interests include CAV coordination protocols, cyber-physical security solutions, and intelligent transportation systems. Djahel leads projects such as the £1.2M AeroPharma Logistics initiative and has secured funding from the Newton Fund and JSPS. He is a recipient of the 2021 JSPS Invitational Fellowship and has published extensively in IEEE journals and conferences. Current projects explore UAVs-as-a-service, digital twins for CAVs, and B5G/6G for smart infrastructure. He advises PhD students on topics like AI-based threat mitigation and transport electrification. Djahel also serves as an external examiner and editorial board member for journals like IEEE Transactions on Intelligent Transportation Systems.

Janki Bhimaniمشاهده پروفایل

استاد

• Emerging Memories
• Flash-Based Storage Systems
• Machine Learning
• +۷ مورد دیگر

Janki Bhimani is a Professor and Director of the Data Management Research Lab (DaMRL) at the School of Computing and Information Science, Florida International University (FIU). Her research focuses on Memory and Storage Systems, Cloud Computing, Performance Modeling, and Applied Machine Learning. She holds a Ph.D. in Computer Engineering from Northeastern University (2019), an M.S. in Electrical and Computer Engineering (2016), and a B.S. in Electrical and Electronics Engineering from GITAM University (2013). Prior to FIU, she taught at Northeastern University and collaborated with Samsung Semiconductor Research Labs on flash-based SSDs. Her research interests include emerging memory technologies, high-performance computing, and datacenter reliability management. She leads innovative projects like Heimdall (machine learning for storage I/O optimization) and MoKE (modular key-value storage emulation). Awards include FIU Top Scholar and KFSCIS Excellence in Applied Research. Teaching highlights include CIS 3530 (Data Structures), CIS 5346 (Storage Systems), and EECE 2560 (Engineering Algorithms). Her work emphasizes bridging theory and practice, with patents on storage system optimization and machine learning integration.