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Mahdi Jafari SiavoshaniView profile

Assistant Professor

• Machine Learning
• Optimization
• Data Science
• +14 more

Mahdi Jafari Siavoshani is an Assistant Professor in the Department of Computer Science and Engineering at Sharif University of Technology, where he leads the Information, Network, and Learning (INL) Lab. He holds a PhD and MSc from the Swiss Federal Institute of Technology (EPFL), and a BSc in Electrical Engineering and Physics from Sharif University of Technology. Prior to his current role, he was a postdoctoral fellow at the Institute of Network Coding, The Chinese University of Hong Kong. His research spans fundamental problems in information processing, transmission, and analysis, with a focus on theoretical limits and practical algorithm design. Key areas include Machine Learning, Optimization, Data Science, Information and Communication Theory, and Computer Networks. His work integrates probabilistic modeling, network coding, and deep learning to address challenges in secure communication, traffic classification, and distributed systems. The recent publications highlight a strong trend in network coding, information theory, and machine learning applications. His work explores coding-theoretic solutions for secrecy, load balancing in cache networks, belief propagation algorithms, and encrypted traffic classification using deep learning. These contributions reflect a blend of theoretical depth and practical relevance in modern communication systems. Assistant Professor, Department of Computer Science and Engineering, Sharif University of Technology PhD and MSc, Swiss Federal Institute of Technology (EPFL) BSc in Electrical Engineering and Physics, Sharif University of Technology Postdoctoral Fellow, Institute of Network Coding, The Chinese University of Hong Kong He advises research in the INL Lab and teaches courses such as Computer Networks, Engineering Probability and Statistics, Network Coding, and Stochastic Processes. While no formal students are listed, his lab environment fosters collaborative research. There is no mention of external grants or funding in the provided texts. The INL Lab serves as the primary research unit, focusing on information theory, network algorithms, and machine learning applications. The lab integrates theoretical research with practical implementations, particularly in networked systems and data analysis.

Keith PurpuraView profile

Associate Professor

• Visual Neuroscience
• Systems Neuroscience
• Computational Neuroscience
• +5 more

Keith Purpura is an Associate Professor of Neuroscience at Weill Cornell Medicine's Brain and Mind Research Institute. He has maintained a continuous academic appointment since 1993, progressing from Assistant Professor to Associate Professor in 2000. His research spans two primary areas of neuroscience: the role of eye movements in visual cortical processing and the therapeutic application of thalamic deep brain stimulation for cognitive disorders. Dr. Purpura received his Ph.D. from The Rockefeller University in 1988 under Drs. Robert Shapley and Ehud Kaplan, followed by post-doctoral work with Dr. Jonathan Victor at Cornell University Medical College and a visiting scientist position at the NIH's National Eye Institute (1991-1993). His undergraduate studies spanned Mannes College of Music, New York University, and Columbia College. His laboratory investigates how eye movements influence neural activity patterns across the visual cortical hierarchy, hypothesizing that these movements generate and access communication channels across cortical areas. Concurrently, in collaboration with Dr. Jonathan Baker, he develops deep brain stimulation techniques targeting the central thalamus to treat disorders of consciousness following traumatic brain injury, which affects over 2 million Americans annually. Analysis of his publication record reveals consistent focus on neural network dynamics, visual processing mechanisms, and translational applications of brain stimulation. His work bridges computational neuroscience with clinical applications, particularly in understanding how cortical networks process visual information and how brain stimulation can restore cognitive function. Searle Award (Post-doctoral support) Charles H. Revson Foundation (Post-doctoral support) McDonnel-Pew Research Program in Cognitive Neuroscience Award Visiting Scientist, National Eye Institute, NIH: 1991-1993 NIH NINDS-K04 Career Development Award 17 summers of research at Marine Biological Laboratory, Woods Hole Dr. Purpura currently serves as Principal Investigator on an NIH National Eye Institute grant (2022-2026) studying eye movements in visual processing networks and as Co-Principal Investigator on an NINDS grant (2020-2025) for central thalamic deep brain stimulation. His laboratory includes collaborators Jonathan L. Baker and Jae-Wook Ryou, and he established both the alert primate physiology laboratory and visual neurophysiology laboratory at Weill Cornell.

• Applied Optimization
• Wireless Internet of Things
• Machine Learning
• +6 more

Carlo Fischione is a Full Professor at KTH Royal Institute of Technology in the School of Electrical Engineering and Computer Science, Division of Network and Systems Engineering, Stockholm, Sweden. He is a Fellow of IEEE, KTH Digital Futures, and the Italian Academy DASP, and a Distinguished Lecturer of the IEEE Communications Society. He holds a PhD and Laurea (Summa cum Laude) in Engineering from the University of L’Aquila, Italy, and has held research positions at MIT, Harvard, and UC Berkeley. PhD in Electrical and Information Engineering, University of L’Aquila (2005) Laurea in Electronic Engineering, Summa cum Laude, University of L’Aquila (2001) His research focuses on applied optimization, wireless Internet of Things, and machine learning , with particular emphasis on federated learning, over-the-air computation, and spectrum sharing in 5G/6G networks. He leads a vibrant research group and has supervised numerous PhD and postdoctoral researchers, many of whom now hold faculty or senior research positions globally. His recent publications reflect a strong trend toward machine learning in distributed and resource-constrained networked environments , especially focusing on communication efficiency, privacy, and scalability. Key themes include federated learning over fading channels, over-the-air computation, and AI-aided wireless channel prediction. IEEE Fellow IEEE Distinguished Lecturer, Communications Society IEEE Communication Society S. O. Rice Award (2018) Best Paper Award, IEEE Transactions on Industrial Informatics (2007) Starting Grant, Swedish Research Council (2008) Prof. Fischione has advised numerous students who have gone on to prominent academic and industry roles. He has secured significant research funding from the Swedish Research Council, SSF, KAW Foundation, Vinnova, and EU Horizon programs, leading projects such as MALEN, SAICOM, TAIRCOMP, and WIDCOMP. He is also the founding General Chair of IEEE ICMLCN and a co-founder of ELK.Audio, demonstrating strong industry and innovation engagement. He leads multiple research initiatives and labs focused on networked machine learning, including groups working on federated learning, wireless AI, and edge intelligence. His team actively contributes to advancing the theoretical and practical foundations of machine learning over networks.

Phillip HellwegeView profile

Professor

• History of Commercial Law
• Insurance Law
• German Civil Law
• +2 more

Prof. Dr. Phillip Hellwege, M.Jur. (Oxford), is the Chair of Civil Law, Commercial Law, and Legal History at the Faculty of Law, University of Augsburg. His research focuses on the historical and comparative analysis of insurance law, German civil law, European private law, and historical comparative law. He has led significant projects, including a 2015–2021 ERC Consolidator Grant-funded study on the comparative history of insurance law in Europe. Chair of Civil Law, Commercial Law and Legal History Principal Investigator, ERC Consolidator Grant (2015–2021) Teaching in Winter Semester 2025/26: Seminar on the History of Commercial Law Research Interests: Hellwege specializes in the history of commercial law (particularly insurance law), German civil law, European private law, and historical comparative law. His work bridges dogmatic legal analysis with historical context, emphasizing German and English law while exploring mixed systems like Scottish and Channel Islands law. Publications & Lectures: Recent works include a 2025 monograph on negligent ignorance in private law and 2024–2025 book chapters on precedent in German private law and negative freedom of contract in medical contexts. He actively presents at international colloquia, such as the 2025 lecture on early modern health care at Frauenwörth Abbey. Scientific Awards: Recognized with an ERC Consolidator Grant for his insurance law research and supervising dissertations that have won prizes like the Arnecke Sibeth Dabelstein Dissertation Prize. Academic Leadership: He supervises doctoral candidates in German civil law, historical comparative law, and European private law, with completed theses covering topics such as banking regulation, life insurance law, and comparative marine insurance. His team includes academic counselors and student assistants supporting research and teaching activities.

Victoria KostinaView profile

Professor

• Information Theory
• Coding Theory
• Wireless Communications
• +4 more

Victoria Kostina is a Professor of Electrical Engineering and Computing and Mathematical Sciences at the California Institute of Technology (Caltech). Her research bridges information theory , coding theory , and wireless communications , with a focus on the nonasymptotic regime to understand fundamental limits of delay-constrained systems. Bachelor's, Moscow Institute of Physics and Technology Master's, University of Ottawa PhD, Princeton University Her work explores the intersection of random processes , concentration of measure , and control theory to develop theoretical frameworks for modern communication systems. She has pioneered techniques for finite blocklength information theory and feedback communication , analyzing stability and performance in stochastic environments. Victoria's publications span channel coding , source-channel coding , and control with communication constraints , with a focus on practical applications in real-time systems . Her research has advanced the understanding of data compression , error exponents , and quantization in nonasymptotic scenarios. Notable scientific recognitions include: Princeton Electrical Engineering Best Dissertation Award (2013) NSF CAREER Award (2017) J. K. Wolf ISIT Student Paper Award Finalist (2021) She actively supervises students in the Computing and Mathematical Sciences (CMS), Control and Dynamical Systems (CDS), and Electrical Engineering (EE) PhD programs and leads the development of the SPECTRE Toolbox for finite blocklength information theory.

• Quantum Communications
• Next-generation Wireless Transmissions
• Channel Coding and Modulation
• +8 more

Prof Soon Xin Ng (Michael) is a Professor of Next Generation Communications at the University of Southampton , affiliated with the School of Electronics and Computer Science. His work bridges quantum communications, wireless technologies, and machine learning, with a focus on the theoretical and practical challenges of next-generation networks. Education: B.Eng. (First Class) in Electronic Engineering and Ph.D. in Telecommunications, both from the University of Southampton Current Roles: ECS Doctoral Programme Director since 2021, IEEE Quantum Communications & Information Technology Emerging Technical Subcommittee Officer Research Interests span quantum communications, channel coding/modulation, cooperative systems, and AI-driven wireless solutions. Recent projects include quantum key distribution over THz channels, UAV path planning with reinforcement learning, and MIMO-OFDM optimization. 2025: 3D spatial compression for UAV navigation 2025: OTFS modulation in quantum THz channels 2024: CV-QKD reconciliation and quantum internet evolution Scientific Awards include the 2013 Dean’s Award for publication excellence, IEEE Senior Membership, and Fellowships from the IET and Higher Education Academy. As an author of 260+ papers and co-editor of Quantum Engineering , he mentors eight active PhD students in electronic and engineering disciplines.

Pawel MordakaView profile

Researcher

• Plant Metabolism
• Synthetic Biology
• Chloroplast Engineering
• +3 more

Dr. Pawel Mordaka is a Postdoctoral Research Associate in the Department of Plant Sciences at the University of Cambridge. His research focuses on synthetic biology, genetic engineering, and plant metabolism, with a particular emphasis on chloroplast engineering and metabolic pathway optimization in model organisms like Chlamydomonas reinhardtii and Clostridium . Department: Plant Sciences Academic Rank: Researcher Email: pmm63@cam.ac.uk His work spans synthetic biology tool development (e.g., CpPosNeg selection systems, Start-Stop DNA assembly), transgene regulation in chloroplasts, and bioengineering of microbial-plant interactions. Recent publications highlight advancements in genetic code compression, promoter engineering, and heterologous pathway reconstruction for biofuel and biocatalysis applications. Dr. Mordaka's research intersects molecular plant biology and industrial biotechnology, leveraging algal chloroplasts as testbeds for radical metabolic rewiring. His methodologies include VIGS protocols, PVX expression vectors, and terminator analysis to refine transgene expression. Contact: pmm63@cam.ac.uk

• Gravitational Physics
• Numerical Relativity
• Quantum Gravity
• +4 more

Roberto De Pietri is an Associate Professor at the Department of Physics and Earth Sciences within the Faculty of Mathematical, Physical and Natural Sciences at the University of Parma, Italy. He has held this position since March 1, 2015, following 10 years as a Researcher (Assistant Professor) at the same institution. His research focuses on gravitational physics, numerical relativity, and quantum gravity, with particular emphasis on compact objects, gravitational wave phenomena, and computational astrophysics. De Pietri has made significant contributions to numerical simulations of relativistic systems, including neutron star oscillations, binary mergers, and gravitational wave emission. His work bridges theoretical frameworks with high-performance computing applications. Analysis of his recent publications reveals a strong focus on gravitational wave astronomy, particularly in catalog development (GWTC series), multi-messenger follow-up strategies, and computational infrastructure for real-time alert generation. His research spans from fundamental quantum gravity investigations to practical applications in gravitational wave detection pipelines. De Pietri has supervised five PhD students to completion and numerous master's theses, with research topics centered on numerical relativity, gravitational waveforms, and quantum gravity. He has secured substantial computational resources through PRACE projects, including 30 million core hours for neutron star merger simulations. His teaching portfolio includes graduate courses in gravitational physics and undergraduate instruction in general physics and computational methods. He has presented his research at major international conferences including the Marcel Grossmann Meetings and specialized workshops on numerical relativity.

Juanjo NogueiraView profile

Researcher

• Quantum Chemistry
• Computational Biology
• Physical Chemistry
• +3 more

Dr. Juanjo Nogueira leads a research group at the Autonomous University of Madrid, focusing on physical and chemical processes in biological environments using quantum, classical, and hybrid computational approaches. His work bridges disciplines like quantum chemistry, biophysics, and molecular dynamics to model complex systems. Scientific Awards & Grants: Programa de Atracción de Talento Investigador 2018 Proyectos I+D+i 2020 Consolidación Investigadora 2022 The group advocates for open science, sharing preprints on ChemRxiv , research videos on their YouTube channel , and open-source codes on MoBioChem GitHub .

Markus FidlerView profile

Professor

• Performance of Communication Systems
• Network Calculus
• Effective Bandwidths
• +13 more

Prof. Dr.-Ing. Markus Fidler is a Professor of Communications Networks at the Institute of Communications Technology , affiliated with the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover since 2009. His academic journey began with a doctoral degree in Computer Engineering from RWTH Aachen University (2004), followed by post-doctoral fellowships at Institute Mittag-Leffler (2004), NTNU Trondheim (2005), and University of Toronto (2006). He led the Emmy Noether Research Group at Technische University of Darmstadt (2007-2008), where he also earned his habilitation (2008). His research interests span Network Calculus , Effective Bandwidths , Available Bandwidth Estimation , and Parallel Systems (e.g., Multi-path Protocols, Synchronization Constraints). He explores Future Internet architectures, Wireless Communication (including Cognitive Radio and Car-2-X systems), and Congestion Control for Cooperative ADAS and Platooning. His work integrates Machine Learning and Stochastic Modeling for network performance analysis. Recent publication trends emphasize Age-of-Information (AoI) in tandem queues, Statistical Bounds for parallel systems, and Granularity Trade-Offs in multi-server environments. He applies Min-plus Algebra to AoI modeling and investigates Hybrid Time-Event Triggered Systems for resource-efficient communication. His projects include ADINeMo (2024) on Deviation-of-Information for sensor sampling and VaMoS 2 (2024) on validated models for MapReduce scaling. Scientific Awards ERC Starting Grant (2012) Advising includes current doctoral students Sami Akin , Brenton Walker , and Mahsa Noroozi , alongside numerous past advisees now holding academic positions globally. He leads DFG-funded projects such as FeelMaTyC (2017-2020) and GRK SocialCars (2014-2023), focusing on IoT, cooperative mobility, and network calculus applications.

• Neuroscience
• Developmental Biology
• Microscopy
• +4 more

Dr. Kimberly L. McArthur is an Assistant Professor of Biology at Southwestern University in Georgetown, Texas, where she has been teaching since 2019. Her research focuses on neural circuit development using larval zebrafish as a model organism to explore fundamental questions about how neural circuits form and function. Education: Ph.D. in Neuroscience from Washington University in St. Louis (2011) B.A. in Biology from Gustavus Adolphus College in Saint Peter, MN (2004) Dr. McArthur's research investigates how neurons choose synaptic partners, how these partnerships change over time and respond to disruptions, and what consequences these have for circuit function and behavior. Her lab directly observes circuit development in the hindbrain of larval zebrafish using electrophysiology, neuronal tracing, calcium imaging, and behavioral analysis. Her work bridges developmental biology and neuroscience to understand the fundamental principles of neural circuit formation. Her recent publications (2023-2024) demonstrate a continued focus on the structural and functional organization of cranial motor neurons, examining dendritic topography, respiratory circuit development, and activity-dependent refinement of neural connections. These works build on her earlier research exploring the resilience of neural circuits to disruptions in neuronal migration, revealing surprising robustness in neural circuit organization. Mentoring Achievements: Annika Tracy '25 won first place undergraduate talk award for neuroscience section based on collaboration with Dr. McArthur Multiple student co-authors on recent publications including Emma Astad '21, Emmett Griffin-Baldwin '22, Bria Tovar '22, and Vivian Tovar '22 Dr. McArthur actively mentors undergraduate researchers in her lab, providing hands-on experience with cutting-edge neuroscience techniques. Her teaching portfolio includes courses in developmental biology, neurobiology, and explorations in biology, where she emphasizes scientific thinking and critical analysis of primary literature. Her laboratory in Fondren-Jones 207 utilizes the larval zebrafish model system to directly observe neural circuit development through electrophysiology, transgenic approaches, and imaging techniques.

Rolf DrechslerView profile

Professor

• Computer Science
• Formal Verification
• Circuit Design
• +3 more

Rolf Drechsler is a Full Professor and Head of the Group of Computer Architecture at the University of Bremen since 2001, with additional role as Director of the Cyber-Physical Systems Group at DFKI Bremen since 2011. He holds a Dr. phil. nat. in computer science from Johann Wolfgang Goethe University Frankfurt and has held academic positions at Albert-Ludwigs University Freiburg and Siemens AG. Education: Diploma and Dr. phil. nat. in Computer Science (Johann Wolfgang Goethe University Frankfurt, 1992-1995) Previous Roles: Albert-Ludwigs University Freiburg (1995-2000), Siemens AG Munich (2000-2001) His research focuses on formal verification , circuit/system design , and data structures for hardware validation . He has pioneered work on polynomial verification methods, BDD-based synthesis, and quantum computing verification frameworks. Recent publications analyze memristor-based in-memory computing, RISC-V security, and LLM-assisted hardware validation. Key awards include ACM Fellow IEEE Fellow Berninghausen Teaching Award (2018) Multiple best paper awards at ICCAD, DATE, DAC, and DDECS He serves as Associate Editor in journals like IEEE Transactions on CAD and ACM Journal on Emerging Technologies. He co-founded the Graduate School of Embedded Systems and Data Science Center at University of Bremen.

Hassan KaisView profile

Researcher

• Acoustics
• Signal Processing
• Machine Learning
• +2 more

Hassan Kais is a Teacher-researcher affiliated with the Institute of Acoustics at Le Mans University. His work bridges acoustics and telecommunications, focusing on advanced signal processing techniques. Key research areas: Acoustics, Machine Learning, Wireless Communications Institution: Le Mans University, France Hassan's research explores the intersection of acoustic signal analysis and next-generation communication systems. Notably, he has contributed to: Innovative microphone array designs for sound capture SCMA (Sparse Code Multiple Access) systems in telecommunications Machine learning applications in acoustic and wireless signal processing mmWave hybrid MIMO systems for 5G networks Thermo-acoustic and electroacoustic sensor development His publications demonstrate interdisciplinary expertise in: Acoustic wave propagation in complex media Deep learning for communication protocols Signal processing algorithms Metamaterials and transducer design Audio sensor networks Non-linear acoustics applications

Raoof KosaiView profile

Researcher

• Acoustics
• Signal Processing
• Machine Learning
• +4 more

Raoof Kosai is a researcher at Le Mans Université specializing in acoustics, signal processing, and wireless communication. His work bridges UAV detection, biomedical sensors, and machine learning. Research Focus: Acoustic localization, drone detection, acoustic myography, and non-orthogonal multiple access (NOMA) systems. Collaborations: Active in projects involving environmental sound classification, medical diagnostics, and sensor network optimization. Key Research Areas include: Acoustic signal processing for UAV tracking Machine learning in biomedical applications (e.g., diabetic neuropathy diagnostics) Optimization of SCMA systems for enhanced communication quality Design of noise-robust sensor arrays and acoustic chambers Recent Publications highlight advancements in beamforming algorithms, deep learning for gesture recognition, and RF front-end error compensation. His work often integrates acoustic myography and time-frequency analysis for real-time tracking and diagnostics. Education & Advisory: Supervised student Aymen CHAKHARI (2014) and collaborated with researchers like Jean-Hugh Thomas and Pascal Charge .

Melike Erol KantarciView profile

Associate Professor

• 5G and 6G Networks
• Artificial Intelligence (AI)
• Tactile Internet
• +9 more

Dr. Melike Erol-Kantarci is an Associate Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, and a Canada Research Chair in AI-enabled Next-Generation Wireless Networks. She founded the Networked Systems and Communications Research (NETCORE) Laboratory and holds a courtesy appointment as Assistant Professor at Clarkson University's Electrical and Computer Engineering Department. With over 6,000 citations and an h-index of 40, she contributes to IEEE as a Senior Member, chairs the Green Smart Grid Communications special interest group, and serves as Editor for IEEE Communications Letters and IEEE Access . Research Focus: 5G/6G wireless networks AI/ML-driven network optimization Smart grid communications Cyber-physical system security Edge computing and IoT Reconfigurable Intelligent Surfaces (RIS) Scientific Contributions: Her recent publications highlight generative AI integration in 6G, intent-driven network management using hierarchical reinforcement learning, physical layer security for connected vehicles, and explainable AI frameworks in communications. The 15 most recent works (2024-2025) span topics like beamforming optimization, federated learning security, UAV-assisted networks, and semantic communication systems. Leadership: As director of the NETCORE Laboratory, she leads cutting-edge research in networked systems, bridging wireless communication paradigms with energy sustainability and security requirements for next-generation networks.