جست‌وجوی استاد و پژوهشگر

Levent Arslanمشاهده پروفایل

استاد

• Speech Recognition
• Speech Synthesis
• Artificial Intelligence
• +۷ مورد دیگر

Prof. Dr. Levent Arslan is a faculty member at Boğaziçi University, where he has served since 1998. He earned his Ph.D. from Duke University in 1996 and worked as a Research Engineer at Entropic Research in the USA before joining academia. He is also the founder and Chairman of the Board at SESTEK, a pioneering company in Turkish speech recognition and synthesis technologies. His research focuses on speech recognition, speech synthesis, assistive technologies, and natural language processing . His innovations have enabled computer access for visually impaired users through synthesized speech. His work bridges academic research and real-world applications in AI-driven voice systems. The analysis of his recent publications reveals a consistent focus on Turkish language speech technologies, including acoustic modeling, speaker adaptation, emotion detection, and robust feature extraction. His work combines deep learning, signal processing, and linguistic analysis to advance voice interfaces in challenging environments. Levent Arslan has made significant contributions to both research and industry. He holds 15 patents and has published extensively in speech technology. His work at SESTEK exemplifies technology transfer from academia to impactful commercial applications. He has advised multiple students and led research projects in speech processing, though specific names are not listed. His lab or research group likely focuses on spoken language systems and AI for accessibility. Future work may involve multilingual voice assistants, low-resource language modeling, and real-time emotion-aware systems.

• Database Systems
• Machine Learning
• Graph Theory
• +۳ مورد دیگر

Shuai Ma is a researcher at Beihang University , School of Computer Science and Engineering, China. His work spans database systems , machine learning , and natural language processing , focusing on temporal knowledge graphs, graph neural networks, and privacy-preserving federated learning. He received his PhD from the University of Edinburgh , UK, in 2011. Research interests include graph theory , spatiotemporal data analysis , data mining , and anomaly detection . His recent publications address: 2025 : Technology mapping for ASICs, temporal network motifs, and 3D geometry compression. 2024 : Knowledge graph completion, scene mining for e-commerce, and secure aggregation for federated learning. Article trends reveal expertise in graph neural networks , temporal data processing , and privacy-aware systems . Collaborations with institutions like Concordia University and industry leaders underscore his interdisciplinary impact.

Abolfazl Saghafiمشاهده پروفایل

دانشیار

• Applied Mathematics
• Statistics
• Machine Learning
• +۹ مورد دیگر

Abolfazl Saghafi is an Associate Professor in the Department of Mathematics at the University of South Florida, within the College of Arts and Sciences. He holds dual PhDs in Applied Mathematics from Iran University of Science and Technology and in Statistics from the University of South Florida. Education: PhD in Statistics, University of South Florida PhD in Applied Mathematics, Iran University of Science & Technology M.Sc. in Mathematical Statistics, Shahid Beheshti University B.Sc. in Statistics, Azad University His research interests are centered on machine learning, time series classification, BIG data analytics, parametric/non-parametric/Bayesian analysis, and extreme value probability distributions . His work bridges theoretical mathematics with practical applications, particularly in signal processing and data science. In 2011, he resolved a long-standing open problem on Poisson distributions of order k by providing a closed-form solution, marking a significant contribution to applied probability. His recent publications focus on innovative applications of statistical and machine learning methods to real-world problems, particularly in object detection using ground-penetrating radar (GPR) data and improved parameter estimation in financial modeling. These works reflect a strong trend toward interdisciplinary research combining statistics, signal processing, and artificial intelligence. Dr. Saghafi has collaborated with researchers such as S. Jazayeri, S. Esmaeili, and C.P. Tsokos, and holds a U.S. patent for buried object detection systems. His work has been published in journals such as Structural Control and Health Monitoring , Expert Systems with Applications , and Journal of Finance and Data Science . Scientific Awards: He advises students in statistics and applied mathematics, though specific names are not listed. He is affiliated with research teams working on data-driven modeling and signal analysis. His future work is likely to extend into deep learning applications for time series and robust statistical modeling under uncertainty.

• Sports Sciences
• Physical Education
• Sports Ethics
• +۳ مورد دیگر

Prof. Dr. Mehmet KUMARTAŞLI is a faculty member at the Faculty of Sports Sciences, Department of Physical Education and Sports, with a focus on athlete psychology, sports ethics, and performance analysis. He holds a doctorate from Gazi University and has published extensively in international and national journals. Education: Licence in Physical Education and Sports Teaching (Selcuk University, 2001), MA in Physical Education and Sports (Dumlupınar University, 2006), PhD in Physical Education and Sports Education (Gazi University, 2010) His research spans sports ethics , nutritional attitudes of athletes, mental resilience , and motor skill development . Recent publications analyze taekwondo performance, pandemic-related anxiety in teachers, and imagery techniques across sports disciplines. Key trends in his 15 most recent articles (2023–2018) emphasize comparative studies in martial arts, psychological impacts of global health crises, and youth athlete development. He has contributed to international journals like Journal of Education and Recreation Patterns and AKDENİZ SPOR BİLİMLERİ DERGİSİ . He has authored/co-authored six books, including Olympic Branches: Summer and Winter Games (2022) and Sports and Recreation Research Book (2019). No specific scientific awards or student advising details are mentioned in the provided data.

Ângelo Miguel Pedregal de Britoمشاهده پروفایل

استادیار مهمان

• Sports Science
• Exercise Physiology
• Biomechanics
• +۲ مورد دیگر

Ângelo Miguel Pedregal de Brito serves as a Visiting Assistant Professor at Universidade de Lisboa's Faculty of Human Kinetics within the Sports and Health Department. His academic appointment focuses on empirical analysis of youth soccer performance metrics across developmental stages. Research interests center on performance dynamics in youth soccer , specializing in: Positional and displacement patterns across match formats (5v5 to 11v11) Surface-type effects on player movement and technical execution Tactical network analysis using spatiotemporal modeling Game format scaling impacts on physiological demands His methodology integrates biomechanical tracking with competitive structure analysis to optimize youth development frameworks. Publication trends reveal consistent focus on age-group progression (U8-U20) and format-dependent performance metrics , with recent work advancing tactical network theory in youth football. Key contributions include establishing position-specific workload benchmarks across playing surfaces and competitive structures. No formal scientific awards or student advisement records were documented in available materials. Current research appears integrated within Universidade de Lisboa's sports performance analytics ecosystem, though specific lab affiliations weren't specified in source texts.

• Automatic text analysis
• Information search
• IT project management
• +۲ مورد دیگر

Natalia Sergeevna Belova is an Associate Professor in the Department of Software Engineering at the Faculty of Computer Science, National Research University Higher School of Economics (HSE University) in Moscow. She has been working at HSE since 2012 with 13 years of scientific and teaching experience. Education: 2010: Candidate of Technical Sciences from Moscow State University of Instrument Engineering and Computer Science, specialty 05.13.11 "Mathematical and software support for computing machines, complexes and computer networks" 2009: Postgraduate study from Moscow State University of Instrument Engineering and Computer Science 2005: Engineer qualification in "Computers, complexes, systems and networks" from Moscow State Academy of Instrument Engineering and Computer Science Research Interests: Dr. Belova's research focuses on automatic text analysis, information search, IT project management, embedded databases, and project-based learning in engineering education. Her work bridges theoretical computer science with practical applications in software engineering education and industry. She has made significant contributions to pattern recognition, face identification systems, and the development of computationally efficient methods for intelligent systems processing multimedia information. Publications Trend: Dr. Belova's research has evolved from foundational work on embedded databases to more recent contributions in computer vision, affect recognition, and AI applications. Her early work (2009-2013) focused on database systems reliability and project-based learning methodologies. Since 2015, her research shifted toward computer vision, pattern recognition, and deep learning applications. Her most recent publications (2022-2025) demonstrate expertise in AI applications across various domains including transportation systems and video analysis. Scientific Achievements: Recipient of the Grant of the President of the Russian Federation for young doctors of science MD-306.2017.9 (2017-2018) Gratitude from the Vice-Rector of HSE University (February 2025) Gratitude from the Faculty of Computer Science, HSE University (July 2023) Multiple publication bonuses for journals in List A and international peer-reviewed publications (2016-2025) Best Teacher award for 2016-2017 Member of the High Professional Potential Group (HSE personnel reserve) Teaching and Mentoring: Dr. Belova has supervised over 25 bachelor's theses on diverse software engineering topics including mobile applications, web platforms, biometric identification systems, and educational software tools. She teaches courses on "Group Dynamics and Communications in Professional Software Engineering Practice" and "Economics of Software Engineering." Her commitment to project-based learning methodology is evident in both her research and teaching practice. Professional Development: Dr. Belova actively participates in advanced training programs, including recent courses on modernization of educational programs in software engineering (2025) and problems of training modern specialists in software engineering (2024).

Matthieu Sozeauمشاهده پروفایل

پژوهشگر

• Type Theory
• Proof Assistants
• Functional Programming
• +۳ مورد دیگر

Matthieu Sozeau is a researcher affiliated with Inria, focusing on type theory, proof assistants, functional programming, and unification. He actively contributes to academic conferences and workshops, including POPL, ICFP, PLDI, CPP, CoqPL, and WITS. Affiliation: Inria Research Interests: Type Theory, Proof Assistants, Functional Programming, Unification Conference Roles: Program Committee Member, Panelist, Speaker His research centers on formal verification, dependently-typed programming, and compiler correctness. He develops tools like MetaCoq and Equations to enhance Coq's capabilities, bridging theoretical research with practical applications in programming and proof automation. Recent publications include work on sort polymorphism for proof assistants (POPL 2025), verified extraction from Coq to OCaml (PLDI 2024), and MetaCoq tutorials (TutorialFest 2024). Earlier contributions focus on operational correctness verification (ML 2022), type system formalization (POPL 2020), and univalent parametricity (ICFP 2018). He is a key member of the Coq Development Team, contributing to workshops and tool evolution. His work often intersects with functional programming and mathematical logic, emphasizing certified software and automated reasoning.

Enrico Tassiمشاهده پروفایل

پژوهشگر

• Interactive Theorem Provers
• Type Theory
• Functional Programming
• +۳ مورد دیگر

Enrico Tassi is a researcher at INRIA (French Institute for Research in Computer Science and Automation) in the STAMP research team. He obtained his Ph.D. from the University of Bologna in 2008, where he worked on the design and implementation of the Matita interactive theorem prover. His research primarily focuses on the technology of formal proofs, particularly type theory implementation and mathematical modeling. Education: Ph.D. in Computer Science, University of Bologna (2008) Tassi's research explores interactive theorem provers, functional programming, and logic programming. He maintains the small scale reflection extension for Coq and develops the Elpi extension language to enhance OCaml software capabilities. His work enables advanced manipulation of mathematical structures and formal proof environments through high-level programming constructs. His publications demonstrate consistent focus on theorem proving, formal methods, and programming language theory. Recent works emphasize practical implementations in proof assistants (Matita, Coq), unification algorithms, and formal verification of mathematical theories including measure theory and algebra. Tassi has contributed to significant projects including the Mathematical Components library (formalizing the Odd Order Theorem), the Paral-ITP project (scaling Coq for large mathematical libraries), and the CoREACT ANR project. He develops open-source tools including Coq-Elpi plugin and Hierarchy-Builder. He serves on program committees for conferences including CPP, CoqPL and FLOPS. While retired from Debian development (2006-2016), he maintains involvement in open-source communities.

Wilhelm Beckerمشاهده پروفایل

پژوهشگر

• Nonlinear Optics
• Atomic Physics
• Quantum Optics
• +۳ مورد دیگر

Wilhelm Becker is a Researcher at the Max Born Institute for Nonlinear Optics and Short Pulse Spectroscopy, where he leads the Strongfield Theory Group. His research focuses on fundamental aspects of laser-matter interactions, particularly in strong-field physics, nonlinear optics, and quantum dynamics. He explores phenomena such as high-order harmonic generation, photoelectron spectra, electron dynamics in laser-driven systems, and the effects of tailored laser fields on atomic and molecular processes. Key areas of investigation include the theoretical analysis of strong-field ionization mechanisms, symmetry properties in photoelectron spectra, and the generation of attosecond pulses using two-color laser fields. His work bridges quantum mechanics and classical models to understand electron trajectories and ionization pathways in ultra-intense laser environments. Becker’s contributions span theoretical advancements in molecular alignment effects, polarization-dependent processes, and the application of saddle-point methods to ionization dynamics. His research has implications for novel light sources and ultrafast spectroscopy techniques.

Denis Firsovمشاهده پروفایل

پژوهشگر

• Formal Methods
• Cryptography
• Type Theory
• +۳ مورد دیگر

Denis Firsov is a researcher at the Department of Software Science at Tallinn University of Technology (TUT) and a formal methods engineer at Input Output Global (IOG) . His work bridges formal methods , cryptography , and type theory , with a focus on zero-knowledge proofs , security verification , and language-based security . He has a PhD from the Institute of Cybernetics at TUT (2016), where he studied constructive type theory using Agda and Coq. Postdoctoral research at the University of Iowa (2016-2018) involved impredicative type theory in Cedille. He has held positions at GuardTime (2018-2020) and Matter Labs (2020-2023), working on formal verification of cryptographic protocols and ZK-circuit DSLs . Research Highlights: Developed formalizations for zero-knowledge protocols (Fiat-Shamir, Schnorr, Blum) in EasyCrypt Created Rust DSLs for ZK-circuits with formal correctness proofs Advanced impredicative lambda-encodings with induction in Cedille Contributed to parser certification for context-free and regular languages Patents: US 11,316,698: Delegated signatures for smart devices EU EP4044501B1: Method for data signatures with unbounded keys

Duncan Adamsonمشاهده پروفایل

مدرس

• Combinatorics on Words
• Algorithms for Combinatorial Objects
• Crystal Structure Prediction
• +۷ مورد دیگر

Duncan Adamson is a Lecturer in the School of Computer Science at the University of St Andrews, United Kingdom. He has held prior research positions at the Leverhulme Research Centre for Functional Materials Design, the University of Göttingen, Reykjavik University, and the University of Liverpool. His academic foundation includes a PhD from the University of Liverpool supervised by Prof. Igor Potapov and undergraduate studies at the University of Glasgow. His research lies at the intersection of theoretical computer science and discrete mathematics, with a focus on combinatorics on words , algorithm design , crystal structure prediction , and temporal graphs . He explores symmetry in multidimensional words, develops algorithms for combinatorial enumeration, and investigates computational hardness in materials science. His work often bridges abstract theory with real-world applications in chemistry and robotics. The recent publications show a strong trend in combinatorial algorithms , particularly in enumeration, ranking, and optimization over structured words, graphs, and sequences. A significant portion of his work involves the k-centre problem for implicitly defined combinatorial classes and temporal graph colouring , with increasing emphasis on algorithmic complexity and practical implementation. His 2024 paper on harmonious colourings in temporal matchings was awarded best paper at SAND 2024, highlighting the impact of his research. Scientific Awards: Best Paper Award, SAND 2024 – 'Harmonious Colourings of Temporal Matchings' Duncan Adamson has been supported by the Leverhulme Research Centre for Functional Materials Design during his PhD and postdoctoral work. While no formal advisees are listed, his supervision by leading researchers and collaborative projects suggest active mentorship and team integration. He teaches core computer science modules at St Andrews, including CS2001 and CS3302, and maintains a busy research schedule with weekly meetings and supervisory responsibilities. His research is conducted within the Algorithms and Complexity group at St Andrews, continuing collaborations with international teams in Iceland, Germany, and beyond. Projects often involve interdisciplinary efforts, especially in applying computational techniques to materials science and chemistry.

• Neurosurgery
• Neurocritical Care
• Machine Learning in Medical Prognostics
• +۳ مورد دیگر

Jennifer Sauvigny is a Physician Scientist at the Department of Neurosurgery , Universitätsklinikum Hamburg-Eppendorf, affiliated with the Medical Faculty of the University of Hamburg. Her work bridges clinical neurosurgery, medical technology evaluation, and neurocritical care research, with a focus on improving outcomes for patients with complex neurological conditions. Key research areas include neurocritical care analytics, brain tumor classification, cerebrovascular surgery, and digital microscopy applications in neurosurgical workflows. She has developed machine learning models for predicting shunt dependency and intracranial hypertension using intensive care unit data. Her publications emphasize technical innovations (e.g., 3D4K exoscope systems) and clinical challenges in subarachnoid hemorrhage, glioblastoma treatment, and postoperative bone resorption. Recent articles demonstrate expertise in machine learning integration for neurological outcome prediction and DNA methylation-based tumor classification . Collaborations span neurosurgery, radiology, and critical care medicine across multiple institutions.

Nada Aminمشاهده پروفایل

استادیار

• Programming Languages
• Artificial Intelligence
• Neuro-Symbolic Systems
• +۵ مورد دیگر

Nada Amin is an Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). She leads the metareflection lab, focusing on neuro-symbolic programming, program synthesis, and meta-programming techniques. Her research combines programming languages (PL) with AI, particularly leveraging LLMs for verified program and proof synthesis. Education: PhD from EPFL (2016), MEng and BS from MIT (2008). Previous roles include University Lecturer at the University of Cambridge (2017–2019) and software engineering at Google (2009–2011). Awards include Distinguished Paper Awards at PLDI 2023 and an Outstanding Paper Award at NeurIPS’24. Research interests span neuro-symbolic systems, meta-programming, probabilistic reasoning, and precision medicine applications. Current projects include VerMCTS, Persimmon, and collapsing towers for secure compilation. She teaches courses like CS152 (Programming Languages) and CS252R (Advanced PL Seminars). Labs/Teams: Harvard PL Group; Metareflection Lab. Collaborates widely on PL+AI, drug repurposing for medicine, and multi-stage relational programming. Supervises ~40 researchers including PhD students, postdocs, and undergraduates.

• Organizational Sociology
• Business and Society
• Climate Change
• +۴ مورد دیگر

Wesley Longhofer is an Associate Professor of Organization & Management and Executive Academic Director of Emory University's Goizueta Business School Business & Society Institute. He holds a PhD in Sociology from the University of Minnesota and a BA from Texas Christian University. His research focuses on organizational sociology, climate change, human rights, and non-profit organizations with a particular emphasis on global governance challenges. Longhofer's work examines complex societal issues such as NGO funding restrictions, carbon emissions from power plants, and civic action effectiveness. His research has been supported by the National Science Foundation and featured in prestigious journals like Administrative Science Quarterly and Nature Communications . Notable publications include Super Polluters (2020), analyzing extreme carbon emitters, and a 2025 study on stranded fossil fuel assets' impact on emissions. Awards: 2018 Emory Williams Teaching Award, 2016 Marc F. Adler Prize, 2016 Poets&Quants '40 Under 40' Grants: NSF-funded climate change/energy sector studies His current initiatives include leading the Business & Society Institute which addresses global challenges through academic research and actionable strategies. Longhofer's work bridges sociological theory with practical policy solutions, particularly in environmental governance and organizational effectiveness.

• Type Theory
• Dependent Types
• Programming Languages
• +۳ مورد دیگر

Andreas Martin Abel is a Senior Lecturer at the University of Gothenburg, affiliated with the Logic and Types department. His research focuses on type theory, dependent types, programming languages, and formal verification. He has contributed significantly to foundational work in type systems, including advancements in cubical Agda, modal logics in type theory, and normalization-by-evaluation techniques. His work often intersects with functional programming and homotopy type theory. Key research areas include formalizing type systems, exploring proof-theoretic properties of logics, and developing mechanized proof systems. He has published extensively in venues like the Journal of Functional Programming and ACM SIGPLAN Notices, collaborating with notable researchers such as Thierry Coquand and Andrea Vezzosi. His recent work includes studies on graded modal dependent type theories, decidability of type conversions, and the integration of univalence principles in Agda. He maintains an active role in advancing type-theoretic foundations for programming languages and formal verification.