جست‌وجوی استاد و پژوهشگر

Rushikesh K. Joshiمشاهده پروفایل

استاد

• Software Engineering
• Distributed Systems
• Program Analysis
• +۵ مورد دیگر

Rushikesh K. Joshi is a Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Bombay. His research focuses on computational models for programs, their structures and dynamics, including processes, interactions, concurrency, and distributed systems. He has taught advanced courses like CS 770 (Process Engineering), CS 787 (Language Engineering), and CS 757 (Design and Re-engineering). Research Interests: He specializes in software engineering, distributed systems, program analysis, and code refactoring. His work includes modular process modeling, trace language mining, and consistency models for business processes. He also explores objectification of procedural code through projects like Ox and AccessViz. Notable Projects: Anonymous Remote Computing (ARC), Filter Objects, Constore Graph Database, and Ox (objectification of Linux kernel structures). Funding sources include IBM, Microsoft, Infosys, and the Ministry of Information Technology. Scientific Contributions: His research has led to publications in IEEE Transactions, LNCS, and other venues. He has advised over 100 theses, including Ph.D. students Karnika Shivhare, Omkarendra Tiwari, and Vrinda Yadav.

• Discrete Optimization
• Scheduling Theory
• Algorithms
• +۳ مورد دیگر

Dr. Sven Jäger is a Researcher at the Department of Mathematics, Faculty of Mathematics and Natural Sciences, Technical University Berlin. His office is located at MA 668 in the Mathematics Building at Straße des 17. Juni 136, 10623 Berlin, Germany. He can be reached by telephone at +49 30 314 23189 and by email at jaeger@math.tu-berlin.de, maintaining a professional presence through his personal website at https://sven-jaeger.gitlab.io . Dr. Jäger's research spans discrete mathematics and optimization with particular expertise in scheduling theory, algorithms, and their cross-disciplinary applications. His work bridges theoretical computer science with practical operations research challenges, evidenced by publications in top-tier venues including Mathematical Programming, European Journal of Operational Research, and SODA. He has developed significant theoretical contributions to non-clairvoyant scheduling, including competitive kill-and-restart strategies and proportional fairness analysis under polyhedral constraints. His research extends to quantum computing applications for discrete optimization and transportation network problems, demonstrating versatility across theoretical and applied domains. Analysis of his publication trajectory reveals three interconnected research streams: (1) theoretical scheduling algorithms with competitive ratio guarantees, (2) quantum-inspired optimization techniques applied to real-world problems like transport robot scheduling, and (3) transportation science applications including user equilibrium modeling and energy-efficient timetabling. His combinatorial work on symmetric chain decompositions and Gray codes provides foundational contributions to discrete mathematics. Dr. Jäger actively contributes to education as a teaching assistant for Analysis II for Engineering Sciences and Computer-Oriented Mathematics II at TU Berlin. While his publication record demonstrates significant scholarly impact across multiple domains, no specific scientific awards are mentioned in the available information. His collaborative work with researchers including Guillaume Sagnol, Anita Schöbel, and Nicole Megow spans theoretical computer science, operations research, and transportation applications, reflecting the interdisciplinary nature of his research program.

• Computational Modeling
• Cognitive Science
• Emotion Modeling
• +۵ مورد دیگر

Professor Stacy Marsella is a Cognitive Neuroimaging researcher at the University of Glasgow with a distinguished career in computational modeling of human cognition, emotion, and social behavior. Her work bridges computer science, cognitive psychology, and artificial intelligence to create sophisticated virtual human systems. Her research interests focus on computational modeling of cognition, emotion and social behavior, with particular emphasis on the interplay between emotion and cognition, Theory of Mind (modeling beliefs about others' mental processes), and the role of nonverbal behavior in face-to-face interaction. She has pioneered applications in virtual human design, where software entities interact with humans using spoken dialogue in virtual environments, and large-scale social behavior simulation. Analysis of her 15 most recent publications reveals a consistent focus on virtual human technologies, social interaction modeling, and decision-making processes. Her work spans multiple disciplines including affective computing, human-computer interaction, cognitive science, and artificial intelligence, with particular strength in gesture generation, social virtual reality, and computational models of human behavior under stress. Recent work shows increasing application to real-world problems like hurricane evacuation decisions, supply chain management, and public speaking training. Professor Marsella has supervised postgraduate students including Marion Roth and Tobias Thejll-Madsen, and has worked with research assistants Stephanie Cheng, Amol Deshmukh, and Alessandro Vinciarelli. Her significant research is supported by multiple major grants including from EPSRC and DARPA. She leads research funded by three major grants: 'From data and theory to computational models of more effective virtual human gestures' (EPSRC, 2020-2022), 'AGENTS with Theory of Mind for Intelligent Collaboration (ATOMIC)' (DARPA, 2019-2023), and 'Graphical Encoding of First Principles for Agent-Based Social Simulation (GEFPABSS)' (DARPA, 2018-2020). These projects reflect her leadership in developing advanced computational models of social cognition and virtual human technologies.

Philip O'Herronمشاهده پروفایل

استادیار

• Neurovascular Coupling
• Visual Processing
• Cerebral Blood Flow
• +۳ مورد دیگر

Philip O'Herron, PhD, is an Assistant Professor at Augusta University's Medical College of Georgia, Department of Physiology. His work bridges neurovascular coupling and visual processing, focusing on the interdependence between cortical neural activity and hemodynamic responses. Education: PhD in Neuroscience (2009, Johns Hopkins University), BA in Chemistry (2002, George Mason University), BA in Philosophy (2000, Christendom College) Research Themes: Dr. O'Herron's lab investigates functional hyperemia's physiological role using optogenetic vascular control. Current projects examine Alzheimer's disease vascular interactions , 3D optogenetic vessel manipulation , and vasculo-glia-neuronal coupling through collaborations with Dr. Jessica Filosa and Dr. Felipe Barros. Article Trends: Recent publications span neurovascular modeling , metabolic adaptation studies , and in vivo optical manipulation techniques , reflecting his work on vascular cognitive impairment and cortical depth-dependent processing. Scientific Awards: First prize MUSC research day (2012) Johns Hopkins neuroscience poster award (2008) Advising & Grants: Leads NIH-funded projects on Alzheimer's blood flow mechanisms (NIA R01) and neurovascular coding (NINDS R01). Mentors postdoctoral fellows in vascular neuroscience and develops models for cortical blood flow regulation.

• Machine Learning
• Pattern Recognition
• Information Fusion
• +۳ مورد دیگر

Tony Pinar serves as an Associate Teaching Professor and Senior Design Coordinator in the Department of Electrical and Computer Engineering at Michigan Technological University. His academic credentials include: PhD in Electrical Engineering (2017) MS in Electrical Engineering (2014) BS in Electrical Engineering (2011) Dr. Pinar's research centers on Machine Learning and Pattern Recognition , with significant contributions to Information Fusion and Signal Processing . His work bridges theoretical frameworks like fuzzy Choquet integrals with practical applications including explosive hazard detection systems and autonomous underwater vehicles. Current projects focus on explainable AI methodologies and real-time data fusion for engineering systems. Publications from 2016-2018 reveal a consistent trajectory in fuzzy integral applications across domains: defense technology (explosive detection), robotics (underwater gliders), and AI interpretability. Key themes include decision-level fusion optimization, multiple kernel learning, and adapting theoretical models to constrained data environments—demonstrating strong interdisciplinary alignment between electrical engineering and machine learning. Prior to academia, Dr. Pinar worked as an electrical design engineer at GE Aviation developing avionic test systems. He maintains industry engagement through independent engineering consulting while leading the ROUGHIE (Research Oriented Underwater Glider for Hands-on Investigative Engineering) development initiative.

Sümeyye KAYNAKمشاهده پروفایل

استادیار

• Artificial Intelligence
• Cloud Computing
• Environmental Informatics
• +۳ مورد دیگر

Sümeyye KAYNAK serves as an Assistant Professor in the Department of Computer Engineering at Sakarya University's Faculty of Computer and Information Sciences. Her academic profile demonstrates interdisciplinary expertise bridging computer science with environmental sustainability and educational technology through computational modeling and data-driven solutions. Her educational foundation includes: Doctorate (2019) from Sakarya University Institute of Science/Computer and Information Engineering with thesis on solar energy potential modeling using 3D data Master's degree (2014) from same institution focusing on AI-based student counseling infrastructure Bachelor's degree (2012) in Computer Engineering from Sakarya University Faculty of Engineering Dr. KAYNAK's research integrates advanced computational methodologies across multiple domains. Her primary focus areas include Artificial Intelligence applications for resource allocation in cloud manufacturing (utilizing genetic algorithms and AHP), Environmental Informatics for flood modeling and hydrological analysis, and Sustainable Energy systems through solar potential estimation tools. Recent work demonstrates significant expansion into geospatial web components for earth science agencies and digital twin frameworks for urban infrastructure resilience, reflecting growing emphasis on climate change adaptation technologies. Publication analysis from 2012-2025 reveals a clear research evolution: early work (2012-2018) concentrated on educational AI systems and solar energy tools, while current output (2023-2025) prioritizes environmental applications with city-scale flood impact modeling, hydroinformatics, and open data frameworks. This trajectory shows increasing sophistication in real-time data analytics and cross-domain integration, particularly between manufacturing systems and environmental monitoring. No scientific awards were documented in the source materials. Regarding academic mentoring, the available documentation contains no references to graduate student supervision or grant-funded research projects. No laboratory affiliations or research team leadership roles were specified in the provided information.

Alfred Taudesمشاهده پروفایل

استاد

• Production Management
• Strategic Management in High-Tech Industries
• Real Options
• +۵ مورد دیگر

Prof. Dr. Alfred Taudes is a faculty member at the Vienna University of Economics and Business, affiliated with the Department of Information Processing and Process Management under the Institute for Production Management. His research spans Production Management, Strategic Management in High-Tech Industries, Real Options, Supply Chain Management, and SAP R/3 integration, with significant contributions to Quantitative Models of Learning Organizations. Key research areas: Production/Operations Management, Strategic High-Tech Industry Analysis, Real Options Theory Notable collaborations with researchers like Mild, Natter, and Dorffner Focus on empirical validation of models in marketing, supply chain optimization, and software platform decisions His publications demonstrate interdisciplinary trends combining Management Science , Information Systems , and Machine Learning . Recurring subfields include Neural Network Applications , Real Options Valuation , Consumer Behavior Modeling , and Process Migration in Distributed Systems . While no explicit scientific awards are listed, his work has been disseminated through leading journals and conference proceedings.

Tomka Yuriy Yaroslavovychمشاهده پروفایل

دانشیار

• Software architectures
• enterprise application development
• .NET platform
• +۳ مورد دیگر

Yuriy Yaroslavovych Tomka is an Associate Professor in the Department of Computer Science at Yuriy Fedkovych Chernivtsi National University. He holds a Candidate of Physical and Mathematical Sciences degree and has been serving as an Associate Professor since April 15, 2021. His academic work spans software engineering, neural networks, and biomedical image processing, with numerous publications in these fields. Dr. Tomka's educational background includes: Bachelor's degree in Laser and Optoelectronic Engineering from Yuriy Fedkovych Chernivtsi National University (2005), with honors Candidate of Physical and Mathematical Sciences degree (2009) in specialty 01.04.05 – Optics, Laser Physics Dr. Tomka's research interests focus on software architectures, enterprise application development on the .NET platform, pattern recognition, digital image processing, and neural networks. His work bridges theoretical computer science with practical applications in biomedical diagnostics, financial technology, and e-commerce systems. He has made significant contributions to the development of information systems, machine learning applications, and educational methodologies in computer science. Analysis of Dr. Tomka's recent publications reveals a strong focus on practical applications of software engineering principles, particularly in the .NET ecosystem. His work spans from fundamental software architecture to specialized applications in biomedical imaging and financial forecasting. There's a clear trend toward interdisciplinary research, combining computer science with fields like medicine and finance, demonstrating the versatility and applicability of his technical expertise. Dr. Tomka has received recognition for his mentorship, guiding student research that won second-degree diplomas in national competitions. His professional development includes numerous certifications in modern software technologies from institutions like Sigma Software University. As an active member of the Bukovina Information Technology Cluster named after Joseph Schumpeter since 2019, Dr. Tomka contributes to regional IT development initiatives. He also provides scientific consulting to the Limited Liability Company "Buknanotech" and has managed research projects including "Development of new methods and biomedical systems for polarization-holographic fractalmetry of crystallites of tissues and fluids of human organs" (2019-2021).

Mark Fryeمشاهده پروفایل

استاد

• Neuroethology
• Sensory Neuroscience
• Visual Motion Processing
• +۶ مورد دیگر

Mark Frye is a full Professor in the Department of Integrative Biology & Physiology at the University of California, Los Angeles and Director of the interdepartmental Molecular, Cellular & Integrative Physiology (MCIP) Ph.D. program. An elected member of the Brain Research Institute, he explores the neural basis of flexible behavior using Drosophila melanogaster as a model. Education M.S., Neuroscience – Union College, 1992 Ph.D., Zoology – University of Washington, 2000 Research Focus Dr. Frye’s laboratory integrates neurogenetics , in vivo calcium imaging , and closed-loop virtual-reality flight arenas to dissect how visual, olfactory, and mechanosensory signals are fused in the fly brain to generate robust navigation. Key questions include how object-detecting neurons compute figure–ground discriminations, how neuromodulators such as serotonin bias sensory-motor transformations, and how species-specific visual ecologies shape tracking strategies. Parallel to his neuroethology work, Frye co-leads large-scale translational studies on bipolar disorder , lithium pharmacogenomics , and ketamine therapeutics , bridging cellular circuits to clinical outcomes. Publication Trends Recent articles (2020–2024) emphasize inhibitory micro-circuits governing motion vision, comparative visual ecology across Drosophila species, and neuromodulatory re-weighting of sensory pathways. Earlier work established fundamental algorithms for elementary motion detection and multisensory flight control . Scientific Honors & Awards NIH K99/R00 Pathway to Independence Award (mentored to trainee Giovanni) MCIP Best Student Talk Award – Lesly (2023) Advising & Funding Dr. Frye mentors ~8–10 Ph.D. students and post-doctoral fellows at any given time. Current and recent trainees include Jean-Michel Mongeau (now tenure-track at Penn State), Mehmet Keleş , and incoming MCIP student Ava Bignell . Research is supported by multiple active NIH R01 and U01 grants, including consortium projects on bipolar genomics and ketamine biomarkers. Laboratory & Affiliations The Frye Laboratory occupies ~2,000 sq ft on the 2nd floor of the Terasaki Life Sciences Building (TLSB 2014). It houses custom-built magnetic-tether and free-flight arenas, two-photon microscopes, and high-speed videography rigs. Core affiliations include the Brain Research Institute , Neuroscience GPB Home Area , and the BD² Precision Medicine Initiative .

• Process Mining
• Software Process Mining
• Object-Oriented Programming
• +۷ مورد دیگر

Sergey Shershakov is an Associate Professor at the Faculty of Computer Science, Department of Software Engineering at the National Research University Higher School of Economics (HSE University). He serves as the Academic Director of the Systems and Software Engineering educational program and has been with HSE University since 2010. His academic journey includes a PhD from HSE University (2020) and a Master's degree in Software Engineering from the same institution (2012). Dr. Shershakov's research focuses primarily on Process Mining and Software Engineering, with specific interests in: Process Mining methodologies and tools Software Process Mining and analysis Object-Oriented and Component-Oriented Programming Information Systems Architecture Verification of Algorithms Embedded Systems development His scholarly contributions demonstrate a consistent focus on developing practical tools and methodologies for process mining, with particular emphasis on creating graphical interfaces (like VTMine for Visio), improving performance of process mining algorithms, and applying these techniques to real-world systems. His work bridges theoretical computer science with practical software engineering applications, especially in the domain of business process analysis and optimization. Dr. Shershakov has received numerous recognitions for his academic work: Best Teacher award (2014, 2017-2021) Best Academic Supervisor in the category 'Admission of Foreign Students' (2024) Multiple Gratitude awards from HSE University leadership (2017-2024) Academic Work Allowance (2016-2021) Member of the 'New Researchers' category in the High Professional Potential Group (2014-2015) As an educator, Dr. Shershakov teaches multiple courses in C++ programming, Algorithms and Data Structures, and Introduction to Programming across different departments at HSE University. He leads research projects including an RFBR grant focused on 'Development of methods for efficient implementation of algorithms of process mining based on large event logs' (2018). He is also an active member of the IEEE Task Force on Process Mining. Dr. Shershakov is affiliated with the Laboratory of Process-Aware Information Systems (PAIS Lab) at HSE University, where he conducts research on process mining techniques and their applications. His work has significant implications for business process optimization, system verification, and software engineering practices.

• Information Systems Architecture
• Design Patterns
• Object-Oriented Programming
• +۵ مورد دیگر

Sergey Aleksandrovich Videnin is an Associate Professor at the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE University) since 2022. His academic background includes a Candidate of Pedagogical Sciences degree (2010) and extensive professional experience in both academia and industry. Prior to joining HSE, he served as Deputy Director of the IT Education Development Center at Moscow Institute of Physics and Technology (2021-2022) and as Head of the Department of Information Systems at Siberian Federal University (2010-2021). Videnin's educational background includes graduation from Krasnoyarsk State Pedagogical University named after V.P. Astafyev in 2005 with a specialty in "Informatics with an additional specialty in pedagogy-psychology" and qualification as a "Teacher-psychologist." He has completed numerous professional development courses in educational technologies, digital transformation of education, and software engineering from HSE University, Siberian Federal University, and other institutions between 2011 and 2025. His research interests span information systems architecture, design patterns, object-oriented programming theory, theoretical foundations of programming, programming languages, and application software. Videnin has made significant contributions to educational technology, particularly in implementing active learning methods in programming education within the CDIO (Conceive-Design-Implement-Operate) engineering education framework. Videnin's recent publications demonstrate a strong focus on the intersection of software engineering principles and educational practices, with particular attention to practical applications in real-world contexts including real estate market analysis, biological image processing, and industrial process control. His work shows a consistent trend toward developing practical solutions that bridge theoretical concepts with tangible applications across diverse domains. Gratitude from the Department of Software Engineering, HSE (November 2023) Best Teacher - 2023-2025 High professional potential group (HSE personnel reserve) Category "New teachers" (2023) Winner of the All-Russian competition "League of Lecturers" organized by the Russian society "Knowledge" (May 2023) Videnin has been actively involved in teaching various computer science courses including Software Design, Computer System Architecture, Operating Systems, and Java Programming. He has participated in significant research projects funded by RFBR, the Ministry of Education RF, and RSF, focusing on information systems architecture, digital transformation of education, and industrial process control. His work demonstrates a strong commitment to both theoretical research and practical applications in software engineering and educational technology.

• Algorithms
• Information System Architecture
• Petri Nets
• +۵ مورد دیگر

Alexey Alexandrovich Mitsyuk serves as Associate Professor at the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE), where he also holds the position of Deputy Dean for Research and Senior Research Fellow at the Research and Educational Laboratory of Process-Oriented Information Systems (POIS). He has been working at HSE since 2013 with 12 years of scientific and teaching experience. Mitsyuk is also a member of the Academic Council of HSE. His educational background includes a PhD from HSE (2019) with a dissertation on "Correction of process models while preserving their structure based on event logs" and a specialist degree in Applied Mathematics from Moscow State Institute of Electronics and Mathematics (2009). He is actively involved in professional associations including IEEE Task Force on Process Mining and BPM Association. Mitsyuk's research focuses on process mining, Petri nets, software architecture, data visualization, and algorithms. His work bridges theoretical computer science with practical applications in software engineering and educational analytics. He has supervised numerous student theses across bachelor's and master's programs, with students completing research on topics ranging from software architecture analysis to process mining applications. His publication record shows consistent contributions to the field of process mining and software engineering, with recent work focusing on advanced visualization techniques, process model correction, and applications of process mining in educational and mobile contexts. His research demonstrates a clear progression from theoretical foundations of process modeling to practical applications in software development and education. Honorary certificate from HSE (May 2025) Gratitude from the Faculty of Computer Science (August 2022) Best teacher awards (2015-2025) High professional potential group (HSE reserve staff) Competition for best Russian-language scientific works (2024) Mitsyuk has coordinated research activities of the faculty, created new research groups, monitored grants, and analyzed publication activities. He led a student team that won first place in the BPI Challenge 2017 student category. His teaching includes courses on Software Systems Architecture and Mathematical Methods of Process Analysis in Software Engineering. He is actively involved in numerous conferences as committee member and reviewer, particularly in the fields of process mining and software engineering.

• Accounting Information Systems
• Ontology
• Blockchain
• +۳ مورد دیگر

William McCarthy serves as a Professor in the Department of Accounting and Information Systems at Michigan State University's Broad College of Business. His research pioneered the Resource-Event-Agent (REA) accounting ontology, establishing foundational frameworks for modern accounting information systems. With ongoing teaching activities documented through 2024 (including graduate courses ACC-821, ACC-823, and ACC-825), he remains an active faculty member advancing the integration of emerging technologies like blockchain into accounting practice. McCarthy's research spans Accounting Information Systems, Ontology, Blockchain, Enterprise Information Systems, Semantic Modeling, and Design Science. He developed the REA model as a generalized framework for shared-data accounting environments, later expanding it into formal ontologies for enterprise modeling. His current work analyzes blockchain's disruptive potential in accounting systems, as highlighted in the Spartan BizCast episode and New York City conference presentations. This research bridges theoretical accounting models with practical enterprise applications through semantic modeling and design science methodologies. Analysis of his 15 most recent publications (1997-2013) reveals three evolving research trajectories: (1) ontological expansion of the REA model into policy specifications and temporal dimensions, (2) blockchain and internet-era applications for supply chain collaboration, and (3) design science methodology development for accounting information systems. His work consistently emphasizes semantic modeling to create interoperable enterprise architectures while addressing innovation gaps between academic research and professional practice. Professor McCarthy has mentored graduate students through specialized courses in accounting information systems from 2011-2024, with teaching ratings publicly available. While the provided text doesn't detail specific grants or awards, his sustained publication record in premier journals like The Accounting Review and Accounting Horizons demonstrates significant research impact. No laboratory or research team affiliations are mentioned in the source materials.

Suresh Jagannathanمشاهده پروفایل

استاد

• Programming Language Semantics
• Formal Verification
• Type Theory
• +۷ مورد دیگر

Professor Suresh Jagannathan is a leading researcher in programming languages and formal verification. His work focuses on semantics of high-level languages, type theory, program analysis, and compiler design, with a particular emphasis on concurrent and distributed systems. He explores formal methods for certified compilation, memory model consistency, and verification techniques enabling safe program optimizations. Core research areas: programming language semantics, formal verification, type theory, compiler design Key applications: concurrent/distributed systems, certified compilation, safe neural network verification Recent publications highlight his contributions to automated verification of concurrent data structures, type-guided repair of input generators, and differentiable logic specifications for AI planning systems. His work combines theoretical rigor with practical implementations like ECOOP best papers and tool developments. Professor Jagannathan has received multiple scientific awards (not specified in available data) and maintains active collaborations with researchers in formal methods and systems verification communities.

Tillmann Rendelمشاهده پروفایل

پژوهشگر ارشد

• Programming Languages
• Software Engineering
• Domain-Specific Languages (DSLs)
• +۴ مورد دیگر

Tillmann Rendel is a Research Fellow at the University of Tübingen , affiliated with the Department of Programming Languages and Software Technology . He contributes to projects involving DSLs , language design , and program transformations . Education: M.Sc. in Computer Science. Research interests center on programming languages , focusing on modular systems , functional programming , and domain-specific language implementation . His work explores invertible syntax descriptions , copattern matching , and variability-aware testing . Publications highlight advancements in parsing , DSL design , and language composition , with a strong emphasis on formal semantics , compiler design , and interactive development tools . Scientific Awards: Most Influential Paper Award at GPCE 2018 for 'Polymorphic Embedding of DSLs' (2008 paper co-authored with Hofer, Ostermann, and Moors). Collaborations include key contributions to the Uroboro project , participation in Dagstuhl Seminars , and presentations at major conferences like OOPSLA , ICFP , and DSLDI .