جست‌وجوی استاد و پژوهشگر

Stefanie Rinderle-Maمشاهده پروفایل

استاد

• Process-Oriented Information Systems
• Flexible and Distributed Process Technologies
• Compliance Management
• +۶ مورد دیگر

Prof. Dr. Stefanie Rinderle-Ma is a full professor for Information Systems and Business Process Management at the Department of Informatics, Technical University of Munich (TUM). Prior to TUM, she held a full professorship at the University of Vienna, leading the Research Group Workflow Systems and Technology. Her research focuses on process-oriented information systems, flexible/distributed process technologies, compliance management, production intelligence, and process mining. She has authored numerous publications in top journals and conferences, including Information Systems and BPM. Education and Career: Studied Business Mathematics at the University of Augsburg. Completed her doctorate and habilitation at the University of Ulm. Postdoctoral stays in the Netherlands and Canada. Headed the Workflow Systems and Technology research group at the University of Vienna before joining TUM in 2021. Research Interests: Her work emphasizes advancing digitalization and automation through processes while supporting human-centric decision-making. Key domains include production, logistics, and healthcare. Awards and Recognition: Best Paper Awards (CAiSE/IEEE EDOC, 2018). BPM Test of Time Award (2013). Merckle Research Prize (2008). Dissertation Prize (Ulm University Society, 2005). IFIP TC2 Manfred Paul Award (2005). Grants and Projects: Principal investigator for AdONE (Advanced Optimization in a Networked Economy, DFG, 2021–2025). Principal investigator for TRPro (Taming Regulatory Document Changes, DFG, 2023–2026). Principal investigator for BPAIS (SAP Signavio-funded project on process modeling, 2023–2027). Labs and Teams: Leads the KrcmarLab and Wittges Lab, focusing on process intelligence, generative AI in process modeling, and IoT integration in process systems.

Dimitra Panagouمشاهده پروفایل

دانشیار

• Motion planning
• Coordination and control
• Robotic networks
• +۱۰ مورد دیگر

Dimitra Panagou is an Associate Professor with the Department of Robotics and the Department of Aerospace Engineering at the University of Michigan. She directs the Distributed Aerospace Systems and Control Laboratory (DASC Lab) located in the Ford Robotics Building, where she leads research in safe and resilient autonomy for robotic systems. Her research interests focus on motion planning, coordination and control of robotic networks, autonomous multi-vehicle systems, nonlinear systems and control, navigation and guidance, distributed/decentralized control, and dynamic coverage. Professor Panagou's work emphasizes the development of planning, learning and control methods to address real-world, safety- and time-critical problems through provably correct solutions. Her research spans nonlinear systems, decision making under constraints and uncertainty, estimation and learning, mission planning, and networked control systems with applications across aerial, ground, marine, and space domains. Professor Panagou's recent publications (2024-2025) demonstrate a strong focus on control barrier functions, safety-critical control, resilient multi-robot systems, and risk-aware navigation. Her work bridges theoretical foundations with practical applications in autonomous systems, with particular emphasis on providing mathematical guarantees for safety and performance. The research spans multiple domains including aerial vehicles, marine systems, and ground robotics, addressing challenges in uncertain environments and under various constraints. Professor Panagou has received several prestigious awards including: NASA Early Career Faculty Award AFOSR Young Investigator (YIP) Award NSF CAREER Award IEEE TCAC Best Student Paper Award (for work from her lab) She has been invited to deliver a plenary talk at CDC 2024 and a keynote talk at ICRA 2025, highlighting her prominence in the control and robotics communities. Her research is supported by multiple grants from agencies including NASA, NSF, and AFOSR. The Distributed Aerospace Systems and Control Laboratory (DASC Lab) is equipped with state-of-the-art facilities including a fleet of UAVs (Hummingbirds, Firefly, and Solos), a high-precision motion capture system with 14 VICON cameras, drone LiDAR, and various sensors. The lab conducts both indoor and outdoor flight experiments, with permission for outdoor flights over the Wave Field at the University of Michigan's North Campus.

Michael Freedmanمشاهده پروفایل

استاد

• Distributed Systems
• Networking
• Security
• +۴ مورد دیگر

Michael J. Freedman is the Robert E. Kahn Professor of Computer Science at Princeton University, leading research in distributed systems, networking, and security. He co-founded Timescale, a cloud platform for time-series data, and previously co-founded Illuminics Systems (acquired by Neustar). His work includes Ethane (basis for OpenFlow/SDN), CoralCDN, and contributions to blockchain-based systems like Blockstack. Education: Ph.D., Computer Science, New York University (Courant Institute), 2007 M.Eng. and S.B., MIT Research Interests: Freedman’s research spans distributed systems, cloud infrastructure, time-series databases, privacy-enhancing technologies, and software-defined networking. He emphasizes practical, scalable solutions for real-world challenges in networking and storage. Article Trends: Recent work focuses on time-series database optimizations (e.g., tiered storage, compression), cloud platform efficiency, GPU acceleration, and blockchain applications. His publications address fault tolerance, query optimization, and resource management in distributed systems. Awards: ACM Grace Murray Hopper Award, PECASE (2010), Sloan Fellowship, multiple best-paper awards at SIGCOMM, ICFP, and TCC. Advising & Grants: Technical advisor to Blockstack and recipient of grants from NSF, ONR, and DARPA. His research has been commercialized through startups like Timescale and Illuminics. Affiliations: Member of Princeton’s Center for Information Technology Policy (CITP), exploring societal impacts of technology.

Patrick Delfmannمشاهده پروفایل

استاد

• Business Process Management
• Process Mining
• Predictive Process Monitoring
• +۵ مورد دیگر

Prof. Dr. Patrick Delfmann is a University Professor at the Department of Computer Science (FB4) of the University of Koblenz, leading the Process Science research group. His roles include Research Dean of the Department and chairman of the Institute for Business and Administrative Information Systems. He holds a Dr. rer. pol. from the University of Münster (2006) and has held academic positions since 2002, including senior academic councillor roles and acting professorships before his current position since 2017. His research focuses on technological aspects of business process management, including process mining, predictive process monitoring, and ontology-based process engineering. Current projects include AI-DPA (funded by Rhineland-Palatinate) and DFG-funded MIB (declarative process models). Methodological foundations include algorithmic graph theory, computational linguistics, and quantum machine learning. Key achievements include the 2024 Best Paper Award at ICPM’s PODS4H workshop for process-oriented cancer data analysis. He advises on interdisciplinary theses requiring strong algorithmic and modeling skills, and collaborates with industry partners to ensure practical applicability of research outcomes. Education: PhD in Business Administration (2006), University of Münster; earlier roles as research assistant (2001–2013). Grants: DFG MIB Project (2023–), RLP AI-DPA Research College (2023–). Labs/Teams: Process Science Group develops tools like declare-js and ProPoneRe, focusing on predictive modeling and process compliance.

Mihai Mitreaمشاهده پروفایل

استاد

• Digital Signal Processing
• Multimedia Security
• Image and Video Processing
• +۴ مورد دیگر

Dr. Mihai Mitrea is a Professor at Telecom SudParis and a key member of the ARMEDIA research team. His work spans Digital Signal Processing , Multimedia Security , and Blockchain Technology , with a focus on video watermarking, content authentication, and adaptive media systems. Research Interests: Robust and semi-fragile video watermarking techniques Blockchain applications in media content tracking and authentication Statistical modeling for multimedia signal processing HEVC/MPEG-4 AVC domain analysis AI-driven sharpness-aware watermarking Recent Article Trends: His publications (2017–2025) highlight advancements in blockchain-assisted content verification, neural network watermarking robustness, and saliency detection in compressed video. Collaborative work with teams in France, Canada, and India further emphasizes cross-disciplinary applications in mobile multimedia and semantic remote display frameworks. Labs & Teams: Affiliated with ARMEDIA at Telecom SudParis, Professor Mitrea contributes to cutting-edge research in multimedia security and blockchain integration for Internet of Media Things (IoMT).

• Grid Computing
• Distributed Systems
• Cloud Computing
• +۷ مورد دیگر

João Nuno De Oliveira e Silva is an Assistant Professor at the Department of Informatics at Instituto Superior Técnico, University of Lisbon. He teaches Concurrent Programming, Systems Programming, and related courses during the 2024/2025 academic semester. His research focuses on distributed systems, grid computing, cloud computing, and cybersecurity, with notable contributions to secure dataflow programming for Android applications, blockchain-based agent collaboration, and distributed computing frameworks like NuBOINC. His work emphasizes parallel execution environments, resource efficiency in dataflow models, and secure middleware solutions for bags-of-tasks. Key research themes include: Grid and distributed computing architectures Secure distributed applications (e.g., SGX enclave migration, anti-repackaging systems) Cloud infrastructure optimization (A2Cloud, geo-replication QoS) Autonomous agent systems for internet routing domains Biometric authentication for legacy systems Automated biological monitoring systems Notable projects include Flowverine (privacy-sensitive Android apps), TEEnder (SGX enclave migration), and Mercury (automatic parallelization middleware). His work bridges theoretical computer science with practical implementations in distributed and cloud environments. He has collaborated on over 30 publications since 2017, focusing on both foundational research and applied systems development. His teaching and research emphasize hands-on experience with modern distributed computing challenges.

• Human Language Technologies
• Robust Speech Recognition
• Speaker and Language Characterization
• +۱۲ مورد دیگر

Alberto Abad is an Associate Professor at the Department of Computer Science and Engineering (DEI), Instituto Superior Técnico (IST), University of Lisbon, and a researcher at INESC-ID. He is the coordinator of the Human Language Technologies (HLT) laboratory at INESC-ID and the deputy coordinator of the Master in Computer Science and Engineering at IST. He holds a PhD and a degree in Telecommunication Engineering from the Technical University of Catalonia (UPC). He is also an IEEE Senior Member, ACM Member, and ISCA Member. Alberto Abad’s research interests include: Robust Speech Recognition Speaker and Language Characterization Applied Machine Learning Healthcare Applications of Speech Processing Privacy-Preserving Speech Technologies Speech as a Biomarker for Disease Detection His recent publications demonstrate a strong focus on privacy-aware speech systems, healthcare diagnostics (e.g., Parkinson’s and Alzheimer’s), children’s speech recognition, and secure speaker verification. He has contributed to over 100 peer-reviewed publications in top-tier conferences and journals such as IEEE TASLP, ICASSP, Interspeech, and LREC. Alberto Abad has been Principal Investigator for multiple national and international projects, including VITHEA (FCT), DIRHA (European), Biovisualspeech (CMU-Portugal), TAPAS ITN (EU), and currently leads the INESC-ID/IST contributions in the Accelerat.ai project. He actively collaborates with industry and startups in the field of speech technology. He has supervised over 25 Master’s theses and more than five PhD students, either as advisor or co-advisor, in areas such as speech biomarkers, privacy-preserving ML, children’s ASR, and cognitive disorder detection. He teaches graduate courses including Speech Processing, Programming Fundamentals, and Master’s Dissertation in Informatics and Computer Engineering. He is involved in the development of tools and platforms such as the SPA web-based platform for speech processing, the VITHEA virtual therapist for aphasia, and the BioVisualSpeech corpus and therapy system. His work bridges theoretical advances with real-world clinical and industrial applications.

Ritwik Guptaمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Ritwik Gupta is an Assistant Professor (starting Fall 2026) at the University of Maryland in the Department of Computer Science and the AI Interdisciplinary Institute. Concurrently, he serves as Technical Director for Autonomy at the Defense Innovation Unit (DIU) , focusing on AI governance and dual-use military-civil technology. Research Interests: His work bridges Artificial Intelligence , Computer Vision , and Technology Policy , with specific interests in physics-integrated vision models, multi-robot perception systems, AI governance frameworks, and climate modeling through hybrid physics-ML approaches. He advocates for data-centric policies over model-focused regulations and explores the societal implications of AI proliferation. Article Trends: Recent publications emphasize Bayesian behavior in LLMs through in-context learning Multi-scale geospatial analysis for climate and satellite imagery Critical evaluations of AI export control policies Advancements in vision-language interaction and dataset curation Awards: Best Paper at NeurIPS 2023 (D&B track) for ClimSim Timothy B. Campbell Innovation Award (2024) Outstanding Reviewer for CVPR 2025 Prospective Students: He encourages applicants to the University of Maryland CS Ph.D. or Public Policy Ph.D. programs to mention his name for advising opportunities, particularly in physics-integrated computer vision , multi-robot perception , and AI governance .

• Business Process Management
• Process Mining
• Automated Planning
• +۳ مورد دیگر

Andrea Marrella is a researcher at Sapienza University of Rome, Italy, with extensive contributions to Business Process Management (BPM), Process Mining, and Automated Planning. His work bridges process modeling with AI integration, IoT, and human-computer interaction, focusing on adaptive cyber-physical systems and data-driven decision making. He has co-authored over 139 publications since 2008.

Roee Shragaمشاهده پروفایل

استادیار

• Data Integration
• Data Discovery
• Human-in-the-loop Machine Learning
• +۷ مورد دیگر

Roee Shraga is an Assistant Professor in the Computer Science department and Data Science program at Worcester Polytechnic Institute (WPI). He previously held a Postdoctoral Research Associate position at the Data Lab within Khoury College of Computer Sciences at Northeastern University in Boston, MA. Ph.D. in Data Science, Technion – Israel Institute of Technology (2020) M.E. in Data Science, Technion (2017) B.Sc. in Industrial Engineering and Management (Information Management Engineering), Technion (2015) Shraga’s research focuses on Data Integration , Data Discovery , Human-in-the-loop Machine Learning , Information Retrieval , and Large Language Models (LLMs) . His work bridges data management, machine learning, and human-computer interaction to improve data quality in AI systems. Recent publications include advancements in LLM-driven data integration , semantic table union search , and contrastive entity resolution . Key contributions include the Explain-Da-V framework for semantic data versioning and FlexER for intent-aware entity resolution. Scientific recognition includes: iiWAS 2024 best paper award TaDA@VLDB24 best paper award Council for Higher Education (VATAT) scholarship Leonard & Diane Sherman Interdisciplinary Fellowship (2017) Daniel Excellence Scholarship (2019) Miriam & Aaron Gutwirth Memorial Fellowship (2020) He leads NSF-funded research on Human-in-the-loop AI (CRII grant) and co-organizes the HILDA workshop. His teams have won multiple Outstanding MQP Awards for undergraduate research.

• Logic
• Well Quasi-Orders
• Verification
• +۷ مورد دیگر

Sylvain Schmitz is a Professor of Computer Science at Université Paris Cité, affiliated with the Institut de Recherche en Informatique Fondamentale (IRIF). He leads the automata and applications team and is a member of the modelling and verification team. His research focuses on logic, well quasi-orders, verification, formal languages, and database theory. He is actively involved in the academic community, serving on steering and program committees for major conferences such as STACS, LICS, and CSL. PhD in Computer Science, defended on September 24, 2007, at I3S Laboratory, Sophia Antipolis. Habilitation titled Algorithmic Complexity of Well-Quasi-Orders , defended on November 27, 2017, at ENS Paris-Saclay. His research interests span logic, well quasi-orders, verification, formal languages, database theory, theoretical computer science, complexity theory, program verification, automata theory, and model checking. His recent work explores complexity bounds in vector addition systems, reachability problems, and logical foundations of verification. His publications exhibit a strong focus on theoretical foundations of computation, particularly in the analysis of infinite-state systems, complexity hierarchies beyond elementary, and logical characterizations of computational problems. Key themes include well-structured transition systems, non-elementary complexity, and applications of ordinal analysis to verification. IUF junior (2018–2023) Sylvain Schmitz has supervised several PhD students, including Hector Buffière, Aliaume Lopez, Anthony Lick, and Simon Halfon, often in joint supervision with researchers such as Jean Goubault-Larrecq, David Baelde, and Philippe Schnoebelen. His research has been funded by multiple ANR projects including BraVAS, PRODAQ, ReacHard, and AVeriSS. He is a key member of the IRIF laboratory, contributing to research in automata, verification, and logic. He has organized major events such as ICALP 2022 and RP 2020, and is deeply involved in the European theoretical computer science community through committee memberships and conference organization.

Philipp Terhörstمشاهده پروفایل

استادیار

• Responsible AI
• Biometrics
• Machine Learning
• +۳ مورد دیگر

Dr. Philipp Terhörst is a Research Group Leader at Paderborn University, specializing in Responsible AI for Biometrics . His work focuses on fairness, privacy, explainability, and uncertainty in machine learning systems for biometric applications. Education: Ph.D. in Computer Science (2021) from Technical University of Darmstadt Previous Affiliations: Fraunhofer IGD (2017–2022), ERCIM Fellowship at Norwegian University of Science and Technology His research addresses critical ethical challenges in biometric AI, including demographic bias mitigation , privacy-enhancing technologies , and confidence-aware verification systems . Recent publications explore explainability frameworks, backdoor attacks, and fairness in deepfake detection. Scientific contributions have earned awards from the European Association for Biometrics and International Joint Conference for Biometrics . He actively participates in academic service as a reviewer for TPAMI, CVPR, and IEEE journals. Teaching: Offers courses in Human-Centered Machine Learning Collaborations: Member of Transregional Collaborative Research Centre 318 Management Programs: Alumnus of the BMBF-funded 'Software Campus' initiative

• Internet of Things (IoT)
• Embedded Systems
• Precision Agriculture
• +۳ مورد دیگر

Deniz Taşkın is an Associate Professor at the Department of Computer Engineering , Trakya University , Turkey. He has served in various academic and administrative roles since 2002, including Head of Department of Information Technology (since 2024) and Deputy Head of Department (since 2016). Education: PhD in Computer Engineering (2007) Master's in Computer Engineering (2004) BSc in Computer Engineering (2002) Edirne Science High School (1998) Research Interests: His research focuses on Internet of Things (IoT) , Embedded Systems , and Precision Agriculture , with applications in sensor networks, wireless communication, and agricultural monitoring. He explores 3D Modeling techniques for optical systems and contributes to Cybersecurity in multimedia and IoT environments. Publication Trends: Deniz has published 15+ articles on IoT architectures, Bluetooth Low Energy sensor networks, 3D calibration methods, and video encryption. His work bridges Digital Circuit Design with Agricultural Technology , emphasizing energy efficiency and real-time data processing. Scientific Awards: 2017 Trakya Project Market: Electric Motor Driver for Autonomous Vehicles 2016 TÜBİTAK: Electromobile Category Runner-Up and Promotion Award 2015 TÜBİTAK: Solar-Powered Vehicle Design Award 2015 Edirne Governorship: Provincial Achievement Certificate Advising and Grants: He has supervised 5 PhD theses and 7 Master's theses , including projects on IoT in Precision Agriculture and FPGA Circuit Design . As a principal investigator, he led 8 scientific projects funded by Trakya University and KOSGEB, focusing on embedded systems, data security, and smart automation. Labs and Teams: He contributes to IoT Research and Embedded Systems Development at Trakya University, collaborating with multidisciplinary teams in agricultural technology and digital design. His work includes designing self-powered sensor nodes and FPGA-based hardware.

Sebastian Fischmeisterمشاهده پروفایل

استاد

• Embedded Systems
• Distributed Systems
• Formal Methods
• +۸ مورد دیگر

Sebastian Fischmeister is a Professor and NSERC/Magna Industrial Research Chair in Automotive Software for Connected and Automated Vehicles at the Department of Electrical and Computer Engineering, University of Waterloo. His research focuses on systems at the intersection of software technology, distributed systems, and formal methods, with applications in automotive systems, avionics, and medical devices. He has pioneered frameworks for scalable location-based pervasive computing and verifiable real-time communication schedules, contributing to the ASTM F29.21 standard. Education: Dipl.-Ing. in Computer Science (Vienna University of Technology, 2000), Ph.D. in Computer Science (University of Salzburg, 2002) Research Themes: Real-time embedded systems, runtime monitoring, security analysis, data analytics for validation, and performance evaluation. Scientific Awards: APART Stipend (2005) Ontario Early Researcher Award (2014) Multiple best paper and tool awards He is an ACM Distinguished Speaker and actively participates in organizing conferences such as ESCAR, RTSS, DATE, and ICPE. His work includes significant contributions to anomaly detection, cybersecurity in automotive networks, and runtime verification techniques under unreliable conditions.

• Natural Language Processing (NLP)
• Machine Learning
• Knowledge Representation
• +۳ مورد دیگر

Bhuwan Dhingra is an Assistant Professor of Computer Science at Duke University's Trinity College of Arts & Sciences. He focuses on Natural Language Processing (NLP) , machine learning , and knowledge representation , with specific interests in question answering , robustness to adversarial inputs , and model calibration . 2020 : Ph.D. in Language Technologies from Carnegie Mellon University 2013 : Master's Thesis on Local Quadrature Reconstruction on Smooth Manifolds at IIT Kanpur His research includes temporal language models , adversarial robustness , and combating misinformation . He leads the ALTER-Math NSF-funded project (2024-2027) and collaborates on CC* Integration-Large (2025-2027) for distributed GPU systems. His 2025 work on adversarial perturbations and 2024 studies on table understanding in materials science highlight his focus on LLM reliability and structured data integration . Notable awards include the Amazon Research Award (2022), NSF Medium Grant (2022), and Google Research Gift (2021). He advises PhD students like Rich Stureborg and undergraduates such as Angikar Ghosal (now at Stanford PhD). Teaching graduate courses like Introduction to NLP and Advanced NLP , he emphasizes long-form QA and collaborative writing in NLP.