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Halis AydemirView profile

Professor

• Hadith Studies
• Islamic Jurisprudence (Inheritance Calculation)
• Probability Theory in Hadith Transmission
• +3 more

Prof. Dr. Halis Aydemir is a Professor at the Department of Basic Islamic Sciences in Dumlupınar University's Faculty of Theology. He holds concurrent administrative roles including Vice Rector (2015–2019), Dean of the Faculty of Islamic Sciences (2015–2020), and Head of the Hadith Department. His academic journey includes a BSc in Electrical Engineering (Istanbul Technical University, 1995) and a PhD in Basic Islamic Sciences (Uludağ University, 2004). His research focuses on applying probability theory to Hadith transmission systems, developing mathematical models for inheritance calculations in Islamic law, and Arabic language education. Notable projects include the 'Al-Musnad al-Sahih' manuscript verification (2002–2012) and multiple inheritance calculation software projects. He has authored over 80 publications including critical editions of Hadith collections and theoretical works on Hadith reliability. Awards: No scientific awards explicitly mentioned. Administrative roles include leadership in religious affairs projects and educational software initiatives. Research highlights include probabilistic analysis of narrator reliability, isnad model evaluation, and digital tools for Islamic legal calculations. His work bridges traditional Islamic scholarship with modern quantitative methods.

Benjamin Mako HillView profile

Associate Professor

• Peer Production
• Online Communities
• Collective Action
• +7 more

Benjamin Mako Hill is an Associate Professor in the University of Washington Department of Communication and an Adjunct Associate Professor in Human-Centered Design & Engineering , the Paul G. Allen School of Computer Science & Engineering , and the Information School at UW. He is a Faculty Associate at the Berkman Klein Center for Internet and Society at Harvard University and a Fellow at the Center for Information Technology Policy at Princeton University during the 2023–2024 academic year. Educational Background : PhD in an interdepartmental program at Massachusetts Institute of Technology (MIT) , involving the MIT Sloan School of Management and the MIT Media Lab , advised by Eric von Hippel, Yochai Benkler, Tom Malone, and Mitch Resnick. MS in Media Arts and Sciences from MIT. B.A. in Technological and Legal History from Hampshire College . Research Interests span peer production, online communities, collective action, cooperation, learning, and computer-mediated communication. His work explores how communication and information technologies shape social outcomes in collaborative environments like Wikipedia and Linux, focusing on governance, moderation, anonymity, and educational platforms such as Scratch. Article Trends : His publications analyze peer production dynamics, privacy in open collaboration, and computational thinking in youth. Topics include underproduction in open source software, algorithmic fairness, taboo knowledge production, and legitimate peripheral participation in online communities. Methodologies combine big data, quasi-experimental, and comparative analyses. Scientific Awards : Dordick Award for Best Dissertation (2013). CHI '22 Best Paper Honorable Mention (2022). CSCW '18 Best Paper Honorable Mention (2018). CHI '17 Best Paper Honorable Mention (2017). CSCW '13 Best Paper Award (2013). CHI '11 Best Paper Honorable Mention (2011). Advising and Grants : He co-founded the Community Data Science Collective and collaborates with researchers like Aaron Shaw. Grants include multiple National Science Foundation awards for studies on digital knowledge commons, anonymous participation, and collaborative success, as well as a Sloan Foundation grant for modeling underproduction in peer production. Labs and Teams : He leads the Community Data Science Collective , an interdisciplinary research group studying online communities, and contributes to open-source projects like Debian and Ubuntu . He actively edits Wikimedia projects and participates in the Cascadia Wikimedians User Group .

• Language Models
• Diffusion Models
• Theory of Deep Learning
• +6 more

Song Mei is an Assistant Professor in the Department of Statistics and Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. She received her Ph.D. from Stanford University in 2020 under Andrea Montanari and maintains active research collaborations with institutions including Amazon (as a 2023 Amazon Research Award recipient) and OpenAI (where she is currently on leave). Her research spans the intersection of statistics, machine learning, information theory, and computer science, with particular emphasis on foundational theories for modern AI systems. Key interests include language models, diffusion models, quantum algorithms, and high-dimensional statistics, often leveraging insights from statistical physics literature. Analysis of her recent publications reveals a strong focus on theoretical underpinnings of generative AI, with significant contributions to understanding contrastive pre-training (CLIP), attention mechanisms in LLMs, and mathematical foundations of diffusion models. Her work demonstrates consistent interdisciplinary connections between statistical theory and practical AI development. Sloan Research Fellowship (2025) Noether Early Career Scholar Award (2025) Google Research Scholar Award (2024) Amazon Research Award (2024) She actively advises graduate students through MA programs and has secured significant research grants including Amazon Research Awards. Her work with AGI Labs at Amazon demonstrates applied impact of theoretical research. Current projects focus on mechanistic interpretability of large language models and mathematical frameworks for generative AI. Professor Mei leads research on the statistical principles behind frontier AI models, with particular focus on developing rigorous theoretical frameworks for understanding emergent behaviors in large-scale systems.

Jennifer L ClarkeView profile

Professor

• Statistical Methodology
• Bioinformatics/Computational Biology
• Data Mining/Machine Learning
• +3 more

Jennifer L. Clarke is a Professor in the Department of Statistics at the University of Nebraska–Lincoln and Director of the Quantitative Life Science Initiative. She holds leadership roles in enabling big data integration across the University of Nebraska system through collaborative research programs. Her affiliations include the Institute of Agriculture and Natural Resources (IANR) and the College of Agriculture and Natural Resources. Dr. Clarke's research focuses on statistical methodology for high-dimensional data, computational biology, bioinformatics, and bacterial genomics. Her work bridges statistical innovation with applications in oncology, microbiome analysis, and agricultural phenomics. Key areas include predictive modeling, machine learning, and genomic/metagenomic data integration. Her recent publications span cancer biomarker discovery, plant phenotyping methodologies, and microbial community analysis, reflecting her interdisciplinary approach. Articles emphasize translational applications like therapeutic target identification and precision agriculture. Dr. Clarke leads initiatives fostering collaboration between statisticians and domain scientists, including the Quantitative Life Science Initiative and contributions to the Agricultural Genome-to-Phenome Initiative (AG2PI). Her work advances data-driven solutions for healthcare and food security challenges. Notable projects include developing statistical tools for microbiome studies, analyzing root architecture via 3D imaging, and investigating cranberry-derived compounds' cancer-inhibitory mechanisms. Her methodological contributions include hybrid clustering techniques and predictive model validation frameworks.

Vijay KumarView profile

Professor

• Robotics
• Multi-Robot Systems
• Micro Aerial Vehicles
• +6 more

Vijay Kumar is the Nemirovsky Family Dean of Penn Engineering at the University of Pennsylvania, with faculty appointments in the Departments of Mechanical Engineering, Computer and Information Science, and Electrical and Systems Engineering. He is a leading figure in robotics and computer architecture research. Research Interests include robotics, particularly multi-robot systems and micro aerial vehicles (MAVs), as well as computer architecture innovations for machine learning, GPU acceleration, and datacenter efficiency. His work spans theoretical foundations and practical applications in autonomous systems and hardware optimization. Scientific Awards include: 1991 NSF Presidential Young Investigator Award 1996 Lindback Award for Distinguished Teaching 2012 ASME Mechanisms and Robotics Award 2014 Engelberger Robotics Award 2017 IEEE George Saridis Leadership Award Multiple best paper awards at DARS, ICRA, and RSS conferences Editorial Leadership includes serving as Editor of the ASME Journal of Mechanisms and Robotics and Advisory Board Member of AAAS Science Robotics Journal . His GRASP Lab team developed foundational frameworks for micro UAV testbeds and swarm robotics.

• Algorithmic Game Theory
• Concurrent Systems
• Formal Verification
• +3 more

Dr. Rasmus Ibsen-Jensen is a Lecturer in Computer Science at the University of Liverpool. Previously, he held a Postdoctoral position at IST Austria under Krishnendu Chatterjee and completed his PhD under Peter Bro Miltersen. Research Focus: Algorithmic game theory, strategy complexity in two-player zero-sum games, control flow graph algorithms, edit distance for automata, and theoretical biology applications. Teaching: Module Coordinator for second-year courses in database development (COMP207), C++ programming (COMP282), and industrial placement (COMP299). His work bridges computational game theory and formal verification, with recent publications exploring memory constraints in partial-information games, algebraic path properties in concurrent systems, and evolutionary spatial dynamics. While no scientific awards are explicitly mentioned in the provided text, his contributions to algorithmic complexity and interdisciplinary research (e.g., theoretical biology) highlight his academic impact.

• Educational Technology
• Human-Computer Interaction
• Data Science
• +4 more

Prof. April Wang is an Assistant Professor in the Department of Computer Science at ETH Zurich. Her work focuses on Educational Technology, Human-Computer Interaction, and AI-driven tools for programming education. She is affiliated with the Professur Educational Technology group and teaches courses such as Human Computer Interaction and Ethics in Computing. Her research explores interactive learning environments, collaborative data science workflows, and AI-augmented educational systems. Her research interests span computational notebooks, live coding interfaces, and human-AI collaboration in software development. Notable contributions include frameworks like DBox for algorithm learning and EDBooks for interactive programming narratives. She also investigates challenges in real-time collaboration tools and automated documentation systems for data scientists. Recent work emphasizes understanding user needs in automated copilot systems and resolving conflicts in collaborative notebook environments. Her projects often bridge theoretical HCI principles with practical educational tools, aiming to enhance both instructor efficacy and student engagement. Prof. Wang’s teaching portfolio includes courses on user-centered interface design and ethical scientific practices. She actively contributes to advancing interdisciplinary computational literacy through initiatives like datAR, which uses everyday objects to teach data concepts.

John K VanDykView profile

Adjunct Assistant Professor

• Information Technology
• Entomology
• Web Development
• +2 more

Dr. John K VanDyk is an Adjunct Assistant Professor at Iowa State University, affiliated with the College of Agriculture and Life Sciences and Department of Entomology. He manages the CALS/LAS Web Team and maintains BugGuide.net, a major online arthropod resource. His research bridges information technology and entomology, focusing on biodiversity databases, web development, and citizen science platforms. Educational background includes a PhD and MS from Iowa State University and BS from Dordt University. Digital Projects: BugGuide.net, ISU Sites service Technical Expertise: Drupal development, data systems architecture

• Biomedical Signal and Image Processing
• Cardiovascular and Neural Modeling
• Physiologically-interpretable Artificial Intelligence systems
• +5 more

Gaetano Valenza is an Associate Professor of Bioengineering at the University of Pisa, Italy, where he leads the Neuro-Cardiovascular Intelligence Lab at the Enrico Piaggio Research Centre. He holds affiliations with the Neuroscience Statistics Research Laboratory at MIT and has served as a Research Fellow at Harvard Medical School and Massachusetts General Hospital. His academic work spans bioengineering, computational physiology, and affective computing. His research focuses on statistical and nonlinear biomedical signal and image processing , cardiovascular and neural modeling , and physiologically interpretable artificial intelligence . He develops wearable systems for physiological monitoring, with applications in autonomic nervous system assessment, brain-heart interactions, and mental health. His work has led to novel metrics such as the Sympathetic and Parasympathetic activity indices derived from ECG. The 15 most recent publications reflect a consistent trend in brain-heart interplay , complexity analysis of physiological signals , explainable AI in healthcare , and virtual reality applications in mental health . His work integrates advanced signal processing, nonlinear dynamics, and machine learning to decode emotional and cognitive states from physiological data. Dr. Valenza is a Senior Member of IEEE and serves on several technical committees. He is an active editorial leader, currently serving as Associate Editor for IEEE-EMBC , Plos One , Complexity , and Scientific Reports , and has guest-edited special issues in Philosophical Transactions of the Royal Society A and IEEE Journal of Biomedical and Health Informatics . He has led or participated in numerous international research projects, including FP7 and H2020 initiatives such as NEVERMIND and EXPERIENCE. He teaches courses in Biostatistics, Probability & Biostatistics, and Advanced Image Processing at the University of Pisa. As lab head and project coordinator, he leads a multidisciplinary team working on neuro-cardiovascular intelligence, wearable systems, and AI-driven mental health interventions.

• Security
• Cryptography
• Theoretical Computer Science
• +3 more

Yan Huang is an Associate Professor in the Department of Computer Science at Indiana University Bloomington, focusing on security and cryptography. His work bridges theoretical foundations with practical systems, emphasizing cryptographic protocols with strong security guarantees for generic computation. University: Indiana University Bloomington School: College of Arts and Sciences Department: Computer Science Academic Rank: Associate Professor His research combines theoretical computer science , program analysis , artificial intelligence , and software engineering to address real-world security problems. Key areas include secure computation , zero-knowledge proofs , and privacy-preserving technologies . Recent publications, such as Phecda (SP'25) and Dubhe (USENIX Security'23), highlight advancements in post-quantum cryptography , AES verification , and privacy-preserving deep packet inspection , reflecting his focus on scalable and practical cryptographic solutions. He has advised notable students including Changchang Ding (PhD, Computer Science) and Ruiyu Zhu (PhD, now at Facebook), and served on program committees for top conferences like ACM CCS and CRYPTO .

Bimlesh WadhwaView profile

Associate Professor

• Software Engineering
• Human-Computer Interaction (HCI)
• Computing Education
• +4 more

Dr. Bimlesh Wadhwa is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS) and serves as Assistant Dean for Student Life at Tembusu College. She holds dual affiliations as a Residential Fellow at Tembusu College and an active member of the School of Computing's academic community. Her work bridges software engineering, human-computer interaction (HCI), and computing education. Dr. Wadhwa's research focuses on gender issues in HCI, software design quality, and digital well-being. She has pioneered initiatives like the Code for Community program to bring computing education to underserved groups. Her pedagogical contributions include developing courses on object-oriented design, software engineering principles, and interaction design. She actively engages with professional communities through roles such as Faculty Representative at the Singapore Computer Society Student Chapter and advisor to the Computing Club at NUS. Her recent work addresses pressing societal challenges like technology-facilitated sexual violence and integrates AI into educational contexts. She has organized major competitions including CodeXtreme and the Singapore Science and Engineering Fair, fostering innovation among students. Her interdisciplinary collaborations span healthcare applications, smart city technologies, and educational equity initiatives. Dr. Wadhwa’s scholarly contributions include over 80 publications in top venues such as FSE, CHI, and IEEE conferences. She has co-edited book chapters for Springer and Wiley on HCI and informatics, reflecting her commitment to advancing both technical and societal dimensions of computing. In addition to her academic roles, she leads MakerLab initiatives and contributes to national educational policies on computational thinking. Her work emphasizes bridging academia-industry gaps through projects like the GEAR mobile game-assisted rehabilitation system and cloud service brokerage frameworks.

• Computer Architecture
• Non-Volatile Memory Systems
• Deep Learning Systems
• +3 more

Jishen Zhao is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, San Diego (Jacobs School of Engineering). His research focuses on computer architecture, non-volatile memory systems, and deep learning acceleration. Dr. Zhao has published extensively in top venues including ISCA, MICRO, ASPLOS, and IEEE Transactions. He collaborates with researchers at UCSD and beyond to advance systems for emerging applications in AI and autonomous vehicles. Dr. Zhao's primary research areas include persistent memory systems, hardware/software co-design for deep learning, and safety-critical computing. He develops techniques for crash consistency, memory disaggregation, and efficient neural network deployment. His work on autonomous vehicles addresses scenario generation and perception-aware system design. Recent projects explore LLM applications for software engineering and hardware verification. Analysis of Dr. Zhao's 2024-2025 publications reveals a strong shift toward AI-integrated systems research. He applies large language models to tasks like RTL verification and software issue localization while continuing to innovate in memory systems for serverless computing. There is growing emphasis on safety-critical systems for autonomous vehicles and energy-efficient neural network training using novel hardware architectures. Information about Dr. Zhao's scientific awards, advising activities, grants, and laboratory facilities was not available in the provided documentation.

Andre BergerView profile

Associate Professor

• Operations Research
• Optimization Algorithms
• Combinatorial Optimization
• +3 more

Andre Berger is an Associate Professor of Operations Research at Maastricht University, affiliated with the QE Operations Research department within the School of Business and Economics. He holds a PhD in Mathematics from Emory University (2006) and completed a postdoc at Technical University Berlin. His research focuses on optimization algorithms, combinatorial optimization, and their applications in scheduling, network design, and operations research. Notable contributions include work on the many-visits Traveling Salesman Problem and cluster editing algorithms. Berger’s recent publications span scheduling theory, MRI-based clinical research collaborations, and theoretical advancements in facility location models. He is based at Tongersestraat 53, Maastricht, and can be reached via a.berger@maastrichtuniversity.nl. Education: MSc in Mathematics, Emory University (2003) PhD in Mathematics, Emory University (2006) Research Interests: Berger’s work bridges theoretical computer science and practical applications in operations research, emphasizing algorithm design for complex optimization problems. Key areas include scheduling algorithms, network flow optimization, and geometric optimization challenges such as the Apollonius problem in facility location. His interdisciplinary approach integrates mathematical programming with real-world scenarios in telecommunications and healthcare.

Liangming PanView profile

Assistant Professor

• Natural Language Processing
• Large Language Models
• Machine Learning
• +3 more

Liangming Pan is an Assistant Professor at the University of Arizona's College of Information Science. His research focuses on building trustworthy large language models (LLMs) with an emphasis on logical reasoning, truthfulness, and safety. He holds a PhD in Computer Science from the National University of Singapore (2022), a Master's from Tsinghua University, and a Bachelor's from Beihang University. Education : PhD in Computer Science, National University of Singapore (2022) Master of Engineering in Computer Science, Tsinghua University (2017) Bachelor of Engineering in Computer Science, Beihang University (2014) Research Interests : Dr. Pan's work centers on enhancing LLMs' reliability through: Logical reasoning mechanisms to ensure faithful deductions Truthfulness verification to combat misinformation Safety protocols to mitigate societal harm Key Contributions : Developed TART, an open-source framework for explainable table-based reasoning Created benchmarks like SCITAB and FactCheck-Bench for evaluating LLMs Advanced techniques for knowledge editing and causal reasoning Awards : Best Paper Runner-Up at NeurIPS Table Representation Workshop (2024) Area Chair Award for Question Answering (IJCNLP-AACL 2023) Service & Outreach : He serves as an Area Chair for EMNLP (2024), COLING (2025), and ACL (2024). He has delivered invited talks at Tsinghua University, Peking University, and other institutions.

Nick MontfortView profile

Professor

• Digital Media
• Electronic Literature
• Computational Poetry
• +3 more

Nick Montfort is a Professor of Digital Media at Massachusetts Institute of Technology (MIT) and Professor II & Principal Investigator at the University of Bergen 's Center for Digital Narrative. He directs MIT's Trope Tank lab/studio and contributes to platform studies, critical code studies, and electronic literature. Ph.D. in Computer and Information Science from University of Pennsylvania (2007) M.A. in Creative Writing (Poetry) from Boston University (2001) S.M. in Media Arts and Sciences from MIT (1998) B.S./B.A. in Computer Science and Liberal Arts from University of Texas at Austin (1995) Montfort's research focuses on computational creativity and digital poetics , particularly through exploratory programming and constraint-based writing . He has developed over ten computer-generated print books and co-edited MIT Press volumes like The Future and The New Media Reader . His work bridges computer science and literary arts , emphasizing algorithmic expression and platform-specific creation. His recent computational works include All the Way for the Win (2025), written entirely in three-letter words, and collaborations like The Deletionist and Sea and Spar Between . Notable books cover interactive fiction ( Twisty Little Passages ), platform studies ( Racing the Beam ), and generative literature ( 10 PRINT ). He also co-edits the Hardcopy and Using Electricity book series. Montfort's academic contributions span digital narrative systems , creative code , and computer-generated literature . His 101 BASIC Poems and Output: An Anthology of Computer-Generated Text exemplify his focus on code as cultural artifact and algorithmic literary practice . He has presented at major conferences including ELO, C&C, and Digital Arts and Culture, addressing topics from minimalist computational poems to narrative modeling . Through collaborations with institutions like University of Bergen and MIT's Comparative Media Studies/Writing, Montfort explores digital storytelling , machine-generated poetry , and platform-specific creativity . His academic leadership includes directing the Trope Tank and co-founding Bad Quarto press.