جست‌وجوی استاد و پژوهشگر

Nate Fosterمشاهده پروفایل

استاد

• Programming Languages
• Networking
• Databases
• +۵ مورد دیگر

Nate Foster is a Professor of Computer Science at Cornell University and currently serves as the Associate Dean for Research in the Ann S. Bowers College of Computing and Information Science. He is also a Visiting Researcher at Jane Street and served as a Visiting Professor at École Polytechnique Fédérale de Lausanne during the 2023-24 academic year. His research uses ideas from programming languages to solve problems in networking, databases, and security. BA in Computer Science, Williams College (2001) MPhil in History and Philosophy of Science, University of Cambridge (2008, all work completed in 2003) PhD in Computer and Information Science, University of Pennsylvania (2009) Foster's research focuses on developing languages and tools that make it easy for programmers to build secure and reliable systems. His current work centers on the design and implementation of languages and tools for programmable networks, particularly using the P4 language. His past work includes bidirectional languages (also known as 'lenses'), database query languages, data provenance, type systems, mechanized proof, and formal semantics. His research group at Cornell has made significant contributions to network verification, software-defined networking, and formal foundations for programmable data planes. Analysis of Foster's recent publications reveals a strong focus on network verification and programming language foundations for networking. His work consistently applies formal methods to practical networking problems, with a particular emphasis on the NetKAT and P4 languages. Over the past five years, his research has evolved toward more complex network verification techniques, including infinite state verification, active learning of network models, and dependently-typed approaches to network programming. His work bridges theoretical computer science with practical networking systems, making formal methods accessible to network engineers. ACM Fellow (2025) ACM SIGPLAN Robin Milner Award (2023) ACM SIGCOMM Rising Star Award (2018) NSF CAREER Award (2013) Alfred P. Sloan Fellowship (2012) Multiple distinguished paper awards across top conferences including POPL, PLDI, and SIGCOMM Foster has advised numerous PhD and Master's students who have gone on to prominent positions in both industry and academia, with many continuing work in programming languages and networking. He has led multiple significant research grants including an NSF CAREER Award and has been involved in the P4 Language Consortium, serving as Chair of the P4 Language Governing Board. His work has been supported by various organizations including NSF, DARPA, and industry partners like Intel and Jane Street. Foster is also active in the programming languages research community, serving on numerous program committees and as Vice Chair of DARPA's Information Science and Technology (ISAT) study group. Foster leads a vibrant research group at Cornell focused on programming languages for networks, with collaborators from academia and industry. His group has developed several influential tools and frameworks including NetKAT, Petr4, and KATch. They maintain strong connections with the P4 community and work closely with industry partners to ensure their research has practical impact on real-world networking systems.

• Financial Reporting
• Corporate Disclosure
• Textual Analysis in Accounting
• +۲ مورد دیگر

Yaping Zheng serves as an Assistant Professor in the Department of Accounting and Business Analytics within the Alberta School of Business at the University of Alberta. Her current teaching responsibilities include ACCTG 222: Introduction to Accounting for Management Decision Making, a course focused on cost behavior analysis, budgeting, and performance measures for management decisions, scheduled for Winter Term 2026 with office location at 3-21C Business Building. Her research spans critical areas in contemporary accounting: Financial Reporting and Corporate Disclosure mechanisms Textual Analysis applications in accounting contexts Big Data integration for financial analysts Management decision-making through accounting information systems Dr. Zheng's recent publication in Management Science (2025) examines empirical evidence of big data adoption by financial analysts, revealing its impact on disclosure practices and reporting usefulness. This work bridges advanced analytics with traditional accounting frameworks to address evolving market demands. No scientific awards were documented in the source materials, though publication in this premier journal signifies substantial scholarly contribution. Information regarding student supervision, research grants, or laboratory affiliations was not provided in the available texts.

Khuzaima Daudjeeمشاهده پروفایل

استاد

• Distributed Systems
• Database Management
• Cloud Computing
• +۳ مورد دیگر

Khuzaima Daudjee is a Professor and David R. Cheriton Faculty Fellow in the Cheriton School of Computer Science at the University of Waterloo. His research focuses on systems-oriented problems at the intersection of systems and data management, particularly building large-scale systems, storage infrastructure in the cloud, and modern hardware applications. He leads projects in distributed database systems, elastic scaling, and resource optimization. His recent work includes Caerus (geo-replicated transactions), Tiresias (predictive storage), and MorphoSys (automatic physical design metamorphosis). Daudjee has chaired major conferences including ICDE 2026 and serves on editorial boards for VLDB, SIGMOD, and IEEE TKDE journals. His awards include ACM Distinguished Scientist and multiple best paper awards. Educational initiatives include developing distributed systems teaching materials and supervising graduate students across database and distributed systems domains. His industry collaborations involve cloud infrastructure optimization and scalable data processing frameworks.

Aditya Parameswaranمشاهده پروفایل

دانشیار

• Database Systems
• Human-Computer Interaction
• Data Analytics
• +۳ مورد دیگر

Aditya Parameswaran is an Associate Professor in the Electrical Engineering and Computer Sciences (EECS) department at the University of California, Berkeley. He co-directs the EPIC Data Lab and the Police Records Access project, focusing on simplifying data science at scale through human-in-the-loop systems, LLM-powered tools, and scalable data systems. His research spans database systems, human-computer interaction, and machine learning, with notable contributions in tools like Lux, Modin, and DataSpread. Education : PhD in Computer Science from Stanford University (2013) BTech in Computer Science and Engineering from IIT Bombay (2007) Research Interests : Parameswaran's work centers on empowering end-users with intuitive data tools. Recent projects include LLM-powered systems for document processing (DocETL, TWIX), proactive data systems, and benchmarking frameworks. He emphasizes democratizing data science through low/no-code solutions and improving production ML workflows. Articles Trends : His recent work (2023–2025) prioritizes LLM integration into data systems, focusing on robust pipelines, assertion generation (SPADE), and debugging tools (RAGGY). Earlier contributions include visualization recommendation (Lux), scalable dataframes (Modin), and spreadsheet optimization (DataSpread). Awards : Recipient of the VLDB Early Career Award (2019), Sloan Research Fellowship (2020), NSF CAREER Award (2017), and multiple best paper/demonstration awards at top venues like SIGMOD and VLDB. Advising & Grants : Guides over 20 PhD/postdoc alumni, many now in academia (e.g., Madelon Hulsebos at CWI) and industry leadership roles. Active in securing grants (e.g., NSF, Army Research Office) and industry partnerships (e.g., Snowflake, LangChain). Labs/Teams : Leads the EPIC Data Lab, focusing on agentic data systems, and co-founded Ponder (acquired by Snowflake). Collaborates on the Police Records Access initiative, building transparency tools for public records.

• Database Management Systems
• Self-Driving Database Architectures
• Transaction Processing Systems
• +۴ مورد دیگر

Andy Pavlo is an Associate Professor with Indefinite Tenure in the Computer Science Department at Carnegie Mellon University's School of Computer Science. He is an active member of the CMU Database Group and the Parallel Data Laboratory, where he leads research in database management systems with a focus on self-driving architectures, transaction processing, and large-scale analytics. His work bridges academic research and industry applications through projects like NoisePage, OtterTune (which he co-founded and served as CEO before it ceased operations), and Peloton. Dr. Pavlo's research interests span database management systems with particular emphasis on autonomous database architectures that can self-tune and optimize without human intervention. His work explores transaction processing systems that can handle high-throughput workloads while maintaining consistency, and large-scale data analytics techniques that efficiently process massive datasets. He has made significant contributions to query optimization, database extensibility, and automatic database tuning using machine learning techniques. His recent work on database extensibility revealed critical issues in PostgreSQL's extension ecosystem, showing that approximately 16% of extensions are incompatible with at least one other extension due to API violations and memory errors. His research output demonstrates a consistent focus on practical database systems challenges, with recent publications examining database extensibility, user-defined function optimization, and the cyclical nature of database research. The articles show a strong trend toward making database systems more autonomous, with increasing integration of machine learning techniques for automatic tuning and optimization. His work often combines deep theoretical analysis with practical implementation in open-source systems. Dijkstra Award 2024 for contributions to database systems research Dr. Pavlo actively mentors graduate students, with current advisees including Wan Shen Lim, William Zhang, and Sam Arch (co-advised with Todd Mowry). His former students have gone on to successful careers in both industry and academia. He has secured significant research funding through CMU's affiliate program with major database companies including ClickHouse, DataStax, dbt, Firebolt, MotherDuck, RelationalAI, SingleStore, Spiral, PingCAP/TiDB, Yellowbrick, and Yugabyte. His research is supported by these industry partnerships and likely includes NSF funding given his active participation in the database research community. At CMU, Dr. Pavlo leads the Database Group and organizes several seminar series including "SQL or Death," "Database Building Blocks," and "ML⇄DB Technical Talks." These seminars bring together researchers and practitioners to discuss cutting-edge developments in database systems. He also runs a summer research internship program that has attracted students for multiple consecutive years, indicating a strong research group with ongoing projects and funding.

Janna Parkerمشاهده پروفایل

استاد

• Retailing
• Digital Marketing
• Advertising
• +۴ مورد دیگر

Janna Parker is a professor in the Department of Marketing at James Madison University, specializing in digital marketing, retailing, and nonprofit marketing. With a career transition from political campaigns, she focuses on social media's role in personal and professional branding. Her research examines work-personal social media boundaries, employer governance policies, and volunteerism in nonprofit contexts. Education: Bachelor's in History (California State University Sacramento), Master's (Cameron University), Doctorate (Louisiana Tech) Teaching Interests: Digital marketing education, social media strategy, nonprofit marketing Her scholarly work spans social media governance, volunteer engagement, and retail dynamics, with recent emphasis on digital marketing pedagogy and cancel culture implications. Parker has contributed to academic journals through empirical studies and conceptual commentaries. Key article trends include: Digital marketing education evolution (2024) Social media governance in corporate and nonprofit contexts (2024) Online teaching satisfaction in higher education (2022) Volunteer brand community dynamics (2020) Consumer behavior frameworks (2019) Her media appearances include expert commentary on holiday retail strategies and social media research, reflecting practical applications of her academic work.

Colin Jonesمشاهده پروفایل

دانشیار

• Optimal Control
• Model Predictive Control
• Optimization
• +۶ مورد دیگر

Colin Jones is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the Automatic Control Laboratory, School of Engineering. He earned his BASc and MASc in Electrical Engineering and Mathematics from the University of British Columbia (1994-2002) and a PhD in Control Theory from the University of Cambridge (2002-2005). Prior to EPFL, he was an assistant professor there and a senior researcher at ETH Zürich. Current role: Director of the Robotics, Control, and Intelligent Systems Doctoral Program at EPFL Research focus: Optimization-based and model predictive control (MPC) for renewable energy systems, green energy management, and data-driven control methods His recent work (2023-2025) spans high-speed predictive control , smart grid optimization , and physically consistent neural networks , with applications to buildings, hovercrafts, and power systems. He has secured an ERC Starting Grant for his research on optimal control of building networks. Publications include over 200 papers in journals like Automatica , IEEE Transactions , and Energy and Buildings . Notable article trends include distributed optimization , data privacy in energy systems , and nonlinear MPC for autonomous vehicles . Scientific Awards : ERC Starting Grant for optimal control of building networks Advising : Supervises 10 current PhD students and has advised 19 past PhD students, including Alessandretti Andrea and Diwale Sanket Sanjay. Grants and projects emphasize smart energy systems , predictive demand response , and nonlinear control .

Zhuoyue Zhaoمشاهده پروفایل

استادیار

• Database systems
• Security
• Query processing
• +۶ مورد دیگر

Zhuoyue Zhao is an Assistant Professor in the Department of Computer Science and Engineering at the University at Buffalo, School of Engineering and Applied Sciences. His office is located at 338I Davis Hall, Buffalo, NY 14260, and he can be reached at zzhao35@buffalo.edu or by phone at (716) 645-4735. Dr. Zhao received his PhD in Computer Science from the University of Utah in 2021, where he was advised by Prof. Feifei Li and Prof. Jeff Phillips. Prior to that, he earned his BS in Computer Science from Shanghai Jiao Tong University in 2016, where he was part of the prestigious ACM Class. During his undergraduate studies, he conducted research under Prof. Kenny Zhu and spent Fall 2015 as a research assistant at Hong Kong Polytechnic University supervised by Prof. Eric Lo. Dr. Zhao's research focuses on database management systems, with specific emphasis on traditional and approximate query processing, query optimization, database systems on modern hardware, transaction processing, indexing, and storage. His work bridges theoretical foundations with practical implementations, often resulting in systems that address real-world database challenges. He has made significant contributions to probabilistic query processing, transaction scheduling, and learned indexing techniques. His recent publications demonstrate a clear trajectory toward optimizing database performance in hybrid transactional/analytical processing environments. His research increasingly integrates systems techniques with machine learning approaches, particularly in the area of learned indexes. There's also a strong focus on making database operations more efficient through innovative scheduling mechanisms and query processing techniques that can handle concurrent updates. Google PhD Fellowship (2019-2021) Best Paper Award at SIGMOD 2016 for "Wander Join: Online Aggregation via Random Walks" Best Paper Award at SIGMOD 2025 for "Low-Latency Transaction Scheduling via Userspace Interrupts" Dr. Zhao currently advises several PhD students including Yunnan Yu, Congying Wang, Gaoxiang Liu (co-advised with Prof. Ziming Zhao), and Zhuoran Li. He has successfully guided MS student Nithin Sastry Tellapuri to graduation (Fall 2023), who is now employed at AirPay. His research is supported by significant funding including an NSF CAREER award (#2339596) totaling $599,977 for research on "Speedy and Reliable Approximate Queries in Hybrid Transactional/Analytical Systems" (2024-2029) and an unrestricted Google gift of $30,000 (2021). Dr. Zhao leads the ADBLab research group at UB, where students work on cutting-edge database systems research. His lab focuses on building practical database systems that address real-world challenges in query processing, transaction management, and indexing. The lab maintains strong connections with industry partners and regularly contributes to open-source database projects.

Michael Baldeaمشاهده پروفایل

دانشیار

• Process Systems Engineering
• Energy Systems
• Nonlinear Optimization
• +۳ مورد دیگر

Michael Baldea is an Associate Professor in the Department of Chemical Engineering at the University of Texas at Austin . He holds a Ph.D. in Chemical Engineering from the University of Minnesota (2006), with prior degrees from 'Babeş-Bolyai' University in Romania (M.Sc. 2001, Diploma 2000). His research group develops theoretical and computational methods for Process and Energy Systems Engineering , focusing on integrated decision-making, performance optimization, and process intensification with industrial validation. Education: Ph.D., Chemical Engineering, University of Minnesota (2006) M.Sc., Interface Process Engineering, 'Babeş-Bolyai' University (2001) Diploma, Chemical Engineering, 'Babeş-Bolyai' University (2000) Research Thrusts: Integrated decision-making in chemical/energy supply chains Process performance monitoring and optimization Process integration and intensification Key applications include grid-responsive chemical plants, intensified distillation/column designs, and renewable energy integration for building systems. Scientific Awards: Frank A. Liddell, Jr. Fellowship NSF CAREER Award (2015-2020) Moncrief Grand Challenges Faculty Award (2014) AIChE Outstanding Young Researcher Award (2017) Implementation : His group has translated research into commercial tools through partnerships with industrial test beds and is working to integrate methods into commercial simulators. They explore predictive approaches for building energy management and strategic capital investment analysis in next-generation energy systems.

• Corruption and Governance
• Economic Development
• Political Settlements
• +۵ مورد دیگر

Mushtaq Khan is a Professor in the Department of Economics at SOAS University of London . His research focuses on governance, corruption, industrial policy, and structural transformation in developing countries, with particular emphasis on Bangladesh, Nepal, and Nigeria. Research Interests : Corruption and Anti-Corruption Strategies Political Settlements and Governance Industrial Policy Design Climate Adaptation and Public Health Systems Policy Contributions : His work addresses challenges such as collusive contracting in energy sectors, doctor absenteeism in rural healthcare, and dual-use climate projects as anti-corruption tools. Advising : He has supervised theses on industrial policy in Nigeria, economic transformation in Rwanda, and federalism in Nepal.

Magda Posaniمشاهده پروفایل

استادیار

• Building Physics
• Hygrothermal Behavior of Materials
• Environmental Sustainability
• +۶ مورد دیگر

Magda Posani is an Assistant Professor in the Department of Civil Engineering at Aalto University, focusing on building physics, hygrothermal behavior of materials, and environmental sustainability. Her research explores the use of bio-based insulation, thermally massive stone and earth walls, and additive manufacturing techniques to enhance indoor comfort and address climate change challenges in Nordic regions. Integrated Master's Degree in 'Building Engineering and Architecture' from the University of Bologna (Italy) Ph.D. in Civil Engineering from the National Laboratory for Civil Engineering (LNEC) and the University of Porto (FEUP, Portugal) Postdoctoral Research at ETH Zürich (Switzerland) Her research integrates vernacular solutions with modern technology, such as combining additive manufacturing with super-hygroscopic materials to develop components for passive humidity regulation. She addresses critical issues like occupant comfort, health risks from improper humidity, and climate change impacts on traditional constructions. The articles highlight her work on low-carbon materials, 3D-printed building components, and strategies for enhancing hygrothermal performance in both modern and historic structures. Key themes include moisture buffering, thermal insulation compatibility, and climate-resilient renovation.

Damien Charrierasمشاهده پروفایل

دانشیار

• Cultural Studies
• Media Theory
• Digital Arts
• +۷ مورد دیگر

Dr. Damien Charrieras is an Associate Professor at the School of Creative Media , City University of Hong Kong, where he serves as Program Leader for the Master of Art in Creative Media and deputy program leader for the PhD in Creative Media. His work bridges cultural studies, new media theory, and the intersection of financial technologies with artistic practices through the ACIM Laboratory for Interventions in Speculative Finance . Doctoral research on digital artists' trajectories in Montreal FRQSC Postdoctoral Fellowship at McGill University Research spans game engine design , datafication of creativity , blockchain in art , and post-anthropocentric creative processes . With over HK$3.14M in grants as Principal Investigator, he explores situated digital creativity in urban contexts, critical worldbuilding pedagogy , and the mediation of technical systems in cultural production. His publications in Cities , Organized Sound , and Human Relations analyze the reconfiguration of artistic practices through software infrastructures and automation paradigms. Scientific awards include: FRQSC Postdoctoral Fellowship

M Rameshمشاهده پروفایل

استاد

• Public Policy
• Governance in Asia
• Health Policy
• +۳ مورد دیگر

M Ramesh is a Professor and UNESCO Chair on Social Policy Design in Asia at the Lee Kuan Yew School of Public Policy , National University of Singapore. He has held academic leadership roles as Founding Head of the Department of Asian and Policy at the Hong Kong Institute of Education, Professor of Social Policy at the University of Hong Kong, and Chair of the Department of Government and International Relations at the University of Sydney. Education : PhD (University of British Columbia, 1989), MA (University of Saskatchewan, 1983), BA (Patna University, 1979) Research Focus : Public policy processes, governance in Asia, health policy, social protection, and education policy Editorial Roles : Founder/Editor of Policy and Society , Policy Design and Practice , and Cambridge Elements in Public Policy Ramesh’s research explores policy and governance design in Asian contexts, particularly healthcare , social protection , and education policy . His work analyzes decentralization , governance failures , and policy capacity through comparative studies across China, India, Thailand, and Southeast Asia. He examines healthcare reforms , social security systems , and public-private dynamics in policy implementation. His recent publications highlight decentralization challenges in China, health policy tools in India, and innovative policy mixes in Singapore. Ramesh also investigates legitimation strategies and capacity deficits in modern governance. Courses Taught : Asian Pacific Politics, Comparative Public Policy, Economic and Social Policies in East Asia, Globalisation and Public Policy, Government and Business, International Political Economy, Public Policy: Introduction, Social Policy: Issues and Options, World Politics. Editorial Boards : American Review of Public Administration, Journal of Comparative Policy Analysis, Global Governance, Social Science and Medicine (2010–2015), and others.

Daniel Adelmanمشاهده پروفایل

استاد

• Business Analytics
• Management Analytics
• Operations Research
• +۵ مورد دیگر

Daniel Adelman is the Charles I. Clough, Jr. Professor of Operations Management at the University of Chicago Booth School of Business. He joined the faculty in 1997 after completing his PhD in industrial engineering and operations research at Georgia Tech. Adelman is a leading expert in Business Analytics and Management Analytics, helping companies deploy data and decision analysis to build world-class strategic and tactical management capabilities. Adelman received his PhD in industrial engineering and operations research in 1997, along with a bachelor's degree in industrial engineering and a master's degree in operations research, all from the School of Industrial and Systems Engineering at the Georgia Institute of Technology. Daniel Adelman's research focuses on applying analytical models to solve complex business problems across multiple industries. He has worked with firms from diverse sectors including internet services, chemical distribution, airlines, third party logistics, fiber-optics manufacturing, semiconductor manufacturing, oil, and healthcare. His research integrates real-world data with analytical models to bring structure and discipline to decision and control processes, enabling firms to achieve higher profits with lower risk. Adelman's recent work has concentrated heavily on healthcare analytics, where he leads the Healthcare Analytics Laboratory at Chicago Booth. This lab works with teams of doctoral and MBA students on projects with major healthcare institutions to optimize clinical, operational, and financial outcomes. His research spans foundational operations research including approximate dynamic programming, inventory theory/supply chain management, and revenue management/pricing optimization, as well as examining the linkage between operational performance metrics and financial performance of firms. Adelman's publications show a clear trend toward increasing focus on healthcare applications while maintaining strong theoretical foundations in operations research. His earlier work focused more on general operations management problems like inventory control and supply chain optimization, while his recent publications demonstrate a strategic shift toward healthcare analytics, particularly examining surgical team dynamics, hospital performance metrics, and resource allocation during public health emergencies like the COVID-19 pandemic. George B. Dantzig Prize (1998) for the best dissertation in operations research and management sciences that is innovative and relevant to practice Adelman regularly advises doctoral and MBA students through the Healthcare Analytics Laboratory at Chicago Booth. He has served as Associate Editor for Management Science, currently serves as Associate Editor for Manufacturing and Service Operations Management, and is the Area Editor for Operations and Supply Chain at Operations Research. His industry collaborations include significant projects with Akamai on internet pricing, with GE Global Research Labs on the electricity smart grid, with BP on gasoline supply contract portfolio optimization, and with Symantec on software release planning. Adelman leads the Healthcare Analytics Laboratory at Chicago Booth, which brings together interdisciplinary teams of doctoral and MBA students to work on a portfolio of projects with major healthcare institutions. The lab focuses on optimizing clinical, operational, and financial outcomes through advanced analytics and decision modeling.

Joy Arulrajمشاهده پروفایل

دانشیار

• Data Systems
• Machine Learning
• Database Systems
• +۲ مورد دیگر

Joy Arulraj is an Associate Professor in the School of Computer Science within the College of Computing at Georgia Institute of Technology. His research focuses on data systems, machine learning, and database systems, with a particular emphasis on video analytics and adaptive query processing. He leads the Data Systems and Analytics Group and is developing the EVA AI-Relational Data System. Dr. Arulraj's research interests span data systems, machine learning, database systems, video analytics, and adaptive query processing. His work centers on developing systems that efficiently process complex queries, particularly for video analytics and machine learning workloads. He has made significant contributions to GPU database systems, non-volatile memory database management, and adaptive query processing techniques. His research often bridges the gap between theoretical database principles and practical implementations for modern hardware architectures. His recent publications show a strong trend toward video analytics systems, adaptive query processing for machine learning workloads, and GPU-accelerated database systems. The EVA system represents a major focus of his recent work, providing end-to-end exploratory video analytics capabilities. His research also addresses fundamental database concepts like buffer management, query optimization, and storage management, adapting these principles for modern hardware and application requirements. Dr. Arulraj has advised numerous graduate students including Pramod Chunduri, Gaurav Tarkok Kakkar, Jiashen Cao, and Sayan Sinha. His graduated students have gone on to work at companies like ServiceNow, Meta Research, and the Korean Army. He actively teaches database system courses at Georgia Tech, including Database System Implementation (CS 4420/6422) and Advanced Database System Implementation (CS 4423/6423), where students build database systems from scratch using C++ and the BuzzDB framework. He maintains an active research program with consistent publication output across top database and systems conferences. His work spans from theoretical database principles to practical system implementations, with a recent emphasis on video analytics, machine learning integration with database systems, and leveraging modern hardware like GPUs and non-volatile memory for database applications.