99 stories
Brett Mullins, Ryan McKenna, and Gerome Miklau’s paper “Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data” is accepted to AISTATS 2024. Authors: Miguel Fuentes, Brett Mullins, Ryan McKenna, Gerome Miklau, Daniel Sheldon
Read story →The following DREAM Lab papers were accepted to the 2023 Winter Simulation Conference: Cen Wang and Peter Haas “Efficient Hybrid Simulation Optimization Via Graph Neural Network Metamodeling” Pracheta Amaranath, Peter Haas, David Jensen, and Sam Witty “Causal Dynamic Bayesian Networks for Simulation Metamodeling”
Read story →Aman Malali, Chenghao Lyu, and Peter Haas presented their work at the BigFastData Workshop. Aman Malali presented “Predictive ML model maintenance”. Peter Haas presented “In-Database Decision Support: Opportunities and Challenges”. Chenghao Lyu presented “An Adaptive, Multi-Resolution, and Multi-Objective Parameter Tuning Approach for Spark SQL”.
Read story →Brett Mullins, Gerome Miklau, and Dan Sheldon’s paper “Quantifying Uncertainty of Unsupported Linear Queries for Private Query Release” is accepted to TPDP 2023.
Read story →Juelin Liu, Sandeep Polisetty, and Marco Serafini’s paper “Minigraph: Accelerating Subgraph Enumeration Using Auxiliary Graphs” is accepted to PACT 2023. Authors: Juelin Liu, Sandeep Polisetty, Hui Guan, Marco Serafini
Read story →Cen Wang and Peter Haas‘ paper “NIM: Generative Neural Networks for Automated Modeling and Generation of Simulation Inputs” was published in the ACM Transactions on Modeling and Computer Simulation.
Read story →Anna Fariha (PhD 2022) is an incoming Assistant Professor at the University of Utah. She was previously a researcher at Microsoft. Anna completed her dissertation under Alexandra Meliou.
Read story →Cen Wang received the 2021-2022 Outstanding Synthesis Project Award from the Manning College of Information and Computer Science. This project is summarized in NIM: Modeling and Generation of Simulation Inputs via Generative Neural Networks from the 2020 Winter Simulation Conference.
Read story →Ryan McKenna received the 2021-2022 Outstanding Dissertation Award from the Manning College of Information and Computer Science for his thesis “Practical Methods for High-Dimensional Data Publication with Differential Privacy“.
Read story →Brett Mullins’ paper “The Shape of Explanations: A Topological Account of Rule-Based Explanations in Machine Learning” is accepted at R2HCAI Workshop at AAAI 2023.
Read story →Gerome Miklau is recognized as 2022 ACM Distinguished Member
Read story →Together with S. Sudarshan, Alexandra Meliou will be program committee chair for SIGMOD 2024.
Read story →Marco Serafini was awarded a grant from the National Science Foundation for the project “Transparently Scaling Graph Neural Network Training to Large-Scale Models and Graphs”. Summary: Large-scale graphs with billions of edges are ubiquitous in many industry, science, and engineering fields such as recommendation systems, social graph analysis, knowledge bases, materials science, and biology. In […]
Read story →Peter Haas and Alexandra Meliou were awarded a $600K grant from the National Science Foundation for the project “Scalable In-Database Prescriptive Analytics for Dynamic Environments”. Summary: The project aims to augment prior work on in-database support for constrained optimization problems with capabilities to handle dynamic environments. Specifically, the project will extend prior methods to handle […]
Read story →Ryan McKenna, Brett Mullins, and Gerome Miklau’s paper “AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data” is accepted to VLDB 2022. Authors: Ryan McKenna, Brett Mullins, Dan Sheldon, Gerome Miklau
Read story →Chenghao Lyu and Yanlei Diao’s paper “Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing” is accepted to VLDB 2022. Authors: Chenghao Lyu, Qi Fan, Fei Song, Arnab Sinha, Yanlei Diao, Wei Chen, Li Ma, Yihui Feng, Yaliang Li, Kai Zeng, and Jingren Zhou
Read story →Ryan McKenna and Gerome Miklau’s paper “Relaxed Marginal Consistency for Differentially Private Query Answering” was accepted to NeurIPS 2021. Authors: Ryan McKenna, Siddhant Pradhan, Daniel Sheldon, Gerome Miklau
Read story →Maliha Tashfia Islam, Anna Fariha, and Alexandra Meliou’s paper “Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification” was accepted to SIGMOD 2022. Authors: Maliha Tashfia Islam, Anna Fariha, Alexandra Meliou, Babak Salimi
Read story →Alexandra Meliou and Zafeiria Moumoulidou’s paper “Improved Approximation and Scalability for Fair Max-Min Diversification” was accepted to ICDT 2022. Authors: Raghavendra Addanki, Andrew McGregor, Alexandra Meliou, Zafeiria Moumoulidou
Read story →Anna Fariha‘s demo paper “DICE: Data Discovery by Example” was accepted to VLDB 2021. Authors: El Kindi Rezig, Anshul Bhandari, Anna Fariha, Benjamin Price, Allan Vanterpool, Vijay Gadepally, Michael Stonebraker
Read story →Sandeep Polisetty‘s paper “NextDoor: Accelerating Graph Sampling for Graph Machine Learning using GPUs” was accepted to Eurosys 2021. Authors: Abhinav Jangda, Sandeep Polisetty, Arjun Guha, Marco Serafini
Read story →Matteo Brucato‘s paper “Solving Markov Decision Processes with Partial State Abstractions” was accepted to ICRA 2021. Authors: Samer B. Nashed, Justin Svegliato, Matteo Brucato, Connor Basich, Roderic Grupen, Shlomo Zilberstein
Read story →Anna Fariha‘s paper “CoCo: Interactive Exploration of Conformance Constraints for Data Understanding and Data Cleaning” was accepted to SIGMOD 2021. Authors: Anna Fariha, Ashish Tiwari, Alexandra Meliou, Arjun Radhakrishna, Sumit Gulwani
Read story →Ryan McKenna, Joie Wu, Arisa Tajima, Brett Mullins, Siddhant Pradhan, and Cecilia Ferrando have recently won the first prize in the National Institute of Standards and Technology (NIST) Differential Privacy Temporal Map Challenge. The challenge seeks new tools with which to push the boundaries of current technologies for de-identifying data sets relevant to public safety.
Read story →Cen Wang‘s paper “NIM: Modeling and Generation of Simulation Inputs via Generative Neural Networks” won Best Contributed Theoretical Paper Honorable Mention at WSC 2020! Authors: Cen Wang, Emily Herbert, Peter J. Haas
Read story →Anna Fariha’s paper “Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems” was accepted to SIGMOD 2021. Authors: Anna Fariha, Ashish Tiwari, Arjun Radhakrishna, Sumit Gulwani, Alexandra Meliou
Read story →Ryan McKenna’s paper “Permute-and-Flip: A new mechanism for differentially private selection” was accepted to NeurIPS 2020. Authors: Ryan McKenna, Daniel Sheldon
Read story →Zafeiria Moumoulidou‘s paper “Diverse Data Selection under Fairness Constraints” was accepted to ICDT 2021. Authors: Zafeiria Moumoulidou, Andrew McGregor, Alexandra Meliou.
Read story →Chenghao Lyu’s paper “Boosting Cloud Data Analytics using Multi-Objective Optimization” was accepted to ICDE 2021. Authors: Fei Song, Khaled Zaouk, Chenghao Lyu, Arnab Sinha, Qi Fan, Yanlei Diao, Prashant Shenoy.
Read story →Dan Zhang‘s paper “Investigating Visual Analysis of Differentially Private Data New” was accepted to IEEE VIS 2020 InfoVis. Authors: Dan Zhang, Ali Sarvghad, Gerome Miklau
Read story →Two papers from DREAM Lab won the Best Demonstration and Best Demonstration Runner-up awards at VLDB 2020. Matteo Brucato, Miro Mannino, Azza Abouzied, Peter J. Haas, Alexandra Meliou won the 2020 VLDB Best Demonstration award for their work on “sPaQLTooLs: A Stochastic Package Query Interface for Scalable Constrained Optimization“. Anna Fariha, Matteo Brucato, Peter J. […]
Read story →Dan Zhang’s paper “Sato: Contextual Semantic Type Detection in Tables” was accepted to VLDB 2020. Authors: Dan Zhang, Yoshihiko Suhara, Jinfeng Li, Madelon Hulsebos, Çagatay Demiralp, Wang-Chiew Tan
Read story →Cen Wang‘s paper “NIM: Modeling and Generation of Simulation Inputs via Generative Neural Networks” was accepted to Winter Simulation Conference (WSC) 2020 Authors: Cen Wang, Emily Herbert, Peter J. Haas
Read story →Alexandra Meliou wins ACM SIGSOFT Distinguished Artifact Award at ICSE 2020. Causal Testing: Understanding Defects’ Root Causes. Authors: Brittany Johnson, Yuriy Brun, Alexandra Meliou.
Read story →LiveGraph: A Transactional Graph Storage System with Purely Sequential Adjacency List Scans Authors: Xiaowei Zhu, Guanyu Feng, Marco Serafini, Xiaosong Ma, Jiping Yu, Lei Xie, Ashraf Aboulnaga, Wenguang Chen. Do the Best Cloud Configurations Grow on Trees? An Experimental Evaluation of Black Box Algorithms for Optimizing Cloud Workloads Authors: Muhammad Bilal, Marco Serafini, Marco Canini, […]
Read story →Ryan McKenna‘s paper “A workload-adaptive mechanism for linear queries under local differential privacy” was accepted to VLDB 2020. Authors: Ryan McKenna, Raj Kumar Maity, Arya Mazumdar, Gerome Miklau.
Read story →College of Information and Computer Sciences (CICS) doctoral candidate Anna Fariha has recently been awarded a 2020 Microsoft Research Dissertation Grant for her proposal, “Enhancing Usability and Explainability of Data Systems.” Fariha’s work focuses on reducing the usability gap between non-expert users and complex data systems. Her thesis aims to enable data-driven systems to become […]
Read story →sPaQLTooLs: A Stochastic Package Query Interface for Scalable Constrained Optimization. Authors: Matteo Brucato, Miro Mannino, Azza Abouzied, Peter J. Haas, Alexandra Meliou. SuDocu: Summarizing Documents by Example. Authors: Anna Fariha, Matteo Brucato, Peter J. Haas, Alexandra Meliou.
Read story →Marco Serafini‘s paper “PushdownDB: Accelerating a DBMS Using S3 Computation” was accepted to ICDE 2020. Authors: Xiangyao Yu, Matt Youill, Matthew E Woicik, Abdurrahman Ghanem, Marco Serafini, Ashraf Aboulnaga, Michael Stonebraker.
Read story →Dan Zhang‘s paper “ϵKTELO: A Framework for Defining Differentially Private Computations” was accepted to ACM TODS. Authors: Dan Zhang, Ryan McKenna, Ios Kotsogiannis, George Bissias, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau.
Read story →Anna Fariha’s paper “Causality-Guided Adaptive Interventional Debugging” was accepted to SIGMOD 2020. Authors: Anna Fariha, Suman Nath, Alexandra Meliou
Read story →Gerome Miklau’s PODS paper from 2010 will be awarded the test-of-time award at PODS 2020. This work was done by lab alumni Chao Li, Michael Hay, along with Andrew McGregor. “Optimizing Linear Counting Queries under Differential Privacy” Authors: Chao Li, Michael Hay, Vibhor Rastogi, Gerome Miklau, and Andrew McGregor
Read story →Anna Fariha’s demonstration paper “ExTuNe: Explaining Tuple Non-conformance” was accepted to SIGMOD 2020. Anna Fariha, Ashish Tiwari, Arjun Radhakrishna, Sumit Gulwani
Read story →Stochastic Package Queries in Probabilistic Databases. Authors: Matteo Brucato, Azza Abouzied, Peter J. Haas, Alexandra Meliou.
Read story →Peter J. Haas is a co-PI of a National Science Foundation Grant entitled “Simulation and Decision-Analysis Algorithms for Integrated Modeling of Diseases: A healthy lives for all approach”
Read story →Alexandra Meliou’s paper “The Complexity of Resilience for Binary Conjunctive Queries with Self Joins” was accepted to Symposium on Principles of Database Systems (PODS), 2020. Authors: Cibele Freire, Wolfgang Gatterbauer, Neil Immerman, Alexandra Meliou
Read story →Peter J. Haas and Alexandra Meliou have received a grant from the National Science Foundation to study In-Database Prescriptive Analytics under Uncertainty.
Read story →Ryan McKenna has recently won the National Institute of Standards and Technology’s (NIST) Differential Privacy Synthetic Data Challenge Match #3. The competition tests participants’ ability to identify and develop practical methods for creating differentially private synthetic data sets. The challenges include empirical evaluation of synthetic data generation on common tasks such as clustering, classification, and […]
Read story →Two papers from DREAM Lab have been recognized as 2018 ACM SIGMOD Research Highlights. Dan Zhang, Ryan McKenna, Ios Kotsogiannis, George Bissias, Michael Hay, Ashwin Machanavajjhala, and Gerome Miklau were recognized with a 2018 SIGMOD Research Highlight Award for their work on “Ektelo: A Framework for Defining Differentially-Private Computations“. Brian Hentschel, Peter J. Haas, and […]
Read story →Spade: A Modular Framework for Analytical Exploration of RDF Graphs Yanlei Diao, Paweł Guzewicz, Ioana Manolescu, Mirjana Mazuran. UDAO: A Next-Generation Unified Data Analytics Optimizer Khaled Zaouk, Fei Song, Chenghao Lyu, Arnab Sinha, Yanlei Diao, Prashant Shenoy. PSynDB: Accurate and Accessible Private Data Generation Zhiqi Huang, Ryan McKenna, George Bissias, Gerome Miklau, Michael Hay, Ashwin […]
Read story →Anna Fariha’s paper “Example-Driven Query Intent Discovery: Abductive Reasoning using Semantic Similarity” was accepted to VLDB 2019. Authors: Anna Fariha, Alexandra Meliou
Read story →Choosing A Cloud DBMS: Architectures and Tradeoffs. Authors: Junjay Tan, Matthew Perron, Xiangyao Yu, Thanaa Ghanem, Michael Stonebraker, David DeWitt, Marco Serafini, Ashraf Aboulnaga, Tim Kraska. The paper was featured by the morning paper, a popular research blog.
Read story →Ryan McKenna’s paper “Graphical-model based estimation and inference for differential privacy” was accepted to ICML 2019. Authors: Ryan McKenna, Daniel Sheldon,Gerome Miklau
Read story →Laura Haas has been given the 2019 IEEE Computer Society Pioneer Award “for significant contributions to early concepts and developments in the electronic computer field that have clearly advanced the state of the art in computing. [Details]
Read story →Ryan McKenna has recently won fourth place and a $3,000 prize in the National Institute of Standards and Technology’s (NIST) second match in the Differential Privacy Synthetic Data Challenge. The competition tests participants’ ability to identify and develop practical methods for creating differentially private synthetic data sets. The challenges include empirical evaluation of synthetic data […]
Read story →Xiaolan Wang got two papers accepted on her dissertation work. MIDAS: Finding the Right Web Sources to Fill Knowledge Gaps (ICDE 2019) Xiaolan Wang, Luna Dong, Alexandra Meliou, Yang Li Explain3D: Explaining Disagreements in Disjoint Datasets (PVLDB 2019) Xiaolan Wang, Alexandra Meliou
Read story →The National Institute of Standards and Technology’s (NIST) Public Safety Communications Research (PSCR) Division is proud to announce the winners of the first of three matches in the Differential Privacy Synthetic Data Challenge. This initiative is the first of its kind in differential privacy and offers a unique opportunity to benchmark implemented systems against each […]
Read story →Alexandra Meliou and Yuriy Brun have received a grant from the National Science Foundation to study how software systems can exhibit bias and how software engineers can develop fairer, more equitable systems. Read More
Read story →Alexandra Meliou was recognized as SIGMOD 2018 distinguished PC member and VLDB 2018 distinguished reviewer.
Read story →Liping Peng’s paper “Optimization for Active Learning-based Interactive Database Exploration” was accepted to VLDB 2019. Authors: Enhui Huang, Liping Peng, Luciano Di Palma, Ahmed Abdelkafi, Anna Liu, Yanlei Diao.
Read story →Ryan McKenna’s paper “Optimizing error of high-dimensional statistical queries under differential privacy” was accepted to VLDB 2018. Xiaolan Wang’s paper “Scalable Semantic Querying of Text” was accepted to VLDB 2018. Authors: Xiaolan Wang, Aaron Feng, Behzad Golshan, Alon Halevy, George Mihaila, Hidekazu Oiwa, Wang-Chiew Tan.
Read story →Xiaolan Wang’s paper “Explaining Data Integration” was accepted to IEEE Data Engineering Bulletin 2018. Authors: Xiaolan Wang, Laura Haas, Alexandra Meliou.
Read story →Peter Haas‘s paper “Temporally-Biased Sampling for Online Model Management” has been selected as the best paper of EDBT 2018!
Read story →Dan Zhang’s paper on differentially-private computations was accepted to SIGMOD 2018. “Ektelo: A Framework for Defining Differentially-Private Computations” Dan Zhang, Ryan McKenna, Ios Kotsogiannis, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala. The paper will be invited to the “Best of SIGMOD 2018” volume of the TODS journal
Read story →Alexandra Meliou will be co-chairing the PhD Symposium at ICDE 2018.
Read story →Peter Haas will be giving an invited talk on approximate query processing at EDBT 2018.
Read story →Peter Haas‘s paper will be presented at EDBT 2018. “Temporally-Biased Sampling for Online Model Management” Brian Hentschel, Peter J. Haas, Yuanyuan Tian
Read story →Peter Haas wins the IBM Research Pat Goldberg Memorial Best Paper Award for his VLDB 2016 paper. “Compressed Linear Algebra for Large-Scale Machine Learning” Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, and Berthold Reinwald
Read story →“SQuID: Semantic Similarity-Aware Query Intent Discovery” Anna Fariha, Sheikh Muhammad Sarwar, Alexandra Meliou “IoT-Dectective: Analyzing IoT Data Under Differential Privacy” Sameera Ghayyur, Ashwin Machanavajjhala, Yan Chen, Michael Hay, Sharad Mehrotra, Roberto Yus, Gerome Miklau “A Nutritional Label for Rankings” Ke Yang, Bill Howe, Julia Stoyanovich, HV Jagadish, Abolfazl Asudeh, Gerome Miklau Congratulations to all […]
Read story →Yue Wang‘s paper on supporting query result diversification was accepted to PVLDB 2018. “RC-Index: Diversifying Answers to Range Queries” Yue Wang, Alexandra Meliou, Gerome Miklau
Read story →Our group attends NEDB 2018.
Read story →Two papers from our DBLab have been nominated and selected for publication in the “Research Highlights” section of the CACM! “Scalable Package Queries in Relational Database Systems” Matteo Brucato, Juan Felipe Beltran, Azza Abouzied, and Alexandra Meliou “Compressed Linear Algebra for Large-Scale Machine Learning” Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, and […]
Read story →CACM Research Highlight published: A Theory Of Pricing Private Data By Chao Li, Daniel Yang Li, Gerome Miklau, Dan Suciu Communications of the ACM, Vol. 60 No. 12, Pages 79-86
Read story →Alexandra Meliou attends the Dagstuhl seminar on “Connecting Visualization and Data Management Research”.
Read story →Matteo Brucato’s paper “Package queries: efficient and scalable computation of high-order constraints” was accepted to the VLDB Journal, special issue on the Best Papers of VLDB 2016. The paper will appear in volume 27 of the VLDB Journal.
Read story →Laura Haas and Peter Haas have joined the DBLab.
Read story →Yue Wang has graduated and is joining MSR.
Read story →Sainyam Galhotra, Alexandra Meliou, and Yuriy Brun‘s work on Fairness Testing has been recognized with the ACM SIGSOFT Distinguished Paper Award.
Read story →Matteo Brucato’s paper at VLDB 2016, “Scalable Package Queries in Relational Database Systems”, was selected for a SIGMOD Research Highlight Award! The highlight will appear on the March 2017 issue of the SIGMOD record. Package Builder Website.
Read story →Professor Jonathan Ullman from Northeastern University will be giving a talk: Dusting for Fingerprints in Private Data.
Read story →Matteo Brucato’s paper at VLDB 2016, “Scalable Package Queries in Relational Database Systems”, was recognized as one of the best papers of the conference, and was invited for an extended version submission to a special “best-of-VLDB-2016” issue at VLDBJ. Package Builder Website.
Read story →Professor Arnab Nandi from the Ohio State University will be giving a talk: Querying Without Keyboards: Challenges in Gesture-driven Data Exploration.
Read story →Professor Tim Kraska from Brown University will be giving a talk: Interactive Data Science.
Read story →Professor Danielle Citron is the Lois K. Macht Research Professor & Professor of Law at the University of Maryland Francis King Carey School of Law. She will be giving a talk: Hate Crimes in Cyberspace.
Read story →Dr. Ce Zhang from Stanford will be giving a talk: DeepDive: A Data Management System for Machine Learning Workloads.
Read story →Xiangyao Yu from MIT will be giving a talk: Time-Traveling Cache Coherence and Concurrency Control.
Read story →Prof. Samuel Madden from MIT will be giving a talk: Interactive Data Analytics: the New Frontier on Jan. 20th. Abstract Data analytics often involves data exploration, where a data set is repeatedly analyzed to understand root causes, find patterns, or extract insights. Such analysis is frequently bottlenecked by the underlying data processing system, as analysts […]
Read story →Prof. Kobbi Nissim from Ben-Gurion University & Harvard University will be giving a talk: Privacy: from Theory to Reality at 4:00pm on Dec. 8th, in Room 150. Abstract The treatment of privacy in data analysis has taken a dramatic shift a little more than a decade ago – as failures of traditional privacy preserving techniques […]
Read story →Prof. Ninghui Li from Purdue University will be giving a talk: Differential Privacy: What Does It Mean and What Can Be Achieved? at 12:30pm on Dec. 7th, in Room 150 & Room 151. Abstract Over the last decade, differential privacy (DP) has emerged as the standard privacy notion for research in privacy-preserving data analysis and […]
Read story →The U.S. Defense Advanced Research Projects Agency (DARPA) this week named University of Massachusetts Amherst professor of computer science Gerome Miklau to lead a 4.5-year, $2.8 million grant to develop tools and techniques that enable the agency to build data management systems in which “private data may be used only for its intended purpose and […]
Read story →Prof. Remco Chang from Tufts University will be giving a talk: Big Data Visual Analytics: A User-Centric Approach at 12:30pm on Oct. 19th, in Room 150. Abstract Modern visualization systems often assume that the data can fit within the computer’s memory. With such an assumption, visualizations can quickly slice and dice the data and help […]
Read story →Dr. Laura Haas from IBM Research Lab will be giving a talk: Accelerating the Discovery of Insights from Data from 1 – 2pm on Oct. 8th, in Room 150/151. Abstract Today, businesses and scientists alike struggle to get to the value in their data. Their challenges include finding and gaining access to the data they need, “wrangling” […]
Read story →Prof. Alexandra Meliou is a PC track Chair for SIGMOD 2016.
Read story →Prof. Michael Hay is visiting for the 2015-2016 academic year.
Read story →Prof. Gerome Miklau will be a fellow of the UMass Interdisciplinary Studies Institute for 2015-2016.
Read story →Prof. Alexandra Meliou received an NSF CAREER award for her work on Reverse Data Management! This project will establish the theoretical foundations and will address practical challenges to support reverse data management capabilities in database systems.
Read story →GESALL, the project on genomic data processing, obtained new NSF funding, joint with the New York Genome Center; a new publication at CIDR 2015; and a new research video, joint with the Harvard Medical School and Boston Children’s Hospital.
Read story →Prof. Alexandra Meliou is a Student Travel Award selection committee co-Chair for SIGMOD 2015.
Read story →Prof. Alexandra Meliou is a New Researcher Symposium co-Chair for SIGMOD 2015.
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