Matteo Interlandi

101 papers A* 10A 6B 2C 2Journal 51Unranked 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ZipFlow: a Compiler-based Framework to Unleash Compressed Data Movement for Modern GPUs. CoRR Gwangoo Yeo, Zhiyang Shen, Wei Cui, Matteo Interlandi, Rathijit Sen, Bailu Ding, Qi Chen, Minsoo Rhu
2025	J	`jnl`	Data formats in analytical DBMSs: performance trade-offs and future directions. VLDB J. Chunwei Liu, Anna Pavlenko, Matteo Interlandi, Brandon Haynes
2025	B	`conf`	FairnessEval: a Framework for Evaluating Fairness of Machine Learning Models. EDBT Andrea Baraldi, Matteo Brucato, Miroslav Dudík, Francesco Guerra, Matteo Interlandi
2025	J	`jnl`	GPU Acceleration of SQL Analytics on Compressed Data. CoRR Zezhou Huang, Krystian Sakowski, Hans Lehnert, Wei Cui, Carlo Curino, Matteo Interlandi, Marius Dumitru, Rathijit Sen
2025	J	`jnl`	GPU Acceleration of SQL Analytics on Compressed Data. Proc. VLDB Endow. Zezhou Huang, Krystian Sakowski, Hans Lehnert, Wei Cui, Carlo Curino, Matteo Interlandi, Marius Dumitru, Rathijit Sen
2025	—	`conf`	Ninth Workshop on Data Management for End-to-End Machine Learning (DEEM). SIGMOD Conference Companion Stefan Grafberger, Madelon Hulsebos, Matteo Interlandi, Shreya Shankar
2025	J	`jnl`	Scaling GPU-Accelerated Databases beyond GPU Memory Size. Proc. VLDB Endow. Yinan Li, Bailu Ding, Ziyun Wei, Lukas M. Maas, Momin Al-Ghosien, Spyros Blanas, Nicolas Bruno, Carlo Curino, Matteo Interlandi, Craig Peeper, Kaushik Rajan, Surajit Chaudhuri, Johannes Gehrke
2025	J	`jnl`	Terabyte-Scale Analytics in the Blink of an Eye. CoRR Bowen Wu, Wei Cui, Carlo Curino, Matteo Interlandi, Rathijit Sen
2025	J	`jnl`	Terabyte-Scale Analytics in the Blink of an Eye. Proc. VLDB Endow. Bowen Wu, Wei Cui, Carlo Curino, Matteo Interlandi, Rathijit Sen
2024	A*	`conf`	Data Debugging with Shapley Importance over Machine Learning Pipelines. ICLR Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang
2024	J	`jnl`	Data Formats in Analytical DBMSs: Performance Trade-offs and Future Directions. CoRR Chunwei Liu, Anna Pavlenko, Matteo Interlandi, Brandon Haynes
2024	—	`conf`	Eighth Workshop on Data Management for End-to-End Machine Learning (DEEM). SIGMOD Conference Companion Madelon Hulsebos, Matteo Interlandi, Shreya Shankar
2024	A*	`conf`	Pushing ML Predictions into DBMSs (Extended Abstract). ICDE Matteo Paganelli, Paolo Sottovia, Kwanghyun Park, Matteo Interlandi, Francesco Guerra
2024	J	`jnl`	Towards Building Autonomous Data Services on Azure. CoRR Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan
2023	J	`jnl`	A Deep Dive into Common Open Formats for Analytical DBMSs. Proc. VLDB Endow. Chunwei Liu, Anna Pavlenko, Matteo Interlandi, Brandon Haynes
2023	J	`jnl`	GPU Database Systems Characterization and Optimization. Proc. VLDB Endow. Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim
2023	J	`jnl`	Optimizing Data Pipelines for Machine Learning in Feature Stores. Proc. VLDB Endow. Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez
2023	—	`conf`	Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques. SIGMOD Conference Companion Matthias Boehm, Matteo Interlandi, Chris Jermaine
2023	J	`jnl`	Pushing ML Predictions Into DBMSs. IEEE Trans. Knowl. Data Eng. Matteo Paganelli, Paolo Sottovia, Kwanghyun Park, Matteo Interlandi, Francesco Guerra
2023	C	`conf`	Query Processing on Gaming Consoles. DaMoN Wei Cui, Qianxi Zhang, Spyros Blanas, Jesús Camacho-Rodríguez, Brandon Haynes, Yinan Li, Ravi Ramamurthy, Peng Cheng, Rathijit Sen, Matteo Interlandi
2023	J	`jnl`	Revisiting Query Performance in GPU Database Systems. CoRR Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim
2023	A	`conf`	The Tensor Data Platform: Towards an AI-centric Database System. CIDR Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
2023	—	`conf`	Towards Building Autonomous Data Services on Azure. SIGMOD Conference Companion Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan
2023	A*	`conf`	Unshackling Database Benchmarking from Synthetic Workloads. ICDE Parimarjan Negi, Laurent Bindschaedler, Mohammad Alizadeh, Tim Kraska, Jyoti Leeka, Anja Gruenheid, Matteo Interlandi
2022	J	`jnl`	Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. CoRR Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang
2022	J	`jnl`	Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. SIGMOD Rec. Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, K. Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
2022	—	`conf`	Deploying a Steered Query Optimizer in Production at Microsoft. SIGMOD Conference Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc T. Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
2022	J	`jnl`	Deploying a Steered Query Optimizer in Production at Microsoft. CoRR Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc T. Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
2022	—	`conf`	End-to-end Optimization of Machine Learning Prediction Queries. SIGMOD Conference Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
2022	J	`jnl`	End-to-end Optimization of Machine Learning Prediction Queries. CoRR Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos
2022	J	`jnl`	Query Processing on Tensor Computation Runtimes. CoRR Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
2022	J	`jnl`	Query Processing on Tensor Computation Runtimes. Proc. VLDB Endow. Dong He, Supun Chathuranga Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi
2022	J	`jnl`	Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem. CoRR Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
2022	J	`jnl`	Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem. Proc. VLDB Endow. Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi
2022	J	`jnl`	The Tensor Data Platform: Towards an AI-centric Database System. CoRR Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi
2021	J	`jnl`	Machine Learning for Cloud Data Systems: the Promise, the Progress, and the Path Forward. Proc. VLDB Endow. Alekh Jindal, Matteo Interlandi
2021	J	`jnl`	Phoebe: A Learning-based Checkpoint Optimizer. CoRR Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal
2021	J	`jnl`	Phoebe: A Learning-based Checkpoint Optimizer. Proc. VLDB Endow. Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal
2021	J	`jnl`	SEIZE: Runtime Inspection for Parallel Dataflow Systems. IEEE Trans. Parallel Distributed Syst. Youfu Li, Matteo Interlandi, Fotis Psallidas, Wei Wang, Carlo Zaniolo
2021	—	`conf`	Steering Query Optimizers: A Practical Take on Big Data Workloads. SIGMOD Conference Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc T. Friedman, Alekh Jindal
2021	J	`jnl`	Tensors: An abstraction for general data processing. Proc. VLDB Endow. Dimitrios Koutsoukos, Supun Nakandala, Konstantinos Karanasos, Karla Saur, Gustavo Alonso, Matteo Interlandi
2021	—	`conf`	Transforming ML Predictive Pipelines into SQL with MASQ. SIGMOD Conference Francesco Del Buono, Matteo Paganelli, Paolo Sottovia, Matteo Interlandi, Francesco Guerra
2021	—	`conf`	Using Descriptions for Explaining Entity Matches (Discussion Paper). SEBD Matteo Paganelli, Paolo Sottovia, Antonio Maccioni, Matteo Interlandi, Francesco Guerra
2021	J	`jnl`	WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele. Proc. VLDB Endow. Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim, Artidoro Pagnoni, Ce Zhang, Byung-Gon Chun, Markus Weimer, Matteo Interlandi
2020	A*	`conf`	A Tensor Compiler for Unified Machine Learning Prediction Serving. OSDI Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
2020	J	`jnl`	A Tensor Compiler for Unified Machine Learning Prediction Serving. CoRR Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
2020	A*	`conf`	Building Continuous Integration Services for Machine Learning. KDD Bojan Karlas, Matteo Interlandi, Cédric Renggli, Wentao Wu, Ce Zhang, Deepak Mukunthu Iyappan Babu, Jordan Edwards, Chris Lauren, Andy Xu, Markus Weimer
2020	A	`conf`	Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML. CIDR Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu
2020	J	`jnl`	Explaining data with descriptions. Inf. Syst. Matteo Paganelli, Paolo Sottovia, Antonio Maccioni, Matteo Interlandi, Francesco Guerra
2020	A	`conf`	Extending Relational Query Processing with ML Inference. CIDR Konstantinos Karanasos, Matteo Interlandi, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Doris Xin, Supun Nakandala, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
2020	A	`conf`	SEIZE User Desired Moments: Runtime Inspection for Parallel Dataflow Systems. ICDCS Youfu Li, Matteo Interlandi, Fotis Psallidas, Wei Wang, Carlo Zaniolo
2019	—	`conf`	Acorn: Aggressive Result Caching in Distributed Data Processing Frameworks. SoCC Lana Ramjit, Matteo Interlandi, Eugene Wu, Ravi Netravali
2019	J	`jnl`	Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML. CoRR Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu
2019	B	`conf`	Coded Elastic Computing. ISIT Yaoqing Yang, Matteo Interlandi, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer
2019	J	`jnl`	Data Science through the looking glass and what we found there. CoRR Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Matteo Interlandi, Avrilia Floratou, Konstantinos Karanasos, Wentao Wu, Ce Zhang, Subru Krishnan, Carlo Curino, Markus Weimer
2019	J	`jnl`	Extending Relational Query Processing with ML Inference. CoRR Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandala, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino
2019	J	`jnl`	Machine Learning at Microsoft with ML .NET. CoRR Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Eric Erhardt, Costin Eseanu, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Shon Katzenberger, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Sarthak Shah, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu
2019	A*	`conf`	Machine Learning at Microsoft with ML.NET. KDD Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu
2019	J	`jnl`	Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach. CoRR Gyeong-In Yu, Saeed Amizadeh, Artidoro Pagnoni, Byung-Gon Chun, Markus Weimer, Matteo Interlandi
2019	A	`conf`	Understanding Data in the Blink of an Eye. CIKM Matteo Paganelli, Paolo Sottovia, Antonio Maccioni, Matteo Interlandi, Francesco Guerra
2018	J	`jnl`	A datalog-based computational model for coordination-free, data-parallel systems. Theory Pract. Log. Program. Matteo Interlandi, Letizia Tanca
2018	J	`jnl`	Adding data provenance support to Apache Spark. VLDB J. Matteo Interlandi, Ari Ekmekji, Kshitij Shah, Muhammad Ali Gulzar, Sai Deep Tetali, Miryung Kim, Todd D. Millstein, Tyson Condie
2018	J	`jnl`	Coded Elastic Computing. CoRR Yaoqing Yang, Matteo Interlandi, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer
2018	—	`conf`	Declarative Algorithms in Datalog with Extrema: Their Formal Semantics Simplified. ICLP (Technical Communications) Carlo Zaniolo, Mohan Yang, Matteo Interlandi, Ariyam Das, Alexander Shkapsky, Tyson Condie
2018	—	`conf`	Declarative BigData Algorithms via Aggregates and Relational Database Dependencies. AMW Carlo Zaniolo, Mohan Yang, Matteo Interlandi, Ariyam Das, Alexander Shkapsky, Tyson Condie
2018	J	`jnl`	From the Edge to the Cloud: Model Serving in ML.NET. IEEE Data Eng. Bull. Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Markus Weimer, Matteo Interlandi
2018	A*	`conf`	PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems. OSDI Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Markus Weimer, Matteo Interlandi
2018	J	`jnl`	PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems. CoRR Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Markus Weimer, Matteo Interlandi
2018	—	`conf`	RIOS: Runtime Integrated Optimizer for Spark. SoCC Youfu Li, Mingda Li, Ling Ding, Matteo Interlandi
2018	J	`jnl`	Scaling-Up Reasoning and Advanced Analytics on BigData. CoRR Tyson Condie, Ariyam Das, Matteo Interlandi, Alexander Shkapsky, Mohan Yang, Carlo Zaniolo
2018	J	`jnl`	Scaling-up reasoning and advanced analytics on BigData. Theory Pract. Log. Program. Tyson Condie, Ariyam Das, Matteo Interlandi, Alexander Shkapsky, Mohan Yang, Carlo Zaniolo
2018	J	`jnl`	Supporting Data Provenance in Data-Intensive Scalable Computing Systems. IEEE Data Eng. Bull. Matteo Interlandi, Tyson Condie
2017	J	`jnl`	Apache REEF: Retainable Evaluator Execution Framework. ACM Trans. Comput. Syst. Byung-Gon Chun, Tyson Condie, Yingda Chen, Brian Cho, Andrew Chung, Carlo Curino, Chris Douglas, Matteo Interlandi, Beomyeol Jeon, Joo Seong Jeong, Gyewon Lee, Yunseong Lee, Tony Majestro, Dahlia Malkhi, Sergiy Matusevych, Brandon Myers, Mariia Mykhailova, Shravan M. Narayanamurthy, Joseph Noor, Raghu Ramakrishnan, Sriram Rao, Russell Sears, Beysim Sezgin, Taegeon Um, Julia Wang, Markus Weimer, Youngseok Yang
2017	—	`conf`	Automated debugging in data-intensive scalable computing. SoCC Muhammad Ali Gulzar, Matteo Interlandi, Xueyuan Han, Mingda Li, Tyson Condie, Miryung Kim
2017	—	`conf`	Cleaning MapReduce Workflows. HPCS Matteo Interlandi, Julien Lacroix, Omar Boucelma, Francesco Guerra
2017	—	`conf`	Debugging Big Data Analytics in Spark with SIGMOD Conference Muhammad Ali Gulzar, Matteo Interlandi, Tyson Condie, Miryung Kim
2017	J	`jnl`	Fixpoint Semantics and Optimization of Recursive Datalog Programs with Aggregates. CoRR Carlo Zaniolo, Mohan Yang, Matteo Interlandi, Ariyam Das, Alexander Shkapsky, Tyson Condie
2017	J	`jnl`	Fixpoint semantics and optimization of recursive Datalog programs with aggregates. Theory Pract. Log. Program. Carlo Zaniolo, Mohan Yang, Ariyam Das, Alexander Shkapsky, Tyson Condie, Matteo Interlandi
2017	C	`conf`	Towards Accelerating Generic Machine Learning Prediction Pipelines. ICCD Alberto Scolari, Yunseong Lee, Markus Weimer, Matteo Interlandi
2016	—	`conf`	Big Data Analytics with Datalog Queries on Spark. SIGMOD Conference Alexander Shkapsky, Mohan Yang, Matteo Interlandi, Hsuan Chiu, Tyson Condie, Carlo Zaniolo
2016	A*	`conf`	BigDebug: debugging primitives for interactive big data processing in spark. ICSE Muhammad Ali Gulzar, Matteo Interlandi, Seunghyun Yoo, Sai Deep Tetali, Tyson Condie, Todd D. Millstein, Miryung Kim
2016	—	`conf`	BigDebug: interactive debugger for big data analytics in Apache Spark. SIGSOFT FSE Muhammad Ali Gulzar, Matteo Interlandi, Tyson Condie, Miryung Kim
2016	J	`jnl`	Combining user and database perspective for solving keyword queries over relational databases. Inf. Syst. Sonia Bergamaschi, Francesco Guerra, Matteo Interlandi, Raquel Trillo Lado, Yannis Velegrakis
2016	—	`conf`	Interactive Debugging for Big Data Analytics. HotCloud Muhammad Ali Gulzar, Xueyuan Han, Matteo Interlandi, Shaghayegh Mardani, Sai Deep Tetali, Todd D. Millstein, Miryung Kim
2016	—	`conf`	Optimizing Interactive Development of Data-Intensive Applications. SoCC Matteo Interlandi, Sai Deep Tetali, Muhammad Ali Gulzar, Joseph Noor, Tyson Condie, Miryung Kim, Todd D. Millstein
2016	—	`conf`	Programming and Runtime Support to Blaze FPGA Accelerator Deployment at Datacenter Scale. SoCC Muhuan Huang, Di Wu, Cody Hao Yu, Zhenman Fang, Matteo Interlandi, Tyson Condie, Jason Cong
2016	—	`conf`	The Magic of Pushing Extrema into Recursion: Simple, Powerful Datalog Programs. AMW Carlo Zaniolo, Mohan Yang, Ariyam Das, Matteo Interlandi
2015	—	`conf`	On the CALM Principle for BSP Computation. AMW Matteo Interlandi, Letizia Tanca
2015	A*	`conf`	Proof positive and negative in data cleaning. ICDE Matteo Interlandi, Nan Tang
2015	J	`jnl`	Titian: Data Provenance Support in Spark. Proc. VLDB Endow. Matteo Interlandi, Kshitij Shah, Sai Deep Tetali, Muhammad Ali Gulzar, Seunghyun Yoo, Miryung Kim, Todd D. Millstein, Tyson Condie
2014	J	`jnl`	On the CALM Principle for Bulk Synchronous Parallel Computation. CoRR Matteo Interlandi, Letizia Tanca
2014	—	`conf`	Towards Declarative Imperative Data-parallel Systems. SEBD Matteo Interlandi, Giovanni Simonini, Sonia Bergamaschi
2013	—	`conf`	Datalog in Time and Space, Synchronously. AMW Matteo Interlandi, Letizia Tanca, Sonia Bergamaschi
2013	J	`jnl`	QUEST: A Keyword Search System for Relational Data based on Semantic and Machine Learning Techniques. Proc. VLDB Endow. Sonia Bergamaschi, Francesco Guerra, Matteo Interlandi, Raquel Trillo Lado, Yannis Velegrakis
2013	—	`conf`	Using a HMM based approach for mapping keyword queries into database terms. SEBD Sonia Bergamaschi, Francesco Guerra, Matteo Interlandi, Silvia Rota, Raquel Trillo, Yannis Velegrakis
2012	A*	`conf`	A Meta-language for MDX Queries in eLog Business Solution. ICDE Sonia Bergamaschi, Matteo Interlandi, Mario Longo, Laura Po, Maurizio Vincini
2012	—	`conf`	Enhancing Datalog with Epistemic Operators to Reason About Knowledge in Distributed Systems. SEBD Matteo Interlandi
2012	A	`conf`	Knowlog: A Declarative Language for Reasoning about Knowledge in Distributed Systems. ER Matteo Interlandi
2012	—	`conf`	Reasoning about Knowledge in Distributed Systems Using Datalog. Datalog Matteo Interlandi
2011	—	`conf`	MediaPresenter, a Web Platform for Multimedia Content Management. SEBD Sonia Bergamaschi, Fabio Ferrari, Matteo Interlandi, Maurizio Vincini
2010	—	`conf`	Automatic Fault Behavior Detection and Modeling by a State-Based Specification Method. HASE Luca Pazzi, Matteo Interlandi, Marco Pradelli