Jialin Ding - RankMe

29 papers A 1Misc 1Journal 19Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	Misc	`conf`	Enhancing In-Memory Spatial Indexing with Learned Search. BTW Varun Pandey, Alexander van Renen, Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Volker Markl, Alfons Kemper
2025	J	`jnl`	KramaBench: A Benchmark for AI Systems on Data-to-Insight Pipelines over Data Lakes. CoRR Eugenie Lai, Gerardo Vitagliano, Ziyu Zhang, Sivaprasad Sudhir, Om Chabra, Anna Zeng, Anton A. Zabreyko, Chenning Li, Ferdi Kossmann, Jialin Ding, Jun Chen, Markos Markakis, Matthew Russo, Weiyang Wang, Ziniu Wu, Michael J. Cafarella, Lei Cao, Samuel Madden, Tim Kraska
2025	J	`jnl`	ODIN: A NL2SQL Recommender to Handle Schema Ambiguity. CoRR Kapil Vaidya, Abishek Sankararaman, Jialin Ding, Chuan Lei, Xiao Qin, Balakrishnan Narayanaswamy, Tim Kraska
2025	J	`jnl`	Parachute: Single-Pass Bi-Directional Information Passing. CoRR Mihail Stoian, Andreas Zimmerer, Skander Krid, Amadou Latyr Ngom, Jialin Ding, Tim Kraska, Andreas Kipf
2025	J	`jnl`	Parachute: Single-Pass Bi-Directional Information Passing. Proc. VLDB Endow. Mihail Stoian, Andreas Zimmerer, Skander Krid, Amadou Ngom, Jialin Ding, Tim Kraska, Andreas Kipf
2025	J	`jnl`	TailorSQL: An NL2SQL System Tailored to Your Query Workload. CoRR Kapil Vaidya, Jialin Ding, Sebastian Kosak, David Kernert, Chuan Lei, Xiao Qin, Abhinav Tripathy, Ramesh Balan, Balakrishnan Narayanaswamy, Tim Kraska
2025	—	`conf`	Utilizing Past User Feedback for More Accurate Text-to-SQL. HILDA@SIGMOD Matthias Urban, Jialin Ding, David Kernert, Kapil Vaidya, Tim Kraska
2024	—	`conf`	Automated Multidimensional Data Layouts in Amazon Redshift. SIGMOD Conference Companion Jialin Ding, Matt Abrams, Sanghita Bandyopadhyay, Luciano Di Palma, Yanzhu Ji, Davide Pagano, Gopal Paliwal, Panos Parchas, Pascal Pfeil, Orestis Polychroniou, Gaurav Saxena, Aamer Shah, Amina Voloder, Sherry Xiao, Davis Zhang, Tim Kraska
2024	—	`conf`	Learning Bit Allocations for Z-Order Layouts in Analytic Data Systems. aiDM@SIGMOD Jenny Gao, Jialin Ding, Sivaprasad Sudhir, Samuel Madden
2023	J	`jnl`	Enhancing In-Memory Spatial Indexing with Learned Search. CoRR Varun Pandey, Alexander van Renen, Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Volker Markl, Alfons Kemper
2022	—	`—`	Instance-Optimized Database Indexes and Storage Layouts Jialin Ding
2022	J	`jnl`	SageDB: An Instance-Optimized Data Analytics System. Proc. VLDB Endow. Jialin Ding, Ryan Marcus, Andreas Kipf, Vikram Nathan, Aniruddha Nrusimha, Kapil Vaidya, Alexander van Renen, Tim Kraska
2022	A	`conf`	Self-Organizing Data Containers. CIDR Samuel Madden, Jialin Ding, Tim Kraska, Sivaprasad Sudhir, David E. Cohen, Timothy G. Mattson, Nesime Tatbul
2021	J	`jnl`	APEX: A High-Performance Learned Index on Persistent Memory. CoRR Baotong Lu, Jialin Ding, Eric Lo, Umar Farooq Minhas, Tianzheng Wang
2021	J	`jnl`	APEX: A High-Performance Learned Index on Persistent Memory. Proc. VLDB Endow. Baotong Lu, Jialin Ding, Eric Lo, Umar Farooq Minhas, Tianzheng Wang
2021	—	`conf`	Instance-Optimized Data Layouts for Cloud Analytics Workloads. SIGMOD Conference Jialin Ding, Umar Farooq Minhas, Badrish Chandramouli, Chi Wang, Yinan Li, Ying Li, Donald Kossmann, Johannes Gehrke, Tim Kraska
2020	—	`conf`	ALEX: An Updatable Adaptive Learned Index. SIGMOD Conference Jialin Ding, Umar Farooq Minhas, Jia Yu, Chi Wang, Jaeyoung Do, Yinan Li, Hantian Zhang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David B. Lomet, Tim Kraska
2020	J	`jnl`	Cortex: Harnessing Correlations to Boost Query Performance. CoRR Vikram Nathan, Jialin Ding, Tim Kraska, Mohammad Alizadeh
2020	—	`conf`	Learning Multi-Dimensional Indexes. SIGMOD Conference Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska
2020	—	`conf`	The Case for Learned Spatial Indexes. AIDB@VLDB Varun Pandey, Alexander van Renen, Andreas Kipf, Jialin Ding, Ibrahim Sabek, Alfons Kemper
2020	J	`jnl`	The Case for Learned Spatial Indexes. CoRR Varun Pandey, Alexander van Renen, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Alfons Kemper
2020	J	`jnl`	Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. CoRR Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska
2020	J	`jnl`	Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. Proc. VLDB Endow. Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska
2019	J	`jnl`	ALEX: An Updatable Adaptive Learned Index. CoRR Jialin Ding, Umar Farooq Minhas, Hantian Zhang, Yinan Li, Chi Wang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David B. Lomet
2019	J	`jnl`	LISA: Towards Learned DNA Sequence Search. CoRR Darryl Ho, Jialin Ding, Sanchit Misra, Nesime Tatbul, Vikram Nathan, Md. Vasimuddin, Tim Kraska
2019	J	`jnl`	Learning Multi-dimensional Indexes. CoRR Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska
2018	J	`jnl`	MacroBase: Prioritizing Attention in Fast Data. ACM Trans. Database Syst. Firas Abuzaid, Peter Bailis, Jialin Ding, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri
2018	J	`jnl`	Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries. CoRR Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, Peter Bailis
2018	J	`jnl`	Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries. Proc. VLDB Endow. Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, Peter Bailis