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ORCIDJialin Ding 0001
Person information
- affiliation: Princeton University, Department of Computer Science, Princeton, NJ, USA
- affiliation: Amazon Web Services, Boston, MA, USA
- affiliation (PhD 2022): Massachusetts Institute of Technology, Cambridge, MA, USA
- affiliation (2014 - 2018): Stanford University, InfoLab, Stanford, CA, USA
Other persons with the same name
- Jialin Ding — disambiguation page
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2020 – today
- 2025
[j6]Mihail Stoian, Andreas Zimmerer, Skander Krid, Amadou Ngom, Jialin Ding, Tim Kraska, Andreas Kipf:
Parachute: Single-Pass Bi-Directional Information Passing. Proc. VLDB Endow. 18(10): 3299-3311 (2025)- [c9]Varun Pandey, Alexander van Renen, Eleni Tzirita Zacharatou
, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Volker Markl, Alfons Kemper:
Enhancing In-Memory Spatial Indexing with Learned Search. BTW 2025: 303-330 - [c8]Matthias Urban, Jialin Ding, David Kernert, Kapil Vaidya, Tim Kraska:
Utilizing Past User Feedback for More Accurate Text-to-SQL. HILDA@SIGMOD 2025: 10:1-10:7 - [i13]Kapil Vaidya, Abishek Sankararaman, Jialin Ding, Chuan Lei, Xiao Qin, Balakrishnan Narayanaswamy, Tim Kraska:
ODIN: A NL2SQL Recommender to Handle Schema Ambiguity. CoRR abs/2505.19302 (2025) - [i12]Kapil Vaidya, Jialin Ding, Sebastian Kosak, David Kernert, Chuan Lei, Xiao Qin, Abhinav Tripathy, Ramesh Balan, Balakrishnan Narayanaswamy, Tim Kraska:
TailorSQL: An NL2SQL System Tailored to Your Query Workload. CoRR abs/2505.23039 (2025) - [i11]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:
KramaBench: A Benchmark for AI Systems on Data-to-Insight Pipelines over Data Lakes. CoRR abs/2506.06541 (2025) - [i10]Mihail Stoian, Andreas Zimmerer, Skander Krid, Amadou Latyr Ngom, Jialin Ding, Tim Kraska, Andreas Kipf:
Parachute: Single-Pass Bi-Directional Information Passing. CoRR abs/2506.13670 (2025) - 2024
- [c7]Jenny Gao, Jialin Ding, Sivaprasad Sudhir, Samuel Madden:
Learning Bit Allocations for Z-Order Layouts in Analytic Data Systems. aiDM@SIGMOD 2024: 5:1-5:9 - [c6]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:
Automated Multidimensional Data Layouts in Amazon Redshift. SIGMOD Conference Companion 2024: 55-67 - 2023
- [i9]Varun Pandey, Alexander van Renen, Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Volker Markl, Alfons Kemper:
Enhancing In-Memory Spatial Indexing with Learned Search. CoRR abs/2309.06354 (2023) - 2022
- [b1]Jialin Ding:
Instance-Optimized Database Indexes and Storage Layouts. MIT, USA, 2022 - [j5]Jialin Ding, Ryan Marcus, Andreas Kipf, Vikram Nathan, Aniruddha Nrusimha, Kapil Vaidya, Alexander van Renen, Tim Kraska:
SageDB: An Instance-Optimized Data Analytics System. Proc. VLDB Endow. 15(13): 4062-4078 (2022) - [c5]Samuel Madden, Jialin Ding, Tim Kraska, Sivaprasad Sudhir, David E. Cohen, Timothy G. Mattson, Nesime Tatbul:
Self-Organizing Data Containers. CIDR 2022 - 2021
- [j4]Baotong Lu, Jialin Ding, Eric Lo, Umar Farooq Minhas, Tianzheng Wang:
APEX: A High-Performance Learned Index on Persistent Memory. Proc. VLDB Endow. 15(3): 597-610 (2021) - [c4]Jialin Ding, Umar Farooq Minhas, Badrish Chandramouli, Chi Wang, Yinan Li, Ying Li, Donald Kossmann, Johannes Gehrke, Tim Kraska:
Instance-Optimized Data Layouts for Cloud Analytics Workloads. SIGMOD Conference 2021: 418-431 - [i8]Baotong Lu, Jialin Ding, Eric Lo, Umar Farooq Minhas, Tianzheng Wang:
APEX: A High-Performance Learned Index on Persistent Memory. CoRR abs/2105.00683 (2021) - 2020
- [j3]Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska:
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. Proc. VLDB Endow. 14(2): 74-86 (2020) - [c3]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:
ALEX: An Updatable Adaptive Learned Index. SIGMOD Conference 2020: 969-984 - [c2]Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska:
Learning Multi-Dimensional Indexes. SIGMOD Conference 2020: 985-1000 - [c1]Varun Pandey, Alexander van Renen, Andreas Kipf, Jialin Ding, Ibrahim Sabek, Alfons Kemper:
The Case for Learned Spatial Indexes. AIDB@VLDB 2020 - [i7]Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska:
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. CoRR abs/2006.13282 (2020) - [i6]Varun Pandey, Alexander van Renen, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Alfons Kemper:
The Case for Learned Spatial Indexes. CoRR abs/2008.10349 (2020) - [i5]Vikram Nathan, Jialin Ding, Tim Kraska, Mohammad Alizadeh:
Cortex: Harnessing Correlations to Boost Query Performance. CoRR abs/2012.06683 (2020)
2010 – 2019
- 2019
- [i4]Jialin Ding, Umar Farooq Minhas, Hantian Zhang, Yinan Li, Chi Wang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David B. Lomet:
ALEX: An Updatable Adaptive Learned Index. CoRR abs/1905.08898 (2019) - [i3]Darryl Ho, Jialin Ding, Sanchit Misra, Nesime Tatbul, Vikram Nathan, Md. Vasimuddin, Tim Kraska:
LISA: Towards Learned DNA Sequence Search. CoRR abs/1910.04728 (2019) - [i2]Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska:
Learning Multi-dimensional Indexes. CoRR abs/1912.01668 (2019) - 2018
- [j2]Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, Peter Bailis:
Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries. Proc. VLDB Endow. 11(11): 1647-1660 (2018) - [j1]Firas Abuzaid, Peter Bailis, Jialin Ding, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri:
MacroBase: Prioritizing Attention in Fast Data. ACM Trans. Database Syst. 43(4): 15:1-15:45 (2018) - [i1]Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, Peter Bailis:
Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries. CoRR abs/1803.01969 (2018)
Coauthor Index
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