Jin Wang (王津)
Ph.D.

Assistant Professor
School of Computing and Augmented Intelligence, Arizona State University

E-mail: jinwang18 [at] asu.edu

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About Me

I am a tenure-track assistant professor at Arizona State University since Fall 2025. I was a Research Scientist in Megagon Labs from 2020 to 2025. Before that I obtained my Ph.D. degree from Computer Science Department, University of California, Los Angeles in July 2020 under the supervision of Professor Carlo Zaniolo. The title of my PhD thesis is "Power, Performance and Scalability for Big Data Query Languages: The Machine Learning Challenge" (Available online here). And I obtained my Master degree of Engineering from Department of Computer Science and Technology, Tsinghua Univeristy in 2015. I am a member of ACM and IEEE.

My research interests lies in the broad areas of database, machine learning and natural language processing. The primary goal of my research is to develop robust and efficient tools and systems for real world data science tasks from various disciplines and application domains. In particular, my recent research focuses on the topics of data integration, data discovery and compound AI systems.

News

Aug. 2025
I start my journey as an assistant professor in ASU! I am looking for one to two PhD students starting at Fall 2026. If you are interested in working with me, please send me an email with your CV and transcripts.
July 2025
Two papers got accepted by VLDB 2025. See you in London!
April 2025
I will join ASU as an assistant professor in Fall 2025.
Aug. 2024
Selected as the Distinguished Reviewer of VLDB 2024 (PVLDB Vol. 17).
June 2023
We will give a tutorial titled "Table Discovery in Data Lakes: State-of-the-art and Future Directions" in SIGMOD 2023. Please visit our website for more information
Feb. 2023
Our work about Semantics-aware Dataset Discovery from Data Lakes got accepted by VLDB 2023. The preprint is available now.
Nov. 2022
Our Sudowoodo paper that employs Contrastive Learning for Entity Matching got accepted by IEEE ICDE 2023, check our repo for the source code.
June 2022
Our Minun paper wins the best paper runner-up of the 6th Workshop on Data Management for End-to-End Machine Learning (co-located w/ SIGMOD 2022)!
Dec. 2021
Our work about Parallel Datalog Query Processing on Multi-core Machine is accepted by SIGMOD 2022!
Nov. 2021
We release the benchmark tasks for Generalized Entity Matching, check our repo.
Mar. 2021
The work towards my PhD defense is accepted by The VLDB Journal! It is part of our Radlog System.
Feb. 2021
Two papers got accepted by IEEE ICDE 2021.
Dec. 2020
Invited as the Senior PC Member of IJCAI 2021, PC Member of ACL and KDD 2021.
Oct. 2020
Our Vision Paper "Deep Entity Matching: Challenges and Opportunities" is accepted by JDIQ.
August 2020
Start my new journey in Megagon Lab!
June 2020
Smoothly pass my final defense.
Feb. 2020
I am granted the Graduate Fellowship for Spring 2020. Really appreciate the gift from the CS Department!
Sept. 2019
I am promoted to Teaching Fellow since Fall 2019.
Aug 2019
Our tutorial titled "Syn­ergy of Data­base Tech­niques and Ma­chine Learn­ing Mod­els for String Sim­il­ar­ity Search and Join" is accepted by CIKM 2019.
May 2019
Smoothly passed oral qualifying exam.
May 2019
Two papers got accepted by IJCAI 2019.
Feb. 2019
Three papers got accepted by IEEE ICDE 2019.
Dec. 2018
Paper "A Transformation-based Framework for KNN Set Similarity Search" accepted by IEEE TKDE.
Nov. 2018
Paper "An Efficient Sliding Window Approach for Approximate Entity Extraction with Synonyms" accepted by EDBT 2019. See you in Lisbon!
Sep. 2018
Finish summer internship at Amazon A9.
Apr. 2017
One full paper accepted by IJCAI 2017.
Jan. 2017
One full paper and one poster accepted by ICDE 2017.
Sep. 2016
Finish a nice internship in Microsoft Research Beijing with Dr. Zhongyuan Wang.
Dec. 2015
Our demo paper of CEP-R System is accepted by ICDE 2016.
Aug. 2015
Sep. 2015. Join University of California, Los Angeles. Go Bruins!