Anna Fariha

I am an Assistant Professor at Kahlert School of Computing, the University of Utah. I co-lead the Data Management Research Center for Human-centered, Efficient, and Scalable Systems. I was a researcher at Microsoft PROSE Research and Engineering team. I obtained my Ph.D. from Manning College of Information and Computer Sciences (CICS), University of Massachusetts, Amherst under the supervision of Prof. Alexandra Meliou.

I am interested in solving various data-management problems targeted towards boosting usability, explainability, and trustworthiness of data systems. My current focus is on designing mechanisms for enhancing system usability and developing intelligent tools towards boosting productivity for a various group of users, ranging from end users to data scientists and developers. My research techniques involve invention of new algorithms and applying theory into practice.

Research Focus: Recommendation Systems for Data-Management Tasks

Recommending Data Summarization

Data-Semantics-Aware Recommendation of Diverse Pivot Tables. SIGMOD 2026
SAGE: Adaptive Recommendation of Spreadsheet Pivot Tables. SIGMOD 2026 Demo (under review)
UTOPIA: Automatic Pivot Table Assistant. VLDB 2024 Demo
SuDocu: Summarizing Documents by Example. VLDB 2020 Demo

Recommending Data Wrangling

WN–Wrangle: Wireless Network Data Wrangling Assistant. SIGMOD 2026 Demo (under review)
CoWrangler: Recommender System for Data-Wrangling Scripts. SIGMOD 2023 Demo
Development of Data Evaluation Benchmark for Data Wrangling Recommendation System. arXiv pre-print

Prospective students

Research positions: I am not looking to hire any student as of now. Do not email me asking for research opportunities.
Seeking TA positions: If you are interested in TA positions for my course, do NOT email me. Apply to the KSoC TA portal.

News

[November 2025] Two papers accepted to SIGMOD 2026.
[June 2025] Presented a paper at the HILDA workshop at SIGMOD 2025.
[May 2025] Gave a talk at the Department of Computer Science, Institute of Science Tokyo.
[May 2025] Gave a talk at Osaka University.
[May 2025] Paper accepted to HILDA workshop at SIGMOD 2025.
[April 2025] Gave a talk at Database Seminar at Cornell University.
[April 2025] Received a Stena Center for Financial Technology Seed Grant for the project Intelligent Data Summary Recommendations for Fintech Data Analysis.
[March 2025] Demonstration paper accepted to SIGMOD 2025.

More News

[December 2024] Demonstration paper accepted to ICDE 2025.

[July 2024] Received NSF CIRC: ENS/Grand: POWDER-ENS Award.

[May 2024] Demonstration paper accepted to VLDB 2024.

[May 2024] Paper accepted to VLDB 2024.

[May 2024] Recognized as one of the distinguished PC members at ACM SIGMOD 2024.

[February 2024] Received a One Utah Data Science Hub Seed Grant for the project Explaining Data Evolution.

[February 2024] Attended CRA Career Mentoring Workshop at Washington, DC.

[February 2024] Was one of the panelists on AI and Data Management at the Northwest Database Society (NWDS) Annual Meeting 2024 at Kirkland, WA.

[November 2023] Attended Workshop on Logic and Algebra for Query Evaluation at Simons Institute for the Theory of Computing, Berkeley, CA.

[November 2023] Attended CRA-WP Career Mentoring Workshop 2023, Chicago, IL.

[October 2023] Paper accepted to SIGCSE 2024.

[June 2023] Recognized as one of the distinguished PC members at ACM SIGMOD 2023.

[May 2023] Gave a talk at Northwest Database Society (NWDS) Annual Meeting 2023, Seattle, WA.

[February 2023] Demonstration paper accepted to SIGMOD 2023.

[September 2022] Attended Grace Hopper Celebration 2022, Orlando, FL.

[September 2022] Paper accepted to OOPSLA 2022.

[June 2022] Recognized as one of the distinguished PC members at ACM SIGMOD 2022.

[June 2022] Won the ACM SIGMOD 2022 Comprehensive Reproducibility Award.

[June 2022] Was one of the panelists at the ACM SIGMOD 2022 New Researcher Symposium, Philadelphia, PA.

[December 2021] Two papers accepted to SIGMOD 2022.

[November 2021] Gave a talk at University of Washington, Northwest Database Society (NWDS), Seattle, WA.

[October 2021] Gave a talk at MIT CSAIL's Semantic data management reading group (Virtual).

[September 2021] Paper accepted to NewSum EMNLP Workshop 2021.

[June 2021] Joined Microsoft PROSE team as a Researcher.

[May 2021] Successfully defended Ph.D. dissertation.

[May 2021] Demonstration paper accepted to VLDB 2021.

[February 2021] Gave a talk at University of Pennsylvania.

[February 2021] Demonstration paper accepted to SIGMOD 2021.

[January 2021] Gave a talk at Data Lab at Northeastern University.

[December 2020] Paper accepted to SIGMOD 2021.

[October 2020] Successfully defended dissertation proposal.

[September 2020] Won the best demonstration runner-up award for SuDocu at VLDB 2020.

[June 2020] Demonstration paper accepted to VLDB 2020.

[June 2020] Received Microsoft Research Dissertation Grant [CICS news].

[May 2020] Completed Masters.

[March 2020] Paper accepted to SIGMOD 2020.

[February 2020] Demonstration paper accepted to SIGMOD 2020.

[June 2019] Paper accepted to VLDB 2019.

[May 2019] Worked as a research intern at PROSE, Microsoft, Bellevue. Mentor: Ashish Tiwari.

[April 2019] Passed portfolio.

[May 2018] Worked as a research intern at DMX, Microsoft Research, Redmond. Mentor: Suman Nath.

[February 2018] Demonstration paper accepted to SIGMOD 2018.

[September 2016] Received Jim Gray Scholarship (CICS, UMass).

Recent Publications

Conference, Journal and Workshop papers and Demonstrations (peer-reviewed)

Anna Fariha, Lucy Cousins, Narges Mahyar, Alexandra Meliou:
Example-Driven User Intent Discovery: Empowering Users to Cross the SQL Barrier Through Query by Example.
Information Systems (2026)
Whanhee Cho, Anna Fariha:
Data-Semantics-Aware Recommendation of Diverse Pivot Tables.
SIGMOD (2026)
Tal Blau, Brit Youngmann, Anna Fariha, Yuval Moskovitch:
Causal Explanations for Disparate Trends: Where and Why?
SIGMOD (2026)
Bhavya Chopra, Ananya Singha, Anna Fariha, Sumit Gulwani, Chris Parnin, Ashish Tiwari, Austin Z. Henley:
Challenges in Using Conversational AI for Data Science. [Workshop]
HILDA@SIGMOD (2025)
Shiyi He, Alexandra Meliou, Anna Fariha:
ChARLES: Change-Aware Recovery of Latent Evolution Semantics in Relational Data. [Demo]
SIGMOD (2025)
Ankita Sharma, Jaykumar Tandel, Xuanmao Li, Lanjun Wang, Anna Fariha, Liang Zhang, Syed Arsalan Ahmed Naqvi, Irbaz Bin Riaz, Lei Cao, Jia Zou:
DataMorpher: Automatic Data Transformation Using LLM-based Zero-Shot Code Generation. [Demo]
ICDE (2025)
Whanhee Cho, Anna Fariha:
UTOPIA: Automatic Pivot Table Assistant. [Demo]
VLDB (2024)
Zifan Liu, Shaleen Deep, Anna Fariha, Fotis Psallidas, Ashish Tiwari, Avrilia Floratou:
Rapidash: Efficient Detection of Constraint Violations.
VLDB (2024)
Anjali Singh, Anna Fariha, Christopher Brooks, Gustavo Soares, Austin Henley, Ashish Tiwari, Chethan M, Heeryung Choi, Sumit Gulwani:
Investigating Student Mistakes in Introductory Data Science Programming.
SIGCSE (2024)
Bhavya Chopra, Anna Fariha, Sumit Gulwani, Austin Z. Henley, Daniel Perelman, Mohammad Raza, Sherry Shi, Danny Simmons, Ashish Tiwari:
CoWrangler: Recommender System for Data-Wrangling Scripts. [Demo]
SIGMOD (2023)

Older Publications

Rohan Bavishi, Harshit Joshi, José Pablo Cambronero Sánchez, Anna Fariha, Sumit Gulwani, Vu Le, Ivan Radiček, Ashish Tiwari:
Neurosymbolic Repair for Low-Code Formula Languages.
OOPSLA (2022)

Sainyam Galhotra, Anna Fariha, Raoni Lourenço, Juliana Freire, Alexandra Meliou, Divesh Srivastava:
DataPrism: Exposing Disconnect between Data and Systems
SIGMOD (2022)

Maliha Tashfia Islam, Anna Fariha, Alexandra Meliou, Babak Salimi:
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification
SIGMOD (2022)

El Kindi Rezig, Anshul Bhandari, Anna Fariha, Benjamin Price, Allan Vanterpool, Andrew Bowne, Lindsey McEvoy, Vijay Gadepally:
Examples are All You Need: Iterative Data Discovery by Example in Data Lakes [Abstract]
CIDR (2022)

Nishant Yadav^*, Matteo Brucato^*, Anna Fariha^*, Oscar Youngquist, Julian Killingback, Alexandra Meliou, Peter J. Haas:
SubSumE: A Dataset for Subjective Summary Extraction from Wikipedia Documents. [Workshop paper]
NewSum@EMNLP (2021)

El Kindi Rezig, Anshul Bhandari, Anna Fariha, Benjamin Price, Allan Vanterpool, Vijay Gadepally, Michael Stonebraker:
DICE: Data Discovery by Example. [Demo]
VLDB (2021)

Anna Fariha, Ashish Tiwari, Alexandra Meliou, Arjun Radhakrishna, Sumit Gulwani:
CoCo: Interactive Exploration of Conformance Constraints for Data Understanding and Data Cleaning. [Demo]
SIGMOD (2021)

Anna Fariha^*, Ashish Tiwari^*, Arjun Radhakrishna, Sumit Gulwani, Alexandra Meliou:
Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems.
SIGMOD (2021)

Anna Fariha, Ashish Tiwari, Arjun Radhakrishna, Sumit Gulwani:
ExTuNe: Explaining Tuple Non-conformance. [Demo]
SIGMOD (2020)

Anna Fariha, Suman Nath, Alexandra Meliou:
Causality-Guided Adaptive Interventional Debugging.
SIGMOD (2020)

Anna Fariha, Matteo Brucato, Peter J. Haas, Alexandra Meliou:
SuDocu: Summarizing Documents by Example. [Demo]
VLDB (2020)

Anna Fariha, Alexandra Meliou:
Example-Driven Query Intent Discovery: Abductive Reasoning using Semantic Similarity.
VLDB (2019)

Anna Fariha, Sheikh Muhammad Sarwar, Alexandra Meliou:
SQuID: Semantic Similarity-Aware Query Intent Discovery. [Demo]
SIGMOD (2018)

Other Publications

Technical reports and pre-prints

Whanhee Cho, Shamit Fatin, Anna Fariha:
SAGE: Adaptive Recommendation of Spreadsheet Pivot Tables
(under submission at SIGMOD 2026 Demo Track)
Anirudh Kamath, Dustin Maas, Jacobus Van der Merwe, Anna Fariha:
WN–Wrangle: Wireless Network Data Wrangling Assistant
(under submission at SIGMOD 2026 Demo Track)
Tal Blau, Brit Youngmann, Anna Fariha, Yuval Moskovitch:
ExDis: Causal Explanations for Disparate Trends
(under submission at SIGMOD 2026 Demo Track)
Tal Blau, Brit Youngmann, Anna Fariha, Yuval Moskovitch:
Causal Explanations for Disparate Trends: Where and Why?
CoRR abs/2512.08679 (2025)
Whanhee Cho, Anna Fariha:
Data-Semantics-Aware Recommendation of Diverse Pivot Tables.
CoRR abs/2409.06892 (2025)
Rania Saber, Anna Fariha:
Formative Study for AI-assisted Data Visualization.
CoRR abs/2409.06892 (2024)
Yuqing Wang, Anna Fariha:
Development of Data Evaluation Benchmark for Data Wrangling Recommendation System.
CoRR abs/2409.10635 (2024)
Bhavya Chopra, Ananya Singha, Anna Fariha, Sumit Gulwani, Chris Parnin, Ashish Tiwari, Austin Z. Henley:
Conversational Challenges in AI-Powered Data Science: Obstacles, Needs, and Design Opportunities.
CoRR abs/2310.16164 (2023)
Zifan Liu, Shaleen Deep, Anna Fariha, Fotis Psallidas, Ashish Tiwari, Avrilia Floratou:
Rapidash: Efficient Constraint Discovery via Rapid Verification.
CoRR abs/2309.12436 (2023)
Rohan Bavishi, Harshit Joshi, José Pablo Cambronero Sánchez, Anna Fariha, Sumit Gulwani, Vu Le, Ivan Radiček, Ashish Tiwari:
Neurosymbolic Repair for Low-Code Formula Languages.
CoRR abs/2207.11765 (2022)
Anna Fariha:
Enhancing Usability and Explainability of Data Systems. Ph.D. Dissertation.
Doctoral Dissertations, University of Massachusetts Amherst (2021)
Sainyam Galhotra, Anna Fariha, Raoni Lourenço, Juliana Freire, Alexandra Meliou, Divesh Srivastava:
DataExposer: Exposing Disconnect between Data and Systems.
CoRR abs/2105.06058 (2021)
Maliha Tashfia Islam, Anna Fariha, Alexandra Meliou:
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification.
CoRR abs/2101.07361 (2021)
Anna Fariha, Lucy Cousins, Narges Mahyar, Alexandra Meliou:
Example-Driven User Intent Discovery: Empowering Users to Cross the SQL Barrier Through Query by Example.
CoRR abs/2012.14800 (2020)
Anna Fariha, Ashish Tiwari, Arjun Radhakrishna, Sumit Gulwani, Alexandra Meliou:
Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems.
CoRR abs/2003.01289 (2020)
Anna Fariha, Suman Nath, Alexandra Meliou:
Causality-Guided Adaptive Interventional Debugging.
CoRR abs/2003.09539 (2020)
Anna Fariha, Alexandra Meliou:
Example-Driven Query Intent Discovery: Abductive Reasoning using Semantic Similarity.
CoRR abs/1906.10322 (2019)

Undergraduate and masters research

Anna Fariha, Chowdhury Farhan Ahmed, Carson K. Leung, Md. Samiullah, Suraiya Pervin, Longbing Cao:
A New Framework for Mining Frequent Interaction Patterns from Meeting Databases.
Engineering Applications of Artificial Intelligence (2015)
Amit Mandal, Mehedi Hasan, Anna Fariha, Chowdhury Farhan Ahmed:
GSCS - Graph Stream Classification with Side Information.
APWeb (2015)
Quazi Marufur Rahman, Anna Fariha, Amit Mandal, Chowdhury Farhan Ahmed, Carson K. Leung:
A Sliding Window-Based Algorithm for Detecting Leaders from Social Network Action Streams.
WI-IAT (2015)
Shafaet Ashraf, Sheikh Muhammad Sarwar, Md. Abeed Hassan, Saifuddin Md. Tareeq, Anna Fariha:
An Efficient Method for Extracting Subtrees Against Forest Query.
IMCOM (2015)
Md. Samiullah, Chowdhury Farhan Ahmed, Anna Fariha, Akiz Uddin Ahmed:
Efficient Graph Classification in Shifted Datasets Using Weighted Correlated Feature Selection.
LMCE@ECML-PKDD (2014)
Md. Samiullah, Chowdhury Farhan Ahmed, Anna Fariha, Md. Rafiqul Islam, Nicolas Lachiche:
Mining Frequent Correlated Graphs with a New Measure.
Expert System with Applications (2014)
Md. Samiullah, Chowdhury Farhan Ahmed, Manziba Akanda Nishi, Anna Fariha, S. M. Abdullah, Md. Rafiqul Islam:
Correlation Mining in Graph Databases with a New Measure.
APWeb (2013)
Anna Fariha, Chowdhury Farhan Ahmed, Carson Kai-Sang Leung, S. M. Abdullah, Longbing Cao:
Mining Frequent Patterns from Human Interactions in Meetings Using Directed Acyclic Graphs.
PAKDD (2013)
Anna Fariha, Shariful Islam, Chowdhury Farhan Ahmed, Byeong-Soo Jeong:
An Algorithm towards Indexing Evolving Graph Databases.
GSTF Journal on Computing (2012)
Shariful Islam, Anna Fariha, Chowdhury Farhan Ahmed, Byeong-Soo Jeong:
EGDIM: Evolving Graph Database Indexing Method.
ICUIMC (2012)