Sajjadur Rahman
Adobe Founders Tower, San Jose, CA 95113

I am a Senior ML Manager at Adobe. My current efforts focus on driving AI Quality initiatives at Adobe Experience Platform where we strive to reimagine how enterprises engage with audiences, orchestrate journeys, and drive personalization in an era shaped by agent-driven intelligence. Prior to that, I was a Senior Research Scientist and the founding Research Manager of the Data-AI Symbiosis (DAIS) group Megagon Labs where I led research efforts that supported agentic workflows over enterprise data to enable self-serving analytics at scale. I received my PhD from CS@Illinois where I worked with Aditya Parameswaran.

My research synthesizes techniques from data management, AI, and HCI to build scalable, interactive, and responsible systems. My work has been published in premier conferences in Databases (SIGMOD and VLDB), HCI (CHI and CSCW), and NLP (EMNLP and NAACL.) I collaborated on research projects that were recognized with the best demo award (at ICDE) and featured in popular tech blogs. My research enabled scalable data exploration in open-source tools (e.g., DataSpread), and enjoyed adoption in the industry (e.g., a planning tool for creative design at the startup B12.) I served as Program Chair of several workshops (DAIS@ICDE'25 and MATCHING@ACL'23) and served on the program committee of SIGMOD, VLDB, EMNLP, ACL, and IEEE ISSRE.

News

  • Received Distinguished Reviewer Award at SIGMOD 2025.
    April 22, 2025
  • Joined Adobe Inc. to lead AI Quaity and Safety initiatives at Adobe Experience Platform.
    April 14, 2025
  • Released Cypherbench, a large-scale benchmark for evaluating NL2Cypher tasks.
    January 7, 2024
  • Article on RAG in the Wild accepted at IEEE Data Engg. Bulletin.
    December 22, 2024
  • Workshop on Data-AI Systems accepted at ICDE'25.
    September 15, 2024
  • Paper on "Characterizing LLMs as Rationalizers" accepted at ACL'24 Findings.
    May 15, 2024
  • Paper on "Benchmarking Data Discovery in the Enterprise" accepted at GUIDE-AI@SIGMOD'24.
    May 12, 2024
  • Demo on "Human-LLM Collaborative Annotation System" accepted at EACL'24.
    January 22, 2024
  • Paper on "Human-LLM Collaborative Annotation Through Effective Verification" accepted at CHI'24.
    January 18, 2024

Selected Projects

A System 2 Perspective of AI Agents

Agentic for Enterprise

We outline our approaches toward understanding and implementing a more effective agentic workflow in the wild. To achieve the goal, we draw on the cognitive science concepts of System 1 (fast, intuitive thinking) and System 2 (slow, deliberate, analytical thinking.).

Human-in-the-loop data science

Characterizing Human-in-the-loop information extraction workflows

We observed that data science workers follow an iterative task model consisting of information foraging and sensemaking loops across all the phases of an information extraction workflow. We found several limitations in both loops stemming from a lack of adherence to existing cognitive engineering principles.

Progressive Visualization with Incvisage

Incvisage

IncVisage is a progressive visualization tool that reveals “salient” features of a visualization quickly while minimizing error, enabling rapid and error-free decision making. The approach is orders of magnitude faster than the traditional visualization systems.

Selected Publications

Synergistic Activities

2024    VLDB'24 (PC), SIGMOD'25 (PC), Reviewer:NLP4HR@EACL'24, TiiS
2023    MATCHING@ACL 2023 (Program Chair), MATHCING@ACL 2023 (Panel Moderator), ACL 2023 (PC), EMNLP 2023 (PC), BLP@EMNLP 2023 (PC), SIGMOD 2023 (Demo PC), BigVIS 2023 (PC), CHI 2023 (Reviewer)
2022    EMNLP 2022 (PC), DaSH@EMNLP 2022 (PC), ISSRE 2022 (Industry PC), BigVIS 2022 (PC), WIT@ACL (PC), CHI 2022 (Reviewer)
2021    SIGMOD 2022 (PC), VLDB 2021 (Panelist), BigVIS 2021 (PC), WIT@KDD (PC), CHI 2021 (Reviewer)
2020    SIGMOD 2021 (PC)
2019    VLDB 2019 (Demo, external reviewer)
2018    IIT 2018 (PC)

Papers by Research Themes

Interactivity

  • Towards Transparent, Reusable, and Customizable Data Science in Computational Notebooks CHI 2023 LBW.
  • [Demo] Weedle: Composable Dashboard for Data-centric NLP in Computational Notebooks WWW 2023.
  • NOAH: Interactive Spreadsheet Exploration with Dynamic Hierarchical Overviews. VLDB 2021.
  • [Workshop] Towards integrated, interactive, and extensible text data analytics with LEAM. DASH-LA@NAACL 2021.
  • Leam: An Interactive System for In-situ Visual Text Analysis. CIDR 2021.
  • MixTAPE: Mixed-initiative Team Action Plan Creation Through Semi-structured Notes, Automatic Task Generation, and Task Classification. CSCW 2020.
  • I’ve Seen “Enough”: Incrementally Improving Visualizations to Support Rapid Decision Making. VLDB 2017.
  • SeeDB: Efficient data-driven visualization recommendations to support visual analytics. VLDB 2015.

    • Scalability

  • [Vision]Toward multifaceted human-centered AI HCAI@NeurIPS 2022.
  • Low-resource Interactive Active Labeling for Fine-tuning Language Models. Findings of EMNLP 2022.
  • Benchmarking Spreadsheet Systems. SIGMOD 2020.
  • NOAH: Interactive Spreadsheet Exploration with Dynamic Hierarchical Overviews. VLDB 2021.
  • [Demo] Faster, Higher, Stronger: Redesigning Spreadsheets for Scale. ICDE 2019.
  • I’ve Seen “Enough”: Incrementally Improving Visualizations to Support Rapid Decision Making. VLDB 2017.
  • SeeDB: efficient data-driven visualization recommendations to support visual analytics. VLDB 2015.

    • Empirical Studies

  • [Workshop] CMDBench: A Benchmark for Coarse-to-fine Multimodal Data Discovery in Compound AI Systems. Guide-AI@SIGMOD 2024.
  • Characterizing LLMs as Rationalizers of Knowledge-intensive Tasks. Findings of ACL 2024.
  • Human-LLM collaborative annotation through effective verification of LLM labels. CHI 2024.
  • Characterizing practices, limitations, and opportunities related to text information extraction workflows: a human-in-the-loop perspective. CHI 2022.
  • Low-resource Entity Set Expansion: A Comprehensive Study on User-Generated Text Findings of NAACL 2022.
  • Benchmarking Spreadsheet Systems. SIGMOD 2020.
  • [Workshop] Understanding Data Analysis Workflows on Spreadsheets: Roadblocks and Opportunities. HILDA@SIGMOD 2020.