Aditya Parameswaran
Associate Professor
Builds data science tools such as Modin, Lux and DocETL, including LLM-powered data processing.
Aditya Parameswaran's lab at UC Berkeley works on data management & big data. 36 papers since 2023, 24 at top venues, mostly VLDB and UIST. Applications close .
At a glance
- papers, 2023–2026
- 9/ year
- at T1 venues
- 67%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 8 papers2026 · T1 4 · collecting
- 12 papers2025 · T1 8
- 10 papers2024 · T1 6
- 6 papers2023 · T1 6
T1 venuesOtherVenues: VLDB, UIST, CIKM, CSCW, ICDE
Research focuspaper titles that use each topic's words
- Data management & big data9 papers
- data processing5 papers
- builds data0 papers
- tools0 papers
- computer sciences0 papers
Paper list
From the lab homepage.
20268 papers
- VLDB (T1)Bolt-on, Verifiable Provenance for LLM-Powered Data Processing
- ACM SIGMOD Int'l Conf. on Management of DataCut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees (opens in a new tab)
- VLDB (T1)Featurized-Decomposition Join: Low-Cost Semantic Joins with Guarantees (opens in a new tab)
- VLDB (T1)Multi-Objective Agentic Rewrites for Unstructured Data Processing (opens in a new tab)
- CHI (T1)RAG Without the Lag: Enabling 'What-If' Analysis for Retrieval-Augmented Generation Pipelines (opens in a new tab)
- CIDRSupporting Our AI Overlords: Redesigning Data Systems to be Agent-First (opens in a new tab)
- ACM SIGMOD Int'l Conf. on Management of DataTask Cascades for Efficient Unstructured Data Processing (opens in a new tab)
- ACM SIGMOD Int'l Conf. on Management of DataVisual Template Inference for Data Extraction from Documents (opens in a new tab)
202512 papers
- VLDB (T1)DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing (opens in a new tab)
- CIDRFlow with FlorDB: Incremental Context Maintenance for the Machine Learning Lifecycle (opens in a new tab)
- IEEE Data Engineering BulletinLLM-Powered Proactive Data Systems (opens in a new tab)
- ICLR (T1)NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval (opens in a new tab)
- ACM SIGMOD Int'l Conf. on Management of DataPhysical Visualization Design: Decoupling Interface and System Design (opens in a new tab)
- NAACL (T1)PromptEvals: A Dataset of Assertions and Guardrails for Custom Production Large Language Model Pipelines (opens in a new tab)
- CSCW (T1)RequestAtlas: Supporting the Slow and Iterative Process of Requesting Public Records (opens in a new tab)
- UIST (T1)Rethinking Dataset Discovery with DataScout (opens in a new tab)
- UIST (T1)Steering Semantic Data Processing With DocWrangler (opens in a new tab)
- ICDE (T1)Towards Accurate and Efficient Document Analytics with Large Language Models (opens in a new tab)
- VLDB Journal (T1)Transactional panorama: a conceptual framework for user perception in analytical visual interfaces (extended version) (opens in a new tab)
- Advances in Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks TrackWhy Do Multi-Agent LLM Systems Fail? (opens in a new tab)
202410 papers
- Workshop on Human-in-the-Loop Data Analytics (HILDA) at the ACM SIGMOD Int'l Conf. on Management of Data'It Took Longer than I was Expecting': Why is Dataset Search Still so Hard? (opens in a new tab)
- CSCW (T1)'We Have No Idea How Models will Behave in Production until Production': How Engineers Operationalize Machine Learning (opens in a new tab)
- TRL Workshop @ NeurIPSBenchmarking Table Retrieval for Generative Tasks
- ACM SIGMOD Int'l Conf. on Management of DataBuilding Reactive Large Language Model Pipelines with Motion (Demo)
- VLDB (T1)Dealing with Acronyms, Abbreviations, and Typos in Real-World Entity Matching
- CIKM (T1)Inferring Visualization Intent from Conversation
- UIST (T1)Quilt: Custom UIs for Linking Unstructured Documents to Structured Datasets (Demo)
- CIDRRevisiting Prompt Engineering via Declarative Crowdsourcing (opens in a new tab)
- VLDB (T1)SPADE: Synthesizing Assertions for Large Language Model Pipelines (opens in a new tab)
- UIST (T1)Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences (opens in a new tab)
20236 papers
- CIKM (T1)Automatic and Precise Data Valitation for Machine Learning (opens in a new tab)
- VLDB (T1)Bolt-on, Compact, and Rapid Program Slicing for Notebooks (opens in a new tab)
- ICDE (T1)Efficient and Compact Spreadsheet Formula Graphs (opens in a new tab)
- VLDB (T1)Towards Observability for Production Machine Learning Pipelines (opens in a new tab)
- VLDB (T1)Transactional Panorama: A Conceptual Framework for User Perception in Analytical Visual Interfaces (opens in a new tab)
- VLDB (T1)Visualizing Spreadsheet Formula Graphs Compactly
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UC BerkeleyFall 2027
UC Berkeley EECS Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS (non-English-country degrees)
- Fee
- See program page
Confirmed on the program page.
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Data
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