Aarti Jha
Employers on the program
- 2025–2026Red Hat4 talks
The year around now
Talks in the past 12 months and announced talks ahead, one row per conference, January to December. Hover a mark for the talk.
Appearances by year
- PyData
- PyCon (national Python conferences)
- SciPy Conference (Scientific Computing with Python)
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Jul 13, 2026 | SciPy 2026 | SciPy Conference (Scientific Computing with Python) | speaker | Docling for Multimodal Retrieval as Red Hat Scientific breakthroughs don’t happen in plain text, they live inside multi-column research papers, dense data tables, and intricate simulation diagrams. Yet…Show lessScientific breakthroughs don’t happen in plain text, they live inside multi-column research papers, dense data tables, and intricate simulation diagrams. Yet the moment standard AI and Retrieval-Augmented Generation (RAG) pipelines encounter these layouts, they fail. | |
| Jul 13, 2026 | SciPy 2026 | SciPy Conference (Scientific Computing with Python) | tutorial | Engineering Better Retrieval for RAG (Room HSEC 3-110) as Red Hat The quality of the retrieval component is what drives Retrieval-Augmented Generation (RAG) systems. Therefore, a well-structured, measurable, and robust…Show lessThe quality of the retrieval component is what drives Retrieval-Augmented Generation (RAG) systems. Therefore, a well-structured, measurable, and robust retrieval pipeline is critical to building effective large language model (LLM) applications. | |
| Sep 24, 2025 | PyData Amsterdam 2025 | PyData | tutorial | Next-Level Retrieval in RAG: Techniques and Tools for Enhanced Performance as Red Hat Retrieval-Augmented Generation (RAG) systems rely heavily on the quality of the retrieval process to generate accurate and contextually relevant outputs. | |
| Sep 12, 2025 | PyCon India 2025 | PyCon (national Python conferences) | talk | Mastering Prompts with Feedback and Pydantic as Red Hat Prompt engineering has become a core skill in working with LLMs, yet writing effective prompts is tedious, inconsistent, and often requires multiple attempts.…Show lessPrompt engineering has become a core skill in working with LLMs, yet writing effective prompts is tedious, inconsistent, and often requires multiple attempts. Most prompt development today is done manually, relying on trial and error, which doesn’t scale well, especially in production... | |
| Nov 6, 2024 | PyData NYC 2024 | PyData | speaker | The Art of Compression: Crafting Insightful Summaries with LLMs | Video |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Mahima Arora | 3 | 4 | 2026 |
| Gil Forsyth | 2 | — | 2026 |
| Jacob Tomlinson | 2 | — | 2026 |
| Katrina Riehl | 2 | — | 2026 |
| Roni Kobrosly | 2 | — | 2026 |
| Javier de la Rúa Martínez | 2 | — | 2025 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.