Data Conference Databasea Query.Farm index
Speakers

Allison Ding

Employers on the program

  1. 2025NVIDIA3 talks
Events2
Conferences2
Talks3
Years active2025
Talk freshness1003 different talks in 3 · 1 circuit, 24 monthsMiles between events272 in-person events · 1 country

Appearances by year

201920202021202220232024202520262027
  • PyData
  • SciPy Conference (Scientific Computing with Python)

Talks

DateEventConferenceRoleTitleLinks
Nov 7, 2025PyData Seattle 2025PyDatatutorialScaling Large-Scale Interactive Data Visualization with Accelerated Computing
as NVIDIA
As datasets continue to grow in both size and complexity, CPU-based visualization pipelines often become bottlenecks, slowing down exploratory data analysis and…Show less

As datasets continue to grow in both size and complexity, CPU-based visualization pipelines often become bottlenecks, slowing down exploratory data analysis and interactive dashboards.

Jul 7, 2025SciPy 2025SciPy Conference (Scientific Computing with Python)tutorialScaling Clustering for Big Data: Leveraging RAPIDS cuML
as NVIDIA
This tutorial will explore GPU-accelerated clustering techniques using RAPIDS cuML, optimizing algorithms like K-Means, DBSCAN, and HDBSCAN for large datasets.…Show less

This tutorial will explore GPU-accelerated clustering techniques using RAPIDS cuML, optimizing algorithms like K-Means, DBSCAN, and HDBSCAN for large datasets. Traditional clustering methods struggle with scalability, but GPU acceleration significantly enhances performance and efficiency.

Jul 7, 2025SciPy 2025SciPy Conference (Scientific Computing with Python)speakerUnlocking AI Performance with NeMo Curator: Scalable Data Processing for LLMs
as NVIDIA
Training Large Language Models (LLMs) requires processing massive-scale datasets efficiently. Traditional CPU-based data pipelines struggle to keep up with the…Show less

Training Large Language Models (LLMs) requires processing massive-scale datasets efficiently. Traditional CPU-based data pipelines struggle to keep up with the exponential growth of data, leading to bottlenecks in model training.

Frequent co-speakers

SpeakerShared eventsShared talksLast together
Avik Basu2—2025
C.A.M. Gerlach2—2025
Carlos García Jurado Suarez2—2025
Daniel Chen2—2025
Noor Aftab2—2025
Sarah Kaiser2—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.