# Josefine Vilsbøll Sundgaard

> researcher, ORCiD ID=0000-0003-2872-4660

**Wikidata**: [Q123436571](https://www.wikidata.org/wiki/Q123436571)  
**Source**: https://4ort.xyz/entity/josefine-vilsbll-sundgaard

## Summary
Josefine Vilsbøll Sundgaard is a researcher specializing in the fields of machine learning and deep learning. She is affiliated with DTU Compute and the Danish Data Science Academy, where she contributes to the study of algorithms and statistical models used in computer science.

## Biography
*   **Known for:** Research in deep learning and machine learning.
*   **Employer(s):** DTU Compute.
*   **Affiliation:** Danish Data Science Academy.
*   **Field(s):** Computer Science, Machine Learning, Deep Learning.
*   **Identifiers:** ORCiD ID: 0000-0003-2872-4660; DBLP Author ID: 269/9949; Google Scholar Author ID: gFkcjsQAAAAJ.

(Note: Specific details regarding birth, nationality, and education were not present in the provided source material and have been omitted.)

## Contributions
Josefine Vilsbøll Sundgaard contributes to the academic and scientific community through her research in computer science, with a specific focus on machine learning and its subset, deep learning. Her work involves the scientific study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions.

She is professionally affiliated with DTU Compute, a department dedicated to mathematics and computer science, and is a recognized member of the Danish Data Science Academy. Her professional output is tracked and verified through multiple academic identifiers, including an ORCiD ID, a DBLP author record, and a Google Scholar profile. These profiles serve as repositories for her contributions to the study of computation and algorithmic development.

## FAQs
### Q: What is Josefine Vilsbøll Sundgaard’s primary research focus?
A: Her primary research focus is in the field of computer science, specifically within machine learning and deep learning.

### Q: Which institutions is Josefine Vilsbøll Sundgaard affiliated with?
A: She is affiliated with DTU Compute and the Danish Data Science Academy.

### Q: How can I find Josefine Vilsbøll Sundgaard’s academic publications?
A: Her academic publications can be found using her identifiers: ORCiD ID 0000-0003-2872-4660, DBLP Author ID 269/9949, or her Google Scholar Author ID gFkcjsQAAAAJ.

## Why They Matter
Josefine Vilsbøll Sundgaard plays a role in the advancement of data science and computational research within the Danish academic landscape. By aligning her work with DTU Compute and the Danish Data Science Academy, she contributes to the broader scientific understanding of how algorithms and statistical models function. Her research area—deep learning—is a critical branch of machine learning that enables complex data processing and pattern recognition. Her involvement in cross-academy collaboration through the Danish Data Science Academy highlights her participation in the strategic development of data science competencies.

## Notable For
*   **Research Specialization:** Focus on deep learning, a complex branch of machine learning.
*   **Academic Affiliation:** Association with DTU Compute, a prominent institution for mathematics and computer science.
*   **National Collaboration:** Membership in the Danish Data Science Academy, contributing to cross-academy collaboration.

## Body
### Research and Field of Work
Josefine Vilsbøll Sundgaard operates within the domain of **computer science**, the study of computation. Her specific field of work focuses on **machine learning**, defined as the scientific study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions.

Within this domain, she specializes in **deep learning**, a distinct branch of machine learning. Her professional identity is anchored in these technical disciplines, which serve as the foundation for her research activities.

### Professional Affiliations
She maintains two primary professional affiliations based on available data:
*   **DTU Compute:** Her primary employer and institutional base.
*   **Danish Data Science Academy (DDSA):** She is listed as part of the organization's cross-academy collaboration sub-commititee, a role verified by DDSA records in November 2023.

### Academic Identifiers
Her research output and academic presence are tracked through several standardized identifiers:
*   **ORCiD ID:** 0000-0003-2872-4660
*   **DBLP Author ID:** 269/9949
*   **Google Scholar Author ID:** gFkcjsQAAAAJ
*   **Google Knowledge Graph ID:** /g/11l6vt0ly2

## References

1. [Source](https://ddsa.dk/organization/cross-academy-collaboration-sub-committee/)