# Sepp Hochreiter

> German computer scientist

**Wikidata**: [Q7451965](https://www.wikidata.org/wiki/Q7451965)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Sepp_Hochreiter)  
**Source**: https://4ort.xyz/entity/sepp-hochreiter

## Summary

Sepp Hochreiter, born February 14, 1967, in Mühldorf am Inn [1], is a researcher in machine learning and bioinformatics . He studied at the Technical University of Munich, Munich University of Applied Sciences, FernUniversität in Hagen, and later returned to the Technical University of Munich . His career includes positions at Allianz SE from 1992 to 1994, the Technical University of Munich, and Johannes Kepler University Linz, where he has worked since 2006 [2].Hochreiter has received notable recognition, including the German AI Award and the Wilhelm Exner Medal [3][4][5]. He is affiliated with several prestigious institutions, serving as a member of the European Laboratory for Learning and Intelligent Systems, the Austrian Academy of Sciences, and the German Academy of Sciences Leopoldina [6][7][8].

## Summary  
Sepp Hochreiter is a German computer scientist and bioinformatician best known for co‑inventing the long short‑term memory (LSTM) recurrent neural network architecture, a cornerstone of modern deep‑learning systems. He leads the Machine Learning department at Johannes Kepler University Linz and has received major honors such as the German AI Award (2023) and the Wilhelm Exner Medal (2025).

## Biography  
- **Born:** 14 February 1967, Mühldorf am Inn, Germany  
- **Nationality:** German  
- **Education:**  
  - Technical University of Munich (1986 – 1991, Ph.D. completed 1999) – doctoral advisor Wilfried Brauer  
  - Munich University of Applied Sciences (1985 – 1986)  
  - FernUniversität in Hagen (dates not specified)  
- **Known for:** Development of the long short‑term memory (LSTM) neural network architecture  
- **Employer(s):**  
  - Johannes Kepler University Linz – Head of Department (since 1 Feb 2006)  
  - Technical University of Munich (former faculty)  
  - Allianz SE (1992 – 1994)  
- **Field(s):** Machine learning, bioinformatics  

## Contributions  
Sepp Hochreiter’s most influential contribution is the invention of the long short‑term memory (LSTM) recurrent neural network architecture, which addressed the vanishing‑gradient problem that limited earlier recurrent models. The LSTM design enables networks to learn long‑range dependencies in sequential data and has become a standard component in speech recognition, language translation, time‑series forecasting, and many other AI applications. Beyond LSTM, Hochreiter has authored numerous high‑impact papers in machine learning and bioinformatics, advancing methods for sequence analysis, deep‑learning optimisation, and neural network regularisation. His research has been widely cited and incorporated into open‑source deep‑learning frameworks, influencing both academic research and industry products. As head of the Machine Learning department at Johannes Kepler University Linz, he mentors a new generation of researchers and steers collaborative projects across Europe, further extending the reach of his foundational work.

## FAQs  
### Q: What is Sepp Hochreiter most famous for?  
A: He co‑invented the long short‑term memory (LSTM) recurrent neural network architecture, which is fundamental to modern deep‑learning systems.  

### Q: Where does Sepp Hochreiter work today?  
A: He is the head of the Machine Learning department at Johannes Kepler University Linz in Austria.  

### Q: Which major awards has he received?  
A: Hochreiter received the German AI Award in 2023 and the Wilhelm Exner Medal in 2025 for his contributions to artificial intelligence.  

### Q: What are his research areas?  
A: His work spans machine learning—especially neural network architectures—and bioinformatics, focusing on computational methods for biological data.  

### Q: Is he a member of any academies?  
A: Yes, he became a member of the Austrian Academy of Sciences in 2024 and the German Academy of Sciences Leopoldina in 2025.  

## Why They Matter  
The LSTM architecture introduced by Hochreiter transformed the capabilities of recurrent neural networks, making it possible to train models that retain information over long sequences. This breakthrough unlocked practical deep‑learning solutions for natural‑language processing, speech recognition, and time‑series analysis, fields that now underpin many everyday technologies such as virtual assistants and translation services. Hochreiter’s work also bridged computer science and biology, applying deep‑learning techniques to bioinformatics challenges and accelerating discoveries in genomics and proteomics. By leading a prominent research department and mentoring scholars, he continues to shape the direction of AI research across Europe, ensuring that his innovations remain at the core of both academic inquiry and commercial development.

## Notable For  
- Co‑inventor of the long short‑term memory (LSTM) neural network architecture.  
- Recipient of the German AI Award (2023).  
- Awarded the Wilhelm Exner Medal (2025).  
- Head of the Machine Learning department at Johannes Kepler University Linz since 2006.  
- Elected member of the Austrian Academy of Sciences (2024) and the German Academy of Sciences Leopoldina (2025).  

## Body  

### Early Life and Education  
- Born in Mühldorf am Inn, Germany, on 14 Feb 1967.  
- Studied at the Munich University of Applied Sciences (1985‑86) before enrolling at the Technical University of Munich (TUM), where he earned his diploma (1986‑91) and later his Ph.D. (1994‑99).  
- Doctoral research was supervised by renowned computer scientist Wilfried Brauer.  

### Academic Career  
- Held a faculty position at the Technical University of Munich, contributing to both teaching and research.  
- Joined Allianz SE as a researcher (1992‑94) before returning to academia.  
- Appointed head of the Machine Learning department at Johannes Kepler University Linz on 1 Feb 2006, where he oversees research groups in deep learning and bioinformatics.  

### Research Contributions  
- **LSTM Architecture:** Introduced a recurrent neural network capable of learning long‑range dependencies, solving the vanishing‑gradient problem.  
- **Machine‑Learning Publications:** Authored seminal papers on neural‑network regularisation, optimisation, and sequence modelling, widely cited in AI literature.  
- **Bioinformatics Applications:** Developed computational methods for analyzing genomic and proteomic data, integrating deep‑learning techniques into biological research.  

### Honors and Memberships  
- Awarded the German AI Award (2023) for outstanding contributions to artificial intelligence.  
- Received the Wilhelm Exner Medal (2025), recognising innovative scientific achievements.  
- Elected to the European Laboratory for Learning and Intelligent Systems, the Austrian Academy of Sciences (2024), and the German Academy of Sciences Leopoldina (2025).  

### Influence and Legacy  
- LSTM has become a standard component in major deep‑learning frameworks (e.g., TensorFlow, PyTorch).  
- His mentorship has produced a generation of AI researchers active in both academia and industry.  
- Ongoing collaborations across European institutions continue to expand the impact of his work on AI and computational biology.  

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## References

1. Mathematics Genealogy Project
2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7449-2528/employment/10092200)
3. [Source](https://www.tips.at/nachrichten/linz/land-leute/620497-spitzenforscher-sepp-hochreiter-mit-deutschem-ki-innovationspreis-ausgezeichnet)
4. [Source](https://science.apa.at/power-search/17839077489851839612)
5. [Source](https://www.sn.at/panorama/wissen/sepp-hochreiter-wilhelm-exner-medaille-186487549)
6. [Source](https://ellis.eu/members)
7. [Source](https://www.ots.at/presseaussendung/OTS_20240415_OTS0023/oeaw-waehlt-34-neue-mitglieder)
8. [Source](https://www.leopoldina.org/mitgliederverzeichnis/mitglieder/member/Member/show/sepp-hochreiter/)
9. [Source](https://www.leopoldina.org/fileadmin/redaktion/Mitglieder/CV_Hochreiter_Sepp_D.pdf)
10. Virtual International Authority File