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Tim Schopf

Department of Computer Science
Chair of Software Engineering for Business Information Systems (sebis)    

Technische Universität München 
Boltzmannstraße 3
85748 Garching bei München, Germany

Phone:  +49 89 289-17105
Fax: +49 89 289-17136
Email: tim.schopf@tum.de

 

Room FMI 01.12.057 

Office hours: by appointment 

 

   timschopf.github.io
  ORCID iD icon 0000-0003-3849-0394 
   @tim.schopf
TimSchopf

 

Student offers:

  • At the moment, unfortunately, I do not have additional capacity for thesis supervision.

Open HiWi Position

  • Currently, I have no open Hiwi positions

Curriculum Vitae

Mr. Schopf joined the chair of Software Engineering for Business Information Systems at the Technical University of Munich in September 2020. He holds a master's degree in Information Engineering and Management from Karlsruhe Institute of Technology and wrote his master's thesis at MHP - A Porsche Company about defending adversarial attacks on deep neural networks for autonomous driving by randomization and anomaly detection. He acquired his bachelor's degree in Information Systems from a joint program of the Universities of Hohenheim and Stuttgart. During his studies he also gained work experience as Data Science Intern at Daimler and as student research assistant at Karlsruhe Institute of Technology. 

 

hackaTUM

As one of the organizers Tim Schopf is responsible for hackaTUM, the official annual TUM hackathon hosted by the Department of Informatics since 2016. Over the last years, it has become one of the biggest hackathons in the EU with over 1700 applications and 900 participants in the last event. 

The next edition of hackaTUM will take place in 2024!
If you are interested in sponsoring the event, contact hackatum.in@tum.de. Further information can be found at https://hack.tum.de

 

Research Interests

  • Natural Language Processing
  • Knowledge Graphs
  • Knowledge Graph Construction 
  • Exploratory Search
  • Ontology Learning 
  • Information Extraction
  • Information Retrieval
  • Knowledge Augmented Language Models

 

Current Research Projects

 

Natural Language Processing Knowledge Graph (NLP-KG)

The NLP knowledge graph is an approach to tackle the information overload challenge of researchers. It aims to help researchers in obtaining an overview of NLP-related topics and find relevant papers more efficiently. More here...

CreateData4AI (CD4AI)

Estimated zettabytes of data are generated every day, with about 80% of this data being unannotated, unstructured text. An as-of-yet unsolved problem with this type of data is how to make it useful for AI applications. Manual annotation of the data can be very precise and incorporate domain-specific knowledge, but it is costly, inefficient, and not scalable. The so-called "80/20 rule" refers to the fact that data scientists often spend up to 80% of their time sorting, cleaning, and otherwise preparing datasets. This project aims to develop a novel hybrid framework that helps domain experts annotate text using Natural Language Processing algorithms, reducing the process to a fraction of the time. More here...

 

Completed Research Projects

 

Technology Scouting as a Service (TSaaS)

Due to the quantity and complexity of data (Big Data), the classical information gathering of engineers, for the search for technologies to solve problems in mechanical and plant engineering, no longer meets the requirements of a modern information society. This project aims to research AI-based processes that offer engineers a completely new possibility to find tailor-made solutions for their problems. For this purpose, natural language processing algorithms will be developed that semantically analyze large amounts of text, extract essential information and transfer it into an information model (knowledge graph) in order to capture and link problems and technologies. By means of matching, solutions for a wide range of problems can then be generated by engineers at the push of a button. More here...

 

Knowledge4Retail (K4R)

The sebis chair is part of the project "Knowledge4Retail", which is a winning project of the "Künstliche Intelligenz als Treiber für volkswirtschaftlich relevante Ökosysteme" programme and thus funded by the Bundesministerium für Wirtschaft und Energie (BMWi). The goal of Knowledge4Retail is to advance the digitization of retail by developing a data platform that enables the combination of online and stationary retail, serves strategic marketing and makes digital solutions available for individual customer service using a semantic digital twin. More here...

 

Research Institution Knowledge Graph (RIKG)

Given that scientific knowledge usually is available in large quantities as unstructured texts, it is very difficult for researchers to obtain an overview of research fields or scientific domains. Similarly, it is difficult for researchers to gain insight into topics being researched at research institutions. Information about conducted research often only exists in unstructured texts on homepages or intranet pages. In addition, the websites are usually designed according to organizational structures of research institutions rather than a logical structure based on research areas. Therefore, a research area based navigation through the instutution websites is hardly possible. This makes exploration and navigation of topics being researched in an institution very difficult for external as well as for internal users. Structuring the scientific knowledge of research institutions and linking semantically related scientific domains offers researchers the potential for enhanced exploration of research areas. More here ...

 

Teaching (in reverse chronological order)

Term Level Title Type Role
WS 23/24 Master IN2106, IN7106SEBA Lab Course Lab Course  Advisor
WS 23/24 Bachelor & Master IN2235Software Engineering in der industriellen Praxis  Lecture Organizer
SS 23 Master IN2106, IN7106SEBA Lab Course (NLP) Lab Course Advisor
SS 23 Master IN2107, IN4816: Natural Language Processing - Methods and Applications  Seminar Advisor
SS 23 Master IN2087Software Engineering for Business Applications - Web Applications Engineering Lab Course Advisor
WS 22/23  Master IN2106, IN7106SEBA Lab Course Lab Course Advisor
WS 22/23  Bachelor & Master IN2235Software Engineering in der industriellen Praxis Lecture Organizer
WS 22/23 Master TUM-DI-LAB Lab Course Advisor
SS 22 Master IN2107, IN4816: Natural Language Processing - Methods and Applications Seminar Advisor
SS 22 Master

IN2087Software Engineering for Business Applications - Web Applications Engineering

Lab Course Advisor
WS 21/22  Master

IN2106, IN7106SEBA Lab Course

Lab Course Advisor 
WS 21/22 Bachelor & Master

IN2235Software Engineering in der industriellen Praxis

Lecture Organizer
SS 21 Master

IN2087Software Engineering for Business Applications - Web Applications Engineering

Lab Course Advisor
WS 20/21 Bachelor & Master IN2235Software Engineering in der industriellen Praxis Lecture Advisor
WS 20/21 Master IN2106, IN7106SEBA Lab Course Lab Course Advisor


Publications (in reverse chronological order)

2023
[PDF]

Schopf, Tim; Machner, Nektarios; Matthes, Florian

A Knowledge Graph Approach for Exploratory Search in Research Institutions, Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KMIS, Rome, Italy, 2023

DOI: 10.5220/0012223800003598

[PDF]  

Schopf, Tim; Arabi, Karim; Matthes, Florian

Exploring the Landscape of Natural Language Processing Research, In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing (RANLP 23), Varna, Bulgaria, 2023

URL: https://aclanthology.org/2023.ranlp-1.111 

[PDF]  

Schopf, Tim; Gerber, Emanuel; Ostendorff, Malte; Matthes, Florian

AspectCSE: Sentence Embeddings for Aspect-based Semantic Textual Similarity using Contrastive Learning and Structured Knowledge, In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing (RANLP 23), Varna, Bulgaria, 2023

URL: https://aclanthology.org/2023.ranlp-1.113 

[PDF]

Schopf, Tim; Schneider, Dennis; Matthes, Florian

Efficient Domain Adaptation of Sentence Embeddings Using Adapters, In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing (RANLP 23), Varna, Bulgaria, 2023

URL: https://aclanthology.org/2023.ranlp-1.112 

[PDF]

Schopf, Tim; Braun, Daniel; Matthes, Florian

Semantic Label Representations with Lbl2Vec: A Similarity-Based Approach for Unsupervised Text Classification, In: Marchiori, M., Domínguez Mayo, F.J., Filipe, J. (eds) Web Information Systems and Technologies. WEBIST WEBIST 2020 2021. Lecture Notes in Business Information Processing, vol 469. Springer, Cham.

DOI: https://doi.org/10.1007/978-3-031-24197-0_4 

2022
[PDF]

Schopf, Tim; Braun, Daniel; Matthes, Florian

Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches, In 2022 6th International Conference on Natural Language Processing and Information Retrieval (NLPIR), Bangkok, Thailand, 2022

DOI: https://doi.org/10.1145/3582768.3582795 

[PDF]

Schopf, Tim; Klimek, Simon; Matthes, Florian

PatternRank: Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction, In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR (IC3K 2022), Valletta, Malta, 2022

DOI: 10.5220/0011546600003335 

[PDF]

Schneider Phillip; Schopf, Tim; Vladika, Juraj; Galkin, Mikhail; Simperl, Elena; Matthes, Florian

A Decade of Knowledge Graphs in Natural Language Processing: A Survey, In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP 2022), Online, 2022

URL: https://aclanthology.org/2022.aacl-main.46 

[PDF]

Schopf, Tim; Dresse, Kilian; Matthes, Florian

Towards AI Platforms for Stationary Retail, 5th International Conference on Artificial Intelligence for Industries (AI4I), Laguna Hills, USA, 2022

DOI: 10.1109/AI4I54798.2022.00012

[PDF]

Schopf, Tim; Weinberger, Peter; Kinkeldei, Thomas; Matthes, Florian

Towards Bilingual Word Embedding Models for Engineering, MSIE 2022, 4th International Conference on Management Science and Industrial Engineering, Chiang Mai, Thailand, 2022

DOI: 10.1145/3535782.3535835

2021

[PDF]

Schopf, Tim; Braun, Daniel; Matthes, Florian

Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics, In Proceedings of the 17th International Conference on Web Information Systems and Technologies, Online, 2021

DOI: 10.5220/0010710300003058

[PDF]

Braun, Daniel; Klymenko, Oleksandra; Schopf, Tim; Akan, Kaan; Matthes, Florian

The Language of Engineering: Training a Domain-Specific Word Embedding Model for Engineering, MSIE 2021: 3rd International Conference on Management Science and Industrial Engineering, Osaka, Japan, 2021

DOI: 10.1145/3460824.3460826