CV

Education

• Ph.D student at LMU of Munich (LMU), 2022.09-present
• M.Sc. at LMU of Munich (LMU), 2020.04-2022.08
  Master thesis: Zero-shot learning on low-resource languages by cross-lingual retrieval (Examiner: Prof. Dr. Hinrich Schuetze)
• B.A. at Shanghai Jiao Tong University (SJTU), 2015.09-2019.06
  Bachelor thesis: A corpus-based study of metaphors in the football language (Supervisor: Prof. Dr. Honggang Zhang)

Professional Experience

• Member of Supply Chain Innovation Team at Infineon Technogolies AG, 2021.08-2022.03
  Supervised by Hans Ehm
  • Ontology Modeling and linguistic analysis of knowledge graphs in the fields of supply chain and semiconductor.
  • Developed and improved a document retrieval system based on the language model of BERT and the knowledge graph of digital reference.

Teaching Experience

• Exercise part of Advanced Module of Master Program Computational Linguistics, WS 2022/23
  Natural Language Processing and Deep Learning (Prof. Dr. Barbara Plank)
  • Prepared NLP relevant python exercises for the lab.
  • Discussed with professor and partner on the course structure and organization.
  • Evaluated lab assignments and answered questions regarding exercises as well as lectures from students.
    
    
• Exercise part of Basic module of Master Program Computational Linguistics, WS 2021/22
  Formal Language and Finite-State Technologies (Prof. Dr. Klaus U. Schulz)
  • Summarized the theoretical contents of the lecture in the field of lexicon automaton.
  • Taught basic python programming skills and prepared Python exercises for students.
  • Instructed students to implement the algorithms learned from the lecture with Python
  • Built and maintained the course web page: https://www.cip.ifi.lmu.de/~nie/basismodul

Publications

• Ingo Ziegler, Bolei Ma, Ercong Nie, Bernd Bischl, David Rügamer, Benjamin Schubert and Emilio Dorigatti. What cleaves? Is proteasomal cleavage prediction reaching a ceiling? NeurIPS Workshop LMRL. 2022. [paper], [code]

Skills

• Programming languages: Python, C++, familiar with common NLP and machine learning packages and frameworks.
• Natural Languages: Chinese Mandarin (Native), English (Fluent), German(Fluent)
• Tools: LaTex, HTML, Linux, Markdown, Git, PyCharm, Jupyter Notebook etc.