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Anum Afzal

Last modified by Anum Afzal Nov 23

Faculty of Informatics
Chair of Informatics 19
Software Engineering for Business Information Systems (sebis)    

Technical University of Munich
Boltzmannstraße 3
85748 Garching, Germany

 

anum.afzal [at] tum.de

Room FMI 01.12.055

Office hours: by appointment

  

 

 

I do not supervise industry thesis.

Open Positions:

Open topics for Guided Research / Thesis:

I have an open master thesis position in the area of domain-specific text summarization using LLMs. If you are interested, please send me your CV and transcript of records to anum.afzal(at)tum.de with subject "Master thesis position domain-specific summarization

Good to have: NLP/ML background, experience with LLM, Python, experience with huggingface, pyTorch, etc

Curriculum Vitae

Anum is Ph.D. candidate at the Technical University of Munich with a focus on topics such as Efficient Transformers and Domain Adaptation for Natural Language Generation. She has been a researcher at the chair for Software Engineering of Business Information Systems (sebis) at the Technical University of Munich (TUM) since September 2021. She holds a master's degree in Computer Science from TUM and wrote her master thesis about Topic Modeling for Employee Objectives using Word Embeddings with Merck Group.

Additionally, She is also a part of the Industry on Campus initiative and support SAP @ TUM Collaboration Lab. Apart from the theoretical research, she works with the industry partners such as SAP and Holtzbrink Publishing Group. She has also worked as a research assistant at chair of Information systems at TUM and also did a student internship at Munich Re during her Master's.

Her research intesrests include but are not limited to applications of Text Generation in Natural Language Processing. At Sebis, she is further responsible for setting up the SAP/TUM collaboration and also works with SAP on research project(s) as a part of her PhD. She also works with Holtzbrinck Publishing Group on a Domain-specifc Text Summarization project.

 

Research Interests

  • Natural Language Processing: Text Summarization, Domain-Adaptation, Efficient Transformers, Parameter-efficient fine-tuning, Conversational AI, chatbots, Text Generation, Natural Language Generation Evaluation, Efficient NLP, Knowledge Injection.
  • Computer Vision: Image segmentation/classification, biomedical Imaging, Remote Sensing 
  • Multi-modal Learning

 

Research Projects

                                         
 

Applications of Text Generation through Semi-supervised learning and beyond

The project explores semi-supervised learning frameworks with applications of text generation using deep learning models. This project addresses several research questions, such as the development of an approach for automated labeling of data generated via chatbot interactions, the integration of user feedback for an enhanced learning experience for the chatbot, and the improvement of chatbot responses where only a limited dataset is available for training.  

 

ATESD: Abstractive Text Summarization for Domain-Specific Documents

Large Language Models work quite well with general-purpose data and many tasks in Natural Language Processing. However, they show several limitations when used for a task such as domain-specific abstractive text summarization. This paper identifies three of those limitations as research problems in the context of abstractive text summarization: 1) Quadratic complexity of transformer-based models with respect to the input text length; 2) Model Hallucination, which is a model's ability to generate factually incorrect text; and 3) Domain Shift, which happens when the distribution of the model's training and test corpus is not the same. Along with a discussion of the open research questions, this project addresses these research gaps in the context of Abstractive Text Summariztion.

 
 

 

 

 

Teaching (in reverse chronological order)

Term Level Title Type Role
 SS 23  Master Natural Language Processing - Methods and Applications  Seminar  Organizer
SS 23 Master SEBA Lab Course (NLP) Lab Course Advisor
 WS 22/23  Master  SEBA Lab Course  Lab Course  Advisor
SS 22 Master Natural Language Processing - Methods and Applications Seminar Organizer
SS 22 Master / Bachelor  Conversational AI workshop Certificate Course Organizer
SS 22 Master Software Engineering for Business Applications (SEBA Master) Lab Course Advisor
WS 21/22 Master SEBA Lab Course Lab Course Advisor

 

Publications (in reverse chronological order)