Ashmi Banerjee, M.Sc.

Email: | ashmi.banerjee[at]tum[dot]de |
Office: | 01.05.053 |
Website: | ashmibanerjee.com |
Address:
| TUM School of Computation, Information and Technoloy |
I am a Ph.D. candidate at the Chair of Connected Mobility at the Technical University of Munich (TUM), from where I also obtained my M.Sc. in Informatics in 2019.
Research Interests
- Multistakeholder Recommender Systems
- Human-Computer Interaction
- Data Mining, Information Retrieval
- Machine Learning
- Fairness & Responsible Recommendations
I am working together with Dr. Wolfgang Wörndl.
Teaching
Theses Topics
No theses available at the moment. Please check again later!
When applying for a topic please follow the guidelines from here.
Legend: [BT] = Bachelor Thesis; [MT] = Master Thesis; [GR] = Guided Research; [AP] = Application Project
Open Topics:
No theses available at the moment. Please check again later!
Other theses and research topics are listed here.
Completed:
- [MT]: Explaining Fairness in Multi-stakeholder Recommender Systems for Tourism
- [BT]: User Interfaces for Combining Multiple Items in Tourism Recommender Systems
In Progress:
- [MT]: An analysis of long-distance train delays and impacted stations in Germany
- [BT]: Exploring Data-Driven Approaches for Train Delay Prediction using Multivariate Models and Machine Learning Techniques
- [GR]: Multi-objective Optimization for Fairness in Tourism Recommender Systems
- [MT]: Exploring Substitution Recommendations: A Literature Review and Analysis
- [BT/MT]: Design and Development of a Web Frontend for Sustainable Hike Recommendations
- [BT]: Analyzing Mobility Trends for Travel Behavior, Preferences, and Sustainability Concerns
- [MT]: User Traits and Responsible Travel Decision Making in Recommender Systems
- [MT]: Evaluating User Decision-Making in Responsible Tourism: A Green Destination Recommender
Recent Publications
An updated list of publications can be found on Google Scholar.
2023
- [Workshop Position Paper]
Ashmi Banerjee, Paromita Banik, and Wolfgang Wörndl, 2023. Towards Individual and Multistakeholder Fairness in Tourism Recommender Systems. In Proceedings of the 6th FAccTRec Workshop on Responsible Recommendation (FAccTRec `23) co-located with the 16th ACM Conference on Recommender Systems (RecSys), September 18-22, 2023, Singapore. ACM, New York, NY, USA.
PDF | BibTeX
- [Workshop Paper]
Paromita Banik, Ashmi Banerjee, and Wolfgang Wörndl. 2023. Understanding User Perspectives on Sustainability and Fairness in Tourism Recommender Systems. In UMAP ’23 Adjunct: Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’23 Adjunct), June 26–29, 2023, Limassol, Cyprus. ACM, New York, NY, USA, 8 pages.
PDF | BibTeX
- [Doctoral Consortium]
Ashmi Banerjee. 2023. Fairness and Sustainability in Multistakeholder Tourism Recommender Systems. In UMAP ’23: Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’23), June 26–29, 2023, Limassol, Cyprus. ACM, New York, NY, USA, 6 pages.
PDF | BibTeX
- [Journal Paper]
Banerjee, A., Banik, P., & Wörndl, W. A Review on Individual and Multistakeholder Fairness in Tourism Recommender Systems. Frontiers in Big Data, 6.
PDF | BibTeX
2020
-
[Workshop Paper]
Ashmi Banerjee, Gourab K Patro, Linus W. Dietz, Abhijnan Chakraborty, Analyzing ‘Near Me’ Services: Potential for Exposure Bias in Location-based Retrieval, International Workshop on Fair and Interpretable Learning Algorithms (FILA 2020) in conjunction with the IEEE International Conference on Big Data (IEEE BigData 2020)
PDF | BibTeX -
[Conference Paper]
Gourab K Patro, Abhijnan Chakraborty, Ashmi Banerjee, Niloy Ganguly, Towards Sustainability and Safety: Designing Local Recommendations for Post-pandemic World, 14th ACM Conference on Recommender Systems (RecSys 2020)
PDF | BibTeX
Miscellaneous
- [Since 2023] Organisation Committee, ACM Women in RecSys Chapter
- [Since 2023] Machine Learning GDE, Google Developer Expert
- [Since 2022] Global Ambassador, Google Women Techmakers