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 Department of Computer Engineering Chair of Connected Mobility (|11) Boltzmannstr. 3 85748 Garching |
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
- Lab Course: Projects in Recommender Systems
- Master Seminar: Topics in Recommender Systems
- Lab Course: Hands-on Recommender Systems
Theses Topics
When applying for a topic please follow the guidelines from here.
The thesis students starter pack for (potential) students supervised by me can be found here.
Legend: [BT]= Bachelor Thesis; [MT] = Master Thesis; [GR] = Guided Research; [AP] = Application Project
No theses available at the moment. Please check again later!
Other theses and research topics are listed here.
Please use your @tum.de or @mytum.de or similar emails for any communication. Otherwise, your emails might end up in spam and never get answered!
In Progress
- [MT] Nudging Towards Responsible Tourism using a Knowledge Graph-Enhanced Conversational Recommender System
- [MT] Leveraging Large Language Models to Enhance Personalization in Conversational Recommender Systems for Tourism
Completed
- [MT] Explaining Fairness in Multi-stakeholder Recommender Systems for Tourism
- [BT] User Interfaces for Combining Multiple Items in Tourism Recommender Systems
- [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] User Traits and Responsible Travel Decision-Making in Recommender Systems
- [MT] Evaluating User Decision-Making in Responsible Tourism: A Green Destination Recommender
- [MT] Exploring Substitution Recommendations: A Literature Review and Analysis
- [BT/MT] Design and Development of a Web Frontend for Sustainable Hike Recommendations
- [GR] Analyzing Responsibility Features in Tourism
- [BT] Analyzing Mobility Trends for Travel Behavior, Preferences, and Sustainability Concerns
- [MT] Dynamic Playlist Generation for Hikers: An Intelligent Recommender System Using Trail Characteristics and Contextual Data
- [GR] Enhancing Sustainable Travel Recommendations Using Retrieval-Augmented Generation
- [MT] Exploring Alternative Travel Destinations: A Metric-Constrained Approach Based on City Interest Profiles
- [BT] Exploring the Applicability and Implications of Large Language Models for Tourism Recommendation
- [MT] Exploring Trade-offs in Travel Planning: Prioritizing Sustainability While Managing Cost and Attractiveness through User-Centric Design
- [MT] Gamification for Sustainable City Trip Planning
- [BT] Balancing Sustainability and Experience: Analyzing User Trade-offs in Digital Trip Planning Tools
- [BT] An Exploration of Hybrid Retrieval Augmented Generation in Conversational Tourism Recommender Systems
- [MT] Balancing Sustainability, Cost, and Appeal in Tourism Recommender Systems: A User-Centric Approach
- [BT] Analyzing the Effects of Visualization Strategies on Sustainable Decision-Making in Tourism Recommender Systems
Recent Publications
An updated list of publications can be found on Google Scholar.
2025
- [Conference Paper: to appear]
SynthTRIPS: A Knowledge-Grounded Framework for Benchmark Query Generation for Personalized Tourism Recommenders
Ashmi Banerjee, Adithi Satish, Fitri Nur Aisyah, Wolfgang Wörndl, and Yashar Deldjoo, Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, July 2025.
- [Journal Paper]
Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity, and Seasonality into Tourism Recommender SystemsAshmi Banerjee, Tunar Mahmudov, Emil Adler, Fitri Nur Aisyah, and Wolfgang Wörndl, Springer Journal in Information Technology and Tourism, January 2025.
2024
- [Workshop Paper]
Enhancing Tourism Recommender Systems for Sustainable City Trips Using Retrieval-Augmented Generation
Ashmi Banerjee, Adithi Satish, Wolfgang Wörndl, Accepted for publication at the 1st International Workshop on Recommender Systems for Sustainability and Social Good (RecSoGood), co-located with ACM RecSys 2024, October 14-18, 2024 Bari, Italy.
- [Workshop Paper]
Green Destination Recommender: A Web Application to Encourage Responsible City Trip Recommendations
Ashmi Banerjee, Tunar Mahmudov, Wolfgang Wörndl, In Proceedings of the 15th Workshop Workshop on Personalized Access to Cultural Heritageco-located with the ACM UMAP 2024 The 32nd ACM Conference on User Modeling, Adaptation and Personalization, July 1-4, 2024, Cagliari, Italy.
- [arXiv preprint]
A User Interface Study on Sustainable City Trip Recommendations.
Ashmi Banerjee*, Tunar Mahmudov*, and Wolfgang Wörndl, 2024. arXiv preprint arXiv:2405.11243 (2024).
2023
- [Workshop Position Paper]
Towards Individual and Multistakeholder Fairness in Tourism Recommender Systems
Ashmi Banerjee, Paromita Banik, Wolfgang Wörndl, 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.
- [Workshop Paper]
Understanding User Perspectives on Sustainability and Fairness in Tourism Recommender Systems
Paromita Banik, Ashmi Banerjee, Wolfgang Wörndl, UMAP'23 Adjunct: Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (UMAP'23), Limassol, Cyprus, June 2023
- [Doctoral Consortium]
Fairness and Sustainability in Multistakeholder Tourism Recommender Systems
Ashmi Banerjee, Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (UMAP'23), Limassol, Cyprus, June 2023
- [Journal Paper]
A Review on Individual and Multistakeholder Fairness in Tourism Recommender Systems,
Ashmi Banerjee, Paromita Banik, Wolfgang Wörndl, Frontiers in Big Data, Volume 6, pages 41 doi: 10.3389/fdata.2023.1168692
2020
- [Workshop Paper]
Analyzing ‘Near Me’ Services: Potential for Exposure Bias in Location-based Retrieval
Ashmi Banerjee, Gourab K Patro, Linus W. Dietz, Abhijnan Chakraborty, International Workshop on Fair and Interpretable Learning Algorithms (FILA 2020) in conjunction with the IEEE International Conference on Big Data (IEEE BigData 2020)
- [Conference Paper]
Towards Sustainability and Safety: Designing Local Recommendations for Post-pandemic World
Gourab K Patro, Abhijnan Chakraborty, Ashmi Banerjee, Niloy Ganguly, 14th ACM Conference on Recommender Systems (RecSys 2020)
Miscellaneous
- [Since 2023] Google Developer Expert (GDE) in ML
- [Since 2023] Organisation Committee, ACM Women in RecSys Chapter
- [Since 2022] Global Ambassador, Google Women Techmakers