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: Hands-on Recommender Systems
Lab Course: Projects in Recommender Systems
- Summer 2025
Master Seminar: Topics in Recommender Systems
- Winter 2023-24
- Winter 2022-23

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

Got a thesis topic in mind that aligns with my research? Let me know!
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!

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
[MT] Nudging Towards Responsible Tourism using an LLM-Based Multi-Aspect Conversational Recommender System
[MT] Towards Sustainable and Diverse City Trips: Leveraging Large Language Models to Address Data Scarcity and Popularity Bias in Tourism Recommender Systems

Recent Publications

An updated list of publications can be found on Google Scholar.

2025

[Conference Tutorial]
A Tutorial on Recent Advances in Generative Conversational Recommender Systems.
Kolb, Thomas Elmar, Ahmadou Wagne, Ashmi Banerjee, Fatemeh Nazary, Julia Neidhardt, Yashar Deldjoo, and Tommaso Di Noia. In Proceedings of the Nineteenth ACM Conference on Recommender Systems (RecSys), pp. 1420-1422. 2025.
[arxiv preprint]
Collab-REC: An LLM-based Agentic Framework for Balancing Recommendations in Tourism
Ashmi Banerjee, Fitri Nur Aisyah, Adithi Satish, Wolfgang Wörndl, and Yashar Deldjoo, 2025. arXiv preprint arXiv:2508.15030 (2025)
[Workshop Paper]
[to appear] Evaluating User Intent Classification and Hybrid Retrieval in a RAG-based Conversational Tourism Recommender System
Akshat Tandon, Ashmi Banerjee, RecTour Workshop 2025, co-located with ACM RecSys conference, September 2025, Prague.
[Conference Paper]
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 Retrieva , 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.

Miscellaneous

Workshop Organizer: LLM4Good Workshop at UMAP 2025, RS4SD Workshop at CIKM'2025
Reviewing:
- ACM RecSys Workshops (FaccTRec 2024, RecSoGood 2024, 2025),
- RecSys LBRs,
- Journals: Springer Journal in Information Technology & Tourism (JITT), Knowledge and Information Systems (KnoSys)
[Since 2023] Organisation Committee, ACM Women in RecSys Chapter
[Since 2023] Google Developer Expert (GDE) in ML
[Since 2022] Global Ambassador, Google Women Techmakers