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

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!

In Progress

  • [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/BT] Understanding user trade-offs in travel decision-making

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

Recent Publications

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

2024

  • [Workshop Paper] [to appear]
    Ashmi Banerjee*, Tunar Mahmudov*, and Wolfgang Wörndl, 2024. Green Destination Recommender: A Web Application to Encourage Responsible City Trip Recommendations. In Adjunct Proceedings of the 32nd ACM Con- ference on User Modeling, Adaptation and Personalization (UMAP Adjunct ’24), July 01–04, 2024, Cagliari, Italy. ACM, New York, NY, USA, 5 pages. https://doi.org/10.1145/3631700.3664909

  • [arXiv preprint]
    Ashmi Banerjee, Tunar Mahmudov, Emil Adler, Fitri Nur Aisyah, Wolfgang Wörndl, 2024. Modeling Sustainable City Trips: Integrating CO2 Emissions, Popularity, and Seasonality into Tourism Recommender SystemsarXiv preprint arXiv:2403.18604 (2024).

  • [arXiv preprint]
    Ashmi Banerjee*, Tunar Mahmudov*, and Wolfgang Wörndl, 2024. A User Interface Study on Sustainable City Trip RecommendationsarXiv preprint arXiv:2405.11243 (2024).

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

Miscellaneous

  • [Since 2023] Organisation Committee, ACM Women in RecSys Chapter
  • [Since 2023] Google Developer Expert (GDE) in ML
  • [Since 2022] Global Ambassador, Google Women Techmakers