e - Sahyatri: AI- Based Personalized Travel Companion - Professor Mukesh Mohania
Event description
e-Sahyatri: AI-Based Personalized Travel Companion
2025 UTS FEIT Research Excellence Lecture Series - Guest Lecture
Abstract
Awareness of dynamically evolving user preferences, events, and points of interest (POIs)—along with their contextual relevance—is essential for curating immersive tourist experiences and enhancing trip planning. E-travel platforms, technologies, and tools have become indispensable for tourists seeking personalized travel planning. As a result, innovative solutions have emerged to help travelers enjoy more tailored and meaningful journeys.
However, despite efforts to define the tourism domain in a standardized manner, existing systems often fall short in simultaneously capturing the multifaceted dimensions of POIs. This limits their ability to:
Provide a nuanced understanding of the POI ecosystem for route classification and en-route storytelling,
Design context-aware, user preference-driven recommendation systems, and
Develop strategic indexing schemes across the domain's conceptual landscape.
To address these challenges, we propose e-Sahyatri (translation: e-companion), a cognitive computing and social sensing-based navigation system designed to deliver highly personalized tourist experiences. We present the architecture of the e-Sahyatri system through illustrative scenarios that demonstrate its built-in storytelling capabilities—educating users about the rich history, culture, heritage, and trivia associated with nearby events and POIs.
Additionally, we introduce a transformer-based model for route classification and storytelling generation. To support efficient and context-aware retrieval of touristic information at varying spatial granularities, we propose a novel spatial index structure: the PCR-tree (Personalized and Contextual R-tree).
Speaker Biography
Mukesh Mohania joined IIIT Delhi as a Professor in November 2019 and is currently a member of the National Statistical Commission, India. He served as the Dean of Innovation, Research, and Development at IIIT Delhi from July 2020 to June 2023. Prior to joining IIIT Delhi, he held senior technical roles at IBM Research in both India and Australia, including serving as Chief Architect of IBM Watson Education.
His work focuses on AI for Education, integration of structured and unstructured data, and the development of complex systems and applications—particularly in the education and financial sectors. Throughout his career, he has led numerous successful projects that have resulted in widely adopted technologies and products, as well as influential, frequently cited research and patents.
Dr. Mohania holds over 60 granted patents and has published more than 120 technical papers in international conferences. He is an active participant in industry forums and has received several prestigious recognitions from IBM, including:
IBM Distinguished Engineer (2013)
Master Inventor (2009)
Member of the IBM Academy of Technology (2010)
Best of IBM (2014)
He has also received multiple IBM corporate and research awards, such as "Excellence in People Management," "Outstanding Innovation Award," "Technical Accomplishment Award," and "Leadership by Doing."
He is the founding Project Director of the DST-sponsored Technology Innovation Hub (TIH) on Cognitive Computing and Social Sensing at IIIT Delhi, which received ₹100 crore (approx. USD 12 million) in funding for 2021–2025. Additionally, he has secured over USD 500,000 in funding from private sector partners since 2021.
Dr. Mohania has held several prominent positions, including:
ACM Distinguished Scientist (since 2011)
DASFAA Industrial Track Co-chair (2024)
VLDB Conference Organizing Chair (2016)
DASFAA General Co-chair (2022)
ER PC Co-chair (2022)
ACM India Vice-President (2015–2017)
Chair, ACM Distinguished Service Award Committee (2017–2018)
He also serves as an adjunct professor and member of industrial R&D boards at leading universities in India and Australia. His contributions have been recognized with the IEEE Meritorious Service Award and the ACM Outstanding Service Award.
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