Atomic Habits
By James Clear | Rating: 4.5/5
A practical framework for building better systems and making tiny improvements stick.
By James Clear | Rating: 4.5/5
A practical framework for building better systems and making tiny improvements stick.
The IITB Mars Rover Team was founded in 2012 with the goal of understanding the science and engineering behind building a rover for the red planet. The team has grown to be a platform for experimentation and production of rover prototypes, similar to how NASA has produced rovers such as the Pathfinder. The team has its own line of 6 rovers that have been upgraded to become more advanced and robust over time.
Short description of portfolio item number 2 
KJ Sunav Choudhary, Atanu R. Sinha, Sarthak Chakraborty, Sai Shashank, et al.
US Patent App. 2023 / Patent
A patent application on identifying merchandisable moments in livestreams and generating offers.
Recommended citation: Sunav Choudhary, K. J., Sinha, A. R., Chakraborty, S., Shashank, S., et al. (2023). LiveStreaming AI: Merchandisable Moment Identification and Offer Generation. US Patent App. 18/176,114.
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V V Ramtekkar, L Dahiya, N Shah, K Nishimiya, T Kuroki, C Song, A Kim, et al.
ICRA Workshop 2024 / Paper
This paper proposes a method for detecting drivable regions in challenging terrains using RGB-D data. By integrating depth information with semantic segmentation, our approach significantly improves detection accuracy across diverse landscapes. Leveraging the SegFormer architecture, we effectively distinguish drivable from non-drivable areas. Additionally, we introduce a depth-based refinement mechanism to ensure reliable performance in real-world scenarios. Extensive evaluation in both off-road and on-road environments confirms the effectiveness of our approach. Using the SA-1B dataset with grounded SAM, our method achieves precise delineation of road classes during training. Overall, this work advances autonomous navigation systems by providing a comprehensive solution for drivable region detection in complex terrains in real time, even on edge computing devices.
Recommended citation: Ramtekkar, V. V., Dahiya, L., Shah, N., Nishimiya, K., Kuroki, T., Song, C., ... & Jeon, M. H. Robust Depth-Aided Segmentation for Drivable Region Detection in Challenging Environments. In ICRA 2024 Workshop on Resilient Off-road Autonomy.
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L Dahiya, R Bagga
SMM4H 2024 / Paper
This paper presents our work for the Task 5 of the Social Media Mining for Health Applications 2024 Shared Task-Binary classification of English tweets reporting children’s medical disorders. In this paper, we present and compare multiple approaches for automatically classifying tweets from parents based on whether they mention having a child with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), delayed speech, or asthma. We use ensemble of various BERT-based models trained on provided dataset that yields an F1 score of 0.901 on the test data.
Recommended citation: Dahiya, L., & Bagga, R. (2024, August). CogAI@ SMM4H 2024: Leveraging BERT-based Ensemble Models for Classifying Tweets on Developmental Disorders. In Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks (pp. 114-116).
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R Manro, R Mao, L Dahiya, Y Ma, E Cambria
ICFT 2024 / Paper
The cognitive state of a CEO can have a great impact on the company’s operational results and stock market performance. Conventional cognitive analysis often relies on interviews with cognitive scientists or psychologists, which are not readily scalable for big data applications in finance. In this work, we leverage a novel method to analyze the cognitive states of top-tier managers of 14 well-known companies. We analyze the concept mappings from their speeches and metaphorical expressions over 15 years. We also conduct breakdown analysis for the concept mappings, according to the trends of stock prices. We identify four distinct types of stock market performance and illustrate the featured concept mappings associated with each category. These representative concept mappings reflect the cognitive states of CEOs and provide insights into which cognitive states are most likely to correlate with positive stock market performance.
Recommended citation: Manro, R., Mao, R., Dahiya, L., Ma, Y., & Cambria, E. (2024). A cognitive analysis of CEO speeches and their effects on stock markets. In Proceedings of the 5th International Conference on Financial Technology, ICFT, Singapore.
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M Buchner, L Dahiya, S Dorer, V Ramtekkar, K Nishimiya, D Cattaneo, et al.
IROS 2025 / Paper
A graph-consensus approach for robust visual loop closure detection in challenging robotic environments.
Recommended citation: Buchner, M., Dahiya, L., Dorer, S., Ramtekkar, V., Nishimiya, K., Cattaneo, D., et al. (2025). Visual Loop Closure Detection Through Deep Graph Consensus. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
L Dahiya, R Bagga
Journal of Computational Social Science 2026 / Paper
Social media platforms, particularly Reddits r/Epilepsy community, offer a unique perspective into the experiences of individuals with epilepsy (PWE) and their caregivers. This study analyzes 57k posts and 533k comments to explore key themes across demographics such as age, gender, and relationships. Our findings highlight significant discussions on epilepsy-related challenges, including depression (with 39.75% of posts indicating severe symptoms), driving restrictions, workplace concerns, and pregnancy-related issues in women with epilepsy. We introduce a novel engagement metric, F(P), which incorporates post length, sentiment scores, and readability to quantify community interaction. This analysis underscores the importance of integrated care addressing both neurological and mental health challenges faced by PWE. The insights from this study inform strategies for targeted support and awareness interventions.
Recommended citation: Dahiya, L., & Bagga, R. (2026). Digital epidemiology: Leveraging social media for insight into epilepsy and mental health. Journal of Computational Social Science, 9(1), 1.
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Undergraduate Course, Indian Institute of Technology, Bombay, 2021
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Undergraduate course", Carnegie Mellon University, 2026