Institutional Repository

This Repository has been created and designed to collect, preserve and disseminate the scholarly intellectual output of Indraprastha Institute of Information Technology - Delhi (IIIT-Delhi). Repositories are important tools for preserving an organization's legacy; they facilitate digital preservation and scholarly communication.

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Recently Added

  • Exploring alias analysis based optimizations missed by the compiler 
    Chitre, Khushboo; Kedia, Piyus (Advisor); Rahul, Purandare (advisor) (IIIT-Delhi, 2026-04)
    Alias analysis is a technique to determine whether a pair of pointers points to overlapping memory locations. Alias information (especially non-overlapping of pointers) is critical for enabling key transformations such as ...
  • Topics in the distribution of farey sequences 
    Bittu; Chaubey, Sneha (Advisor) (IIIT-Delhi, 2026-04)
    In this thesis, we study the distribution of Farey sequences. Let Q be a positive integer. The Farey sequence FQ of order Q is the set of irreducible fractions in [0, 1] whose denominators do not exceed Q. The first study ...
  • Deep learning based electromagnetic field estimation for neural engineering applications 
    Kumar, Vickery; Kumar, Suyash; Surya, Pourav; Kosta, Pragya (Advisor); Sarkar, Shamik (Advisor); Singh, Pushpender (Advisor) (IIIT-Delhi, 2024-12-11)
    Understanding neural activity through stimulation offers significant potential for neuroscience research and clinical applications. However, experimental setups involving magnetic or electrical stimulation, such as those ...
  • ConcurBench: a benchmark framework for evaluating LLM-generated concurrent code 
    Gupta, Kshitij; Chaterjee, Bapi (Advisor) (IIIT-Delhi, 2025-07-17)
    This thesis presents ConcurBench, a novel benchmark framework designed to evaluate the capa- bilities of Large Language Models (LLMs) in generating concurrent code. Concurrent program- ming remains one of the most challenging ...
  • Development of an interactive wall using computer vision 
    Dabas, Ram; Dagar, Kartik; Tejas, Kumar; Shankhwar, Kalpana (Advisor); Ratn, Anoop (Advisor) (IIIT-Delhi, 2024-11-27)
    This report presents the development of an Interactive Wall, a gesture-based drawing application that integrates Computer Vision, Machine Learning, and Unity to enable intuitive interaction with a virtual canvas. Using ...

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