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.

Communities in Repository

Recently Added

  • Impact of Flip-Flop design choices on sustainability for IoT application 
    Khan, Najeeb Mohammad; Grover, Anuj (Advisor) (IIIT-Delhi, 2025-05-14)
    With the rise of semiconductor devices, there has been an exponential increase in their demand. By 2030, approximately 40 billion IoT devices are projected to exist globally. These devices’ design, fabrication, and operation ...
  • Impact of testability on PPAS 
    Horke, Gangaprasad; Grover, Anuj (Advisor) (IIIT-Delhi, 2025-08-21)
    As semiconductor technology advances toward higher integration and functional density, the challenges associated with Design-for-Testability (DFT) have become increasingly significant, particularly in terms of power ...
  • In silico approaches for biomolecule-driven disease diagnosis and therapy 
    Tomer, Ritu; Raghava, Gajendra Pal Singh (Advisor) (IIIT-Delhi, 2025-10)
    Developments in computational biology have facilitated the systematic study of biomolecules including peptides, proteins or nucleic acids. Such advancements have provided disease-oriented research and therapeutic discovery ...
  • Devolopment of PPAS framework to study the impact of design choices on sustainability in "SAR ADC" architectures 
    Farhan, Ahmad; Grover, Anuj (Advisor) (IIIT-Delhi, 2025-05-10)
    Analog-to-Digital Converters (ADCs) are essential components bridging analog inputs with digital processing systems. Among various architectures, Successive Approximation Register (SAR) ADCs are known for their power and ...
  • Balancing content retention in neural style transfer 
    Agrawal, Yash; Abrol, Vinayak (Advisor) (IIIT-Delhi, 2025-05)
    This thesis work focuses on advancements in neural style transfer, a process that enables the blending of content and style features to generate stylized images. It explores feature extraction using two encoders: a VGG19-based ...

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