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  • Adapting vehicular planning and communications for optimized driving 
    Pal, Mayank Kumar (IIIT-Delhi, 2020-07)
    Connected Autonomous Vehicles (CAVs) have for long had the attention of the intelligent transportation systems community due to their promise of improving road safety and efficiency via increased perception. CAVs broadly ...
  • Adaptive algorithms for control of robots 
    Natarajan, Ashwin Ram; Roy, Sayan Basu (Advisor) (IIIT-Delhi, 2023-11-29)
    Adaptive control is essential for the successful operation of robots in unknown environments. Existing literature involves the use of mathematical assumptions and regression techniques for estimation. This BTP develops an ...
  • Adaptive algorithms for control of robots 
    Natarajan, Ashwin Ram; Roy, Sayan Basu (Advisor) (IIIT-Delhi, 2024-04-29)
    Adaptive control is essential for the successful operation of robots in unknown environments. Existing literature involves the use of mathematical assumptions and regression techniques for estimation. This BTP develops an ...
  • Adaptive biomedical knowledge graph querying: orchestrating multi-agent AI for complex data retrieval 
    Kharkwal, Rahul; Sengupta, Debarka (Advisor) (IIIT-Delhi, 2025-08-20)
    This thesis explores the development and evaluation of a smart, multi-agent system designed to retrieve information efficiently from a diverse biomedical knowledge graph. The graph was carefully built using BioKG data in ...
  • Adaptive concurrency throttling in the exascale era 
    Gupta, Raghav; Kumar, Vivek (Advisor) (IIIT-Delhi, 2022-05)
    Future multi-core processors will be heterogeneous, be increasingly less reliable, and operate in dynamically changing operating conditions. Such environments will result in a constantly varying pool of hardware resources ...
  • Addressing coldstart problem in recommender systems 
    Banerjee, Shisagnee; Majumdar, Angshul (Advisor) (2016-09-15)
    In the following three chapters of my thesis, I have applied several methods to solve the coldstart problem in Recommender Systems. The coldstart problem is the situation where a user or item is new to a website and ...
  • Advancing CNS tumor diagnosis: deep learning applications in histopathology of H&E-stained images 
    Deepak, Maganti; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2024-11-27)
    Deep learning has become a pivotal tool in computational pathology, particularly for classifying CNS tumors in histopathology images stained with hematoxylin and eosin (H&E). This study evaluates the performance of the ...
  • Advancing gene signature discovery with generative models : a case study in sepsis 
    Sharma, Anjali; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2023-05-01)
    Sepsis and diabetes present intricate medical conditions that present substantial challenges to healthcare systems globally. Timely detection and precise diagnosis are critical in facilitating effective treatment and ...
  • Advancing gene signature discovery with generative models: a case study ovarian cancer 
    Anand, Alok; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2025-06)
    Ovarian cancer is a highly aggressive malignancy with poor survival rates, largely due to late detection and extensive tumor heterogeneity. This study introduces a computational framework, NIGAM (Normalize, Identify, ...
  • Advancing graph-based computational approaches to decipher omic signature of diseases 
    Mishra, Shreya; Kumar, Vibhor (Advisor) (IIIT-Delhi, 2022-10-31)
    Omic signatures of disease are important for personalized treatment because of theheterogeneity of diseases. Despite the advancement of computational tools, there arelimited methods that can capture the latent inter-relationships ...
  • Advancing text summarization with conscience, comprehension, and multimodality 
    Kumar, Yash; Goyal, Vikram (Advisor); Chakraborty, Tanmoy (Advisor) (IIIT-Delhi, 2024-01)
    Summarization, an essential technique for efficiently condensing extensive textual content into concise versions, has become increasingly valuable in the face of the information deluge characterizing the modern digital ...
  • Adversarial network mining 
    Sharma, Ansh Kumar; Kukreja, Rahul; Chakraborty, Tanmoy (Advisor) (IIIT-Delhi, 2021-12)
    Recent advancements in the field of graph representation learning and the introduction of algorithms like DeepWalk, LINE and Graph Convolutional Networks (GCNs) have helped achieve state-of-the-art results for tasks like ...
  • Adversary detection tool 
    Goel, Akhil; Singh, Anirudh; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (IIITD-Delhi, 2019-04-30)
    Extensive research on attacks on deep learning models has shown that these models are not as robust as they seem. A carefully designed low magnitude perturbation is enough to cause havoc and completely confuse the model. ...
  • Advertisement generator startup 
    Garg, Nitesh; Grover, Anuj (Advisor) (IIIT-Delhi, 2024-11-27)
    This report outlines the development of a startup aimed at addressing advertising challenges faced by small-to-medium scale enterprises (SMEs) through innovative, AI-driven solutions. Initially focused on enabling users ...
  • Advertisement understanding 
    Garikaparthi, Aniketh; Shah, Rajiv Ratn (Advisor) (IIIT-Delhi, 2023-11-29)
    In the contemporary landscape of marketing, online video advertisements have emerged as a potent force, wielding the ability to captivate audiences and mold consumer behavior. This research delves into the intricate realm ...
  • Aerial pedestrian detection using vision based approach 
    Chaudhuri, Yashwardhan; Buduru, Arun Balaji (Advisor) (IIIT-Delhi, 2022-12)
    Aerial object detection is becoming increasingly popular since images with a large field of view provide higher information per pixel than images with a short field of view. It is popularly used for pedestrian detection ...
  • Affective analysis 
    Madan, Sanya; Akhtar, Md. Shad (Advisor) (IIIT-Delhi, 2023-11-29)
    The aim of this work was focused on data collection and annotation for Aspect-Based Academic Review Analysis. The goal is to understand the sentiments expressed in course feedback regarding different aspects of a course. ...
  • AgAnt : a computational tool to assess the mode of interaction between a protein-ligand complex 
    Choudhary, Bhumika; Ray, Arjun (Advisor) (IIIT-Delhi, 2024-08)
    Protein-ligand interactions are fundamental in regulating protein activity within cellular environments, playing a pivotal role in numerous biochemical processes. These interaction studies are important for understanding ...
  • AI based NLP systems 
    Nair, Ashwin R; Shah, Rajiv Ratn (Advisor) (IIIT-Delhi, 2023-11-29)
    Citation Text Generation (CTG) is the task of generating the text that explains the relationship between a pair of scientific documents. Given the context of a source paper (citing paper) X and a cited paper Y, the task ...
  • AI based NLP systems 
    Addala, Krishnasai; Baghel, Kabir Dev Paul; Shah, Rajiv Ratn (Advisor) (IIIT-Delhi, 2023-11-27)
    Despite the growing capabilities of Large Language Models (LLMs) in various domains, their proficiency in addressing domain-specific high-school physics questions remains an unexplored area. In this study, we present a ...