PhD Theses

Recent Submissions

  • Goyal, Nidhi; Kumaraguru, Ponnurangam (Advisor); Mutharaju, V. Raghava (Advisor); Sachdeva, Niharika (Advisor) (IIIT Delhi, 2024-09)
    Online professional platforms such as Indeed, LinkedIn, Naukri, Stack Overflow, and Blind serve as digital ecosystems to connect professionals, employers, and job seekers. These platforms witness online user activities, ...
  • Singhal, Shivangi; Shah, Rajiv Ratn (Advisor); Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2023-06)
    Fake news refers to intentionally and verifiably false stories created to manipulate people’s perceptions of reality. Fake news is destructive and has been used to influence voting decisions and spread hatred against ...
  • Hitkul; Shah, Rajiv Ratn (Advisor); Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2024-03)
    Do online interactions trigger reactions back in the offline world? How can these reactions be detected and quantified? Specifically, what insights can be extracted for users, platform owners, and policymakers to minimize ...
  • Majumdar, Puspita; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (IIIT-Delhi, 2024-06)
    The remarkable achievements and the robust performance of deep models have been instrumental in the evolution of facial analysis systems. Employed across a wide array of applications, these systems assist in making crucial ...
  • Mehrotra, Nikita; Purandare, Rahul (Advisor) (IIIT-Delhi, 2024-06)
    Code clones, duplicate code fragments sharing similar syntax or semantics, have become increasingly prevalent due to the success of software management tools like GitHub and advancements in Open Source Software (OSS). ...
  • B, Ashwini; Shukla, Jainendra (Advisor) (IIIT-Delhi, 2024-03)
    The diagnostic process for Autism Spectrum Disorder (ASD) is complex,requiring extensive expertise to integrate information from diverse sourcessuch as parental reports and clinical observations. However, limited accessto ...
  • 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 ...
  • Keshari, Rohit; Singh, Richa (Advisor); Vatsa, Mayank (Advisor) (IIIT-Delhi, 2024-03)
    Deep Neural Networks (DNNs) have achieved remarkable success across various machine learning and computer vision tasks, especially when abundant training samples are available. In Convolutional Neural Network (CNN) research, ...
  • Neha, Kumari; Buduru, Arun Balaji (Advisor); Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2024-02)
    Protests (or movements) are a form of collective sociopolitical action in which mem- bers with similar beliefs express their objections to a cause or situation. Often, a heated debate during protests on social media, such ...
  • Kumar, Shivani; Chakraborty, Tanmoy (Advisor) (IIIT-Delhi, 2024-03)
    In the past decade, Natural Language Processing has undergone a transformative journey, marked by profound changes. The realm of conversational discourse, in particular, has witnessed remarkable advancements, with contemporary ...
  • Malhotra, Aakarsh; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (IIIT-Delhi, 2024-01)
    Attributed to extensive acceptance and research, lives can and inked fingerprints are successfully used for human recognition. However, applications such as contactless biometrics amidst the pandemic and crime scene ...
  • Goswami, Chitrita; Sengupta, Debarka (Advisor) (IIIT-Delhi, 2023-02)
    In an era where machine learning (ML) is changing the landscape of financial markets, education, security and privacy, the retail sector, and many other crucial aspects of human life, it is only fitting that we should use ...
  • Baride, Srikanth; Goyal, Vikram (Advisor) (IIIT-Delhi, 2023-12)
    Spatial data mining is a specialized field that focuses on extracting meaningful insights and patterns from geographical or spatial data. One particular area of interest in spatial data mining is colocation pattern mining. ...
  • Goel, Anurag; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2023-11)
    The traditional way of clustering is first extracting the feature vectors according to domain-specific knowledge and then employing a clustering algorithm on the extracted features. Deep learning approaches attempt to ...
  • Ghosh, Soumyadeep; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (IIIT-Delhi, 2023-03)
    Face recognition under controlled and constrained scenarios have reached a significant level of maturity with respect to performance and reliability. However, under unconstrained and un controlled settings, current ...
  • Gupta, Pooja; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2023-09)
    There are many real-world problems pertaining to the need for the fusion of information from multiple sources. Consider, for example, the problem of demand forecasting that requires estimating the power consumption at a ...
  • Biswas, Koushik; Pandey, Ashish Kumar (Advisor); Banerjee, Shilpak (Advisor) (IIIT-Delhi, 2023-07)
    Artificial neural networks (ANNs) have occupied the centre stage in deep learning. An activation function is a crucial component in the neural network, which introduces the non-linearity in the network. An activation ...
  • V, Venktesh; Mohania, Mukesh (Advisor); Goyal, Vikram (Advisor) (IIIT-Delhi, 2023-03)
    Education in traditional classroom settings was restricted to static content in textbooks. It also assumes all the learners have a similar pace of learning. Online learning platforms have shifted the paradigm and have made ...
  • Nagar, Pravin; Arora, Chetan (Advisor) (IIIT-Delhi, 2023-02)
    Egocentric videos are recorded in a hands-free, always-on, under enhanced privacy-sensitive scenario and are often collected from day to weeks. For efficient consumption, such videos require robust video analysis techniques ...
  • Jain, Monika; Subramanyam, A V (Advisor) (IIIT-Delhi, 2022-06)
    Correlation Filter based visual trackers have demonstrated tremendous progress in object tracking. These trackers primarily use hierarchical features learned from multiple layers of a deep network. However, issues related ...

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