Computer Science and Engineering: Recent submissions

  • Building performant, privacy-enhancing, and blocking-resistant communication systems 
    Kumar, Piyush; Chakravarty, Sambuddho (Advisor); Maity, Mukulika (Advisor) (IIIT- Delhi, 2021-08)
    Free and open communication over the Internet is essential for the overall advancement of modern societies. However, there are numerous ways with which malevolent adversaries try to control the flow of information, by ...
  • Leveraging the external resources and meta-data to highlight the gap between a programs’s implementation and its documentation 
    Sondhi, Devika; Purandare, Rahul (Advisor) (IIIT- Delhi, 2021-06)
    With the ever-growing dependency on software, testing for their unexpected behavior is as important as verifying for their known properties, to avoid potential losses. Existing software testing approaches assume either ...
  • A quest for cyber high ground : impact of internet structure on (anti-) censorship 
    Gosain, Devashish; Chakravarty, Sambuddho (Advisor) (IIIT-Delhi, 2020-07)
    The original design of the Internet was a resilient, distributed architecture, that should be able to route around (and therefore recover from) massive disruption — up to and including nuclear war. However, network routing ...
  • Supporting ongoing training of community health workers through mobile-based solutions in rural India 
    Yadav, Deepika; Singh, Pushpendra (Advisor) (IIIT-Delhi, 2021-08)
    Community health workers (CHWs) in low- and middle-income countries play a vital role in public healthcare. CHWs particularly assist in improving maternal and child health conditions of the poor and vulnerable who often ...
  • On the secure design of multi-biometric template protection approaches for biometric authentication 
    Garg, Surabhi; Chang, Donghoon (Advisor) (IIIT-Delhi, 2021-06)
    The biometric systems are widely deployed in various sectors for authentication purposes– India’s Aadhaar project (a multi-biometric database of above 1.3 billion of India’s population) being the prominent example. The ...
  • Malware detection through binary analysis 
    Maheshwary, Yashit; Kurian, Deepak; Buduru, Arun Balaji (Advisor) (IIIT-Delhi, 2020-05-29)
    Malware Detection is an important problem in modern day due to the increasing frequency of malware attacks using unknown malware strains. Unlike traditional detection techniques which require a signature for each sample, ...
  • Taboos in Education 
    Tomar, Yash; Singh, Pushpendra (Advisor) (IIIT-Delhi, 2020-06-03)
    Taboo is prohibition or restriction by social custom. So generally teaching a taboo topic is not easy for a teacher as well a student might feel hesitated to ask doubts for the taboo topics.We aim to study can VR help ...
  • K-center problems 
    Ahuja, Yajur; Das, Syamantak (Advisor) (IIIT-DElhi, 2020-06-03)
    We consider a generalization of the classical K-center problem with capacities, demands, and outliers. The capacitated K-center problem adds a constraint to the original K-center problem of every vertex having a capacity ...
  • Knowledge graph construction from text 
    Saini, Vipul; Mutharaju, Vijaya Raghava (Advisor); Chakraborty, Tanmoy (Advisor) (IIIT-Delhi, 2020-06-05)
    Knowledge graphs have become quite popular and their utility is increasing at a very fast rate. There exist numerous extensive knowledge graphs that contain information on a plethora of topics. With new information ...
  • Shepherding large swarms with visibility constraints 
    Bhatia, Vedant; Sujit, PB (Advisor) (IIIT-Delhi, 2020-06-04)
    The shepherding problem is a problem setting in the multi-agent systems domain. The primary aim is to guide or ‘shepherd’ a swarm of unwilling agents to a destination, with the help of autonomous agents. We explore this ...
  • Online algorithms : the online job assignment problem and its variants 
    Ramanathan, Varun; Raman, Rajiv (Advisor) (IIIT-Delhi, 2020-06-01)
    Traditionally, algorithms try to find the optimal solution for a problem in a “three-phase” approach: fetch the input, run the algorithm, output the solution. But recently, there has been an interest in understanding ...
  • Finding textual description for paths in knowledge graphs 
    Agrawal, Dewangee; Kumar, Suraj Prathik; Bhatia, Sumit (Advisor); Mutharaju, Vijaya Raghava (Advisor) (IIIT-Delhi, 2019-11-15)
    We address the problem of finding a textual summary of facts within a path in a knowledge graph.Knowledge graphs are increasingly used in search engines and store data in the form of a Semantic Web structure making ...
  • Detecting early signs of depression using user-generated data from social media 
    Suhavi; Shah, Rajiv Ratn (Advisor); Kumaraguru, Ponnurangam (Advisor) (IIIT-Delhi, 2020-05-29)
    Social media has now become the most popular medium for self-expression and community building. More and more people are turning to it to express, write, vent or just be while being comfortable doing so because it’s an ...
  • Developing an objective measure for research publications 
    Jain, Shubhi; Singh, Pushpendra (Advisor) (IIIT-Delhi, 2020-06-05)
    Using the publicly available data-sets and the surveys, we aim to design a web-portal that would be able to provide insights into venues that are considered important for research as well as information of researchers ...
  • Hide and seek: outwitting community detection algorithms 
    Mittal, Shravika; Chakraborty, Tanmoy (Advisor) (IIIT-Delhi, 2020-05-27)
    Community affiliation of a node plays an important role in determining its contextual position in the network, which may raise privacy concerns when a sensitive node wants to hide its identity in a network. Oftentimes, ...
  • Approximate description logic reasoning 
    Yadav, Raj Kamal; Mutharaju, Vijaya Raghava (Advisor); Bhatia, Sumit (Advisor) (IIIT-Delhi, 2015-11-15)
    Approximate Reasoning involves compromising the soundness or the completeness of reasoning over description logic ontologies in favor of significant speed up in the run time. The efficiency of approximate Reasoning can ...
  • Multimodal deep learning 
    Sood, Raghav; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (2020-05-31)
    Modality refers to how something happens or is experienced. It is the representation format in which information is stored. Multimodal Learning involves relating information from multiple sources. Many modalities are ...
  • Deep mean shift clustering 
    Madaan, Pulkit; Maiti, Abhishek; Anand, Saket (Advisor); Mittal, Sushil (Advisor) (IIIT-Delhi, 2019-11-15)
    We use Mean Shift clustering in the latent space of an auto-encoder to have a better representation of the data and a more structured latent space. Instead of just using the mode of the distribution calculated using kernel ...
  • Unsupervised learning of low rank subspace projection using graph embedding 
    Jain, Kshitiz; Priysha; Subramanyam, A V (Advisor) (IIIT-Delhi, 2020-05-28)
    Subspace learning has often been explored for various applications such as dimensionality reduction, denoising, clustering and feature extraction among others. However, low rank subspace learning for clustering as well ...
  • On DenseResNet: residual connection finetuning 
    Prakash, Pragya; Vatsa, Mayank (Advisor); Singh, Richa (Advisor) (IIIT-Delhi, 2020-05-25)
    Transfer learning is widely used for many applications, but it is difficult to adapt intermediate layers of the network to a new learning task with less data available. Learning the importance that key connections play ...

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