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  • MAB on hardware 
    Pareek, Animesh; Darak, Sumit Jagdish (Advisor) (IIIT-Delhi, 2023-11-29)
    The Multi Armed Bandit (MAB) problem in the Reinforcement Learning field refers to the problem of allocating resources in certain choices for achieving an overall goal with the objective of maximizing expected gain. Our ...
  • Machine learning aided cancer drug response prediction using chemo-genomic data 
    Sharma, Prashant; Sengupta, Debarka (Advisor) (IIIT-Delhi, 2023-07)
    The intricate nature of tumor heterogeneity and the personalized responses of cancer patients to drug treatments present significant challenges in the field of oncology. In this thesis, I aim to address such challenges by ...
  • Machine learning and deep learning models for prediction of protein-ligand binding affinity 
    Kaur, Parneet; Murugan, N Arul (Advisor) (IIIT-Delhi, 2024-05-01)
    In recent years, there has been significant interest in using Machine Learning and Deep Learning to predict protein-ligand binding affinity. This is due to the rapid growth of the computational approaches that have evolved ...
  • Machine learning and deep learning models for solvation energy prediction 
    Tejas; Murugan, N Arul (Advisor) (IIIT-Delhi, 2023-08)
    Drug discovery is divided into 4 phases. The first phase is in-silico processes beginning with target identification and validation, followed by the hit discovery process, assay development, high throughput screening, ...
  • Machine learning and tanimoto similarity based virtual screening of chemical libraries to develop novel PD therapeutics 
    Singhal, Divyanshi; Murugan, N Arul (Advisor) (IIIT-Delhi, 2024-05-01)
    Parkinson's disease is a prevalent neurodegenerative disorder that affects a significant portion of the aging population worldwide. The etiology of Parkinson's disease involves the accumulation of misfolded proteins, ...
  • Machine learning approaches in cancer detection and treatment 
    Sarita; Sengupta, Debarka (Advisor); Kumar, Lalit (advisor) (IIIT-Delhi, 2023-12)
    Cancer has become the second leading cause of mortality worldwide, and early de-tection and adequate treatment are crucial in reducing the cancer burden. Metastasis,which involves malignant cells detaching from the primary ...
  • Machine learning assisted EDFA modelling for gain and ASE prediction 
    Singh, Kshitiz; Mitra, Abhijit (Advisor) (IIIT-Delhi, 2022-05)
    Machine Learning methods and algorithms have found use in a vast number of industries, including the optical networks industries. One of the key components of any optical network is the Erbium Doped Fibre Amplifier, or ...
  • Machine learning based design of multi-targeting inhibitors for Alzheimer disease and structure based validation 
    Kumar, Virendra; Murugan, N Arul (Advisor) (IIIT-Delhi, 2024-06-01)
    Neurodegenerative diseases are one of the major problems in today's world, and Alzheimer's is one of them. The disease-associated symptoms are not diagnosed earlier, and also very few FDA-approved disease-reversing drugs ...
  • Machine learning for intensive care units 
    Sehgal, Rahul; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2023-11-29)
    Intensive Care Units (ICUs) generate extensive time series data, particularly patient vitals, holding immense potential for meaningful insights crucial for timely interventions and enhanced patient outcomes. Conventional ...
  • Machine learning for intensive care units 
    Deeptanshu; Sethi, Tavpritesh (Advisor) (IIIT-Delhi, 2023-05-09)
    Intensive Care Units (ICUs) collect vast amounts of data, including patient vitals which are often recorded as time series data. This data can be analysed to extract meaningful data, which can aid in timely intervention, ...
  • Machine learning in cancer genomics 
    Gupta, Taejas; Gupta, Anubha (Advisor) (IIITD-Delhi, 2019-04-28)
    Cancer is caused by an increased amount of cell growth in an area due to alterations in protein synthesis caused by mutations in certain genes known as cancer driver genes. Determining the gene regulatory network for the ...
  • Machine learning provides preliminary snapshots of disease-specific variations in gut microbial aging-trajectories 
    T R, Seerapthynath; Ghosh, Tarini Shankar (Advisor) (IIIT-Delhi, 2025-08)
    The human gut microbiome plays a critical role in metabolism, immunity, and disease resistance, with its composition shifting notably with age. These changes have positioned the microbiome as a potential “biological clock” ...
  • Machine learning regression models for predicting hemolytic concentration (HC50) of peptides using curated activity data 
    Singh, Ayushi; Raghava, Gajendra Pal Singh (Advisor) (IIIT-Delhi, 2025-06)
    In this thesis, we first compiled hemolytic activity data of peptides in terms of hemolytic concentration (HC50), defined as the concentration required to lyse 50% of red blood cells (RBCs). We then developed regression ...
  • A machine learning-based approach for predicting a recipe’s cooking time from its ingredients and direction 
    Reddy, Sreekar; Thappa, Deepak; Kaushal, Divyansh; Bagler, Ganesh (Advisor) (IIIT-Delhi, 2024-11-28)
    This paper focuses on predicting cooking times for recipes based on advanced natural language processing techniques and machine learning models. With the increase in the number of online recipe datasets, there is a massive ...
  • Machine learning-driven timing analysis and physical design for VLSI 
    Beniwal, Pooja; Saurabh, Sneha (Advisor) (IIIT-Delhi, 2026-08)
    Electronic design automation (EDA) comprises software tools for designing modern integrated circuits that includes synthesis, placement, routing, timing analysis, and verification. As designs scale to billions of transistors, ...
  • Magical interaction in XR 
    Kumar, Prince; Kumar, Ayush; Ansari, Mohammad Areeb; Srivastava, Anmol (Advisor) (IIIT-Delhi, 2024-11-27)
    This project introduces a novel Magical Interaction in XR, enabling users to create floating platforms in real-time using intuitive hand gestures. These platforms act as sequential stepping stones, blending walking and ...
  • Maginot lines and tourniquets : on the defendability of national cyberspace 
    Gosain, Devashish; Rawat, Madhur; Sharma, Piyush Kumar; Acharya, Hrishikesh Bhatt (IIIT-Delhi, 2020-01)
    National governments know the Internet as both a blessing and a headache. On the one hand, it unlocks great economic and strategic opportunity. On the other hand, government, military, or emergency-services become vulnerable ...
  • Making project manager as super project managers 
    Dholaria, Parthiv Ashokkumar; Garg, Utsav; Jalote, Pankaj (Advisor); Kumar, Dhruv (Advisor) (IIIT-Delhi, 2024-11-27)
    The objective of this project is to explore the use of Large Language Models (LLMs) in au tomating aspects of software project management, starting with the objective of creating a ”Su per Project Manager” capable of ...
  • Malware detection through behavioral analysis 
    Anand, Mrinal; Buduru, Arun Balaji (Advisor) (IIIT-Delhi, 2023-11-29)
    As the usage of Android mobile devices has increased rapidly, so has the occurrence of Android malware. To mitigate the risk posed by Android malware, it is important to develop effective detection techniques. In this ...
  • 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, ...

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