Understanding neural activity through stimulation offers significant potential for neuroscience research and clinical applications. However, experimental setups involving magnetic or electrical stimulation, such as those ...
This thesis presents ConcurBench, a novel benchmark framework designed to evaluate the capa- bilities of Large Language Models (LLMs) in generating concurrent code. Concurrent program- ming remains one of the most challenging ...
This report presents the development of an Interactive Wall, a gesture-based drawing application that integrates Computer Vision, Machine Learning, and Unity to enable intuitive interaction with a virtual canvas. Using ...
The project titled ”Tech Consultancy for Institute Administration” aims to address the various inefficiencies faced by students and administration in a college, especially where manual tasks can be automated through ...
Shah, Het Riteshkumar; Akhtar, Md. Shad (Advisor)(IIIT-Delhi, 2024-11-27)
Faithfulness is a critical aspect of effective mental health conversa- tions, particularly when Large Language Models (LLMs) are deployed as virtual therapists. While LLMs have shown great potential in facilitat- ing mental ...
Singh, Harshvardhan; Deb, Sujay (Advisor); Akhtar, Md. Shad (Advisor)(IIIT-Delhi, 2024-11-27)
This report presents the development of a resource-efficient college chatbot assistant using Retrieval-Augmented Generation (RAG) to handle academic and administrative queries. The system automates document preprocessing ...
This project, Pixel to Plate, aims to bridge computer vision and natural language processing to automate recipe generation from images of ingredients. The first phase of the project focuses on object detection, employing ...
The focus of this project is to analyze and study the amalgamation of two very promising fields graph signal processing and fractality analysis, inspired by an extensive review of existing litera- ture on fractal dimensions, ...
This thesis undertakes a comprehensive exploration of object detection technologies with a particular emphasis on their application in autonomous driving and related application settings. The burgeoning field of autonomous ...
Critical applications are now incorporating more and more machine-learning (ML) models, this implies that the aforementioned security and privacy flaws must undergo tough screening to prevent attacks. The main objective ...
This report outlines the methodology, execution, and results of predicting the three- dimensional (3D) structures of miRNA sequences using AI and machine learning tech- niques. Using the RNAfold tool to predict the secondary ...
In recent times, cyber attackers have progressively become stealthier and persistent, and have come to be known as Advanced Persistent Threats (APTs). These attackers are usually state sponsored with a defined objective ...
Navigating a robot in an new environment without predefined graphs presents significant chal- lenges in perception, planning, and adaptability. However, traditional approaches rely on struc- tured maps, which limits their ...
This project presents the development of a mobile telepresence system that enables real-time 3D mapping and remote environment visualization using a VR headset. At its core, the system in- tegrates an Intel RealSense D455 ...
Determining whether a drug molecule inhibits a target protein is a critical step in the drug discovery process. While the pIC50 value is commonly used to quantify the inhibitory effect of a drug, experimentally determining ...
Sharma, V. Divya; Gupta, Anubha (Advisor)(IIIT-Delhi, 2026-04)
High-quality synthetic speech has transformative potential for accessibility, education, entertainment, and personalized human–computer interaction. However, it also poses serious risks: synthetic voices can be exploited ...
The growing reliance on relational databases across industries and the ability to efficiently query and extract from a structured database has become a crucial skill in the industry. However, the Complexity of SQL Syntax ...
We combine domain-specific knowledge graphs with general knowledge graphs to enrich a language model. The objective of this semester was to implement baselines, test var- ious previous literature surveyed, and try to ...
This study addresses the challenge of large-scale, multi-label recipe classification us- ing a real-world dataset of over 600,000 recipes collected from heterogeneous sources. The raw data exhibited significant noise, ...
Bhagat, Amil; Jain, Milind; Subramanyam, A V (Advisor)(IIIT-Delhi, 2024-05)
This project focuses on leveraging consistency models for downstream tasks involving the trans- lation and mapping between different modalities, such as converting visible images to their corresponding infrared representations. ...