MS (Entrepreneurship)

Development of Digital Twin of Civilian and Defense Infrastructure for Situational Awareness and Management

The proposed system integrates structured and unstructured data from multiple sources into a real-time Digital Twin, enabling advanced situational awareness, anomaly detection, and data-driven decision-making. It also provides intent-based orchestration of heterogeneous robotic assets, automatically translating high-level objectives into optimized tasks based on each asset’s capabilities, availability, and real-time status.

Venturearch: AI Enabled Venture Building Platform

VentureArch is a unified platform for higher education institutions to manage innovation, entrepreneurship, incubation, cohort programs, training, venture building, and funding opportunities, with end-to-end tracking of startups from onboarding to graduation.

TerraTwin: Multimodal, Physics-Aware Digital Twins of Real-World

TerraTwin creates physics-consistent digital twins of real-world environments by combining camera, LiDAR, radar, and IMU data. It models physical properties such as material reflectance, friction, stiffness, and sound propagation. This enables accurate “what-if” analysis, simulation, prediction, and design. The platform transforms real environments into queryable digital models for multiple applications. It also offers twin creation, simulation computing, and validated sensor modules through a SaaS-based model.

Reinventing Drug Formulation Technology for Improved Onset of Action and Lower Dose Requirements

This project aims to improve the solubility and bioavailability of existing drugs by reformulating active pharmaceutical ingredients (APIs) with biocompatible organic compounds. Initial studies showed significantly improved solubility and faster dissolution for drugs such as aspirin, paracetamol, ibuprofen, and diclofenac. The approach could enable faster drug action, lower doses, and liquid formulations for oral or injectable delivery.

Commercialization of a wave energy converter

We are designing a wave energy converter, which should be commercialized. Hence, it is inevitable to go for market discovery, costing, financial analysis, and fund management.

Design of smart pixels for CMOS image sensors for real-time, scene-adaptive performance

This project uses tunable-capacitance ReRAM (TCReRAM) technology to develop advanced CMOS image sensors with adaptive analog conversion gain. It enables in-pixel adjustment for over- and under-exposure without additional post-processing circuits, reducing area overhead, energy consumption, and latency. The technology is particularly suited for applications requiring real-time image and information capture.

Development of a web platform for estimation of flood and its frequency at any location in India

This project develops a web portal to estimate flood frequencies and depths at locations across India, including ungauged areas. It combines satellite data with observed records from gauged locations to provide reliable flood estimates. The platform can support land selection, agricultural planning, and flood insurance decisions. It can also help policymakers and insurance companies improve flood-risk planning and management.

Assisted learning for children with neurodiverse behavior

Simplify the audio recordings of classroom discussions using AI so complex sentences can be broken into simpler forms for easier understanding by children with autism

Three-Dimensional Acoustic Surveillance Network for Detection and Localization of Aerial and Ground-Based Threats in Controlled Environment

The project develops a passive acoustic sensing and localization system to detect and track stationary and mobile acoustic sources. It uses microphone arrays and time-reversal signal processing for 3D localization under noise, multipath, and changing atmospheric conditions. An AI-based classification layer helps distinguish target signals from false alarms. The system is designed for perimeter monitoring of airports, critical infrastructure, and other security-sensitive environments, with potential for field deployment and commercialization.

Development of a Data-Driven Platform for Optimal Management of Construction and Demolition Waste Management for cities

This project develops a digital waste-tracking and analytics system for Construction and Demolition (C&D) waste management. It combines computer vision and GIS technologies to detect, quantify, and characterize C&D waste across cities. The system also supports optimized collection planning and is being advanced through field testing. The goal is to help cities and government agencies improve C&D waste tracking, management, and resource planning

Measurement of blood-based biomarkers

This project develops a microfluidics-based diagnostic platform for rapid isolation and detection of target cells and biomarkers from biological fluids. It enables fast, accurate, and cost-effective analysis with minimal sample processing. The initial application focuses on early detection of mastitis in dairy animals through somatic cell quantification. The portable and scalable platform can be adapted for broader diagnostic applications and commercialization.

Digital-twinning and AI-enhancement for Molten Salt Reactors for Nuclear Energy

This project develops a high-fidelity Digital Twin of a 5 MW thorium-based Molten Salt Reactor (MSR) for safety assurance and operational optimization. It uses OpenModelica-based multiphysics modelling to simulate reactor behaviour, including neutronic, thermal-hydraulic, and natural convection effects. The twin integrates thermophysical data to provide an accurate virtual representation of reactor operation and support monitoring, analysis, and optimization.

Laser-processed medical materials and devices - lab-to-market

This project develops next-generation surgical meshes using femtosecond laser processing of polypropylene sheets. Bio-inspired microstructures are created on the surface to improve wettability, cell attachment, and biocompatibility without chemical treatment. The laser-based manufacturing process enables precise, customizable surface properties and is scalable for mass production. The technology offers a pathway for developing advanced, high-performance medical implants.

Customizable silicone wearables in healthcare

This project uses multi-material extrusion 3D printing to manufacture customizable silicone-based medical products. High-viscosity silicone materials can be printed into complex shapes using UV curing and advanced mixing techniques. The technology enables patient-specific designs for prosthetics and other non-implant healthcare applications, offering improved customization and personalized care.

Development of a Machine Learning-Based Lubricant Condition Monitoring System for Electric Vehicle Applications

Development of a Machine Learning-Based Multi-Parameter Lubricant Condition Monitoring System for Electric Vehicle Applications.Project includes both machine design and machine learning.

Ensuring Safety in Railways: Locomotive Axle Lock IoT and Prognosis

This project develops a modelling and detection system to identify and predict axle lock conditions in locomotives using real-time sensor data. It combines physics-based models of wheel–rail interaction with data-driven analytics to detect abnormal wheel movement and anticipate failures. The system aims to improve locomotive safety, prevent wheel and track damage, reduce maintenance costs, and enhance operational reliability.

AI-Assisted Project-Based Learning Platform for Schools and Colleges

The platform helps school and college students learn engineering, robotics, and simulation through hands-on projects and interactive learning tools. An AI assistant provides hints and explanations, while teachers can assign projects, track progress, and review student portfolios through a dashboard. The platform follows a paid pilot and annual SaaS subscription model for educational institutions.