Our projects
of AI, Cybersecurity, IoT, and Next-Generation Networks. We collaborate with
industry, government, and academic partners to build impactful, future-ready solutions.
Unsupervised crowdsourcing with cost and accuracy guarantees
The crowdsourcing platform is assumed to be divided into multiple classes, based on workers skill, experience, etc. We consider the problem of cost optimal utilization of a crowdsourcing platform for binary, unsupervised classification of a collection of items, given a prescribed error threshold.
Faculty associated
Prof. N. Hemachandra (IEOR)
&
Prof. Jayakrishnan Nair (EE)
Automating Threat Detection and Response in Linux Endpoints
Endpoint Detection and Response EDR is an advanced technology for the detection and prevention of attacks on cyberinfrastructure. It is an integrated security solution that combines realtime continuous monitoring and collection of endpoint data with rules-based automated response and analysis capabilities.
Faculty associated
Prof. Manjesh K. Hanawal (IEOR)
3D Medical Image data synthesis for classification and segmentation using deep generative techniques abeling 3D medical images
Typical prediction tasks using 3D medical images like classification and segmentation using deep neural networks require large amounts of labeled training data. In this project, we will develop novel variants of deep networks e.g. generative adversarial networks GANs, variational encoders VAEs to synthesize 3D medical image data for classification and segmentation tasks.
Faculty associated
Prof. P. Balamurugan (IEOR)
AI/ML Applications for Enhanced Smart Metering for Residential Electricity Consumption
Residential electricity consumption accounts for 24% of the total electricity demand in India and is the largest connected on the Indian power grid. Smart metering allows utilities to continuously monitor and potentially control this load. In this project, we are working with SustLabs to develop AI/ML-based algorithms for load disaggregation at the smart meter level.
Faculty associated,
Dr. Anupama Kowli,
Associate Professor, Dept of EE, IIT Bombay
Pattern Recognition-AI and NMR aided HOS analysis for structural similarity of Biological Drugs
Biosimilar refers to the biological drug that is highly similar to the available marketed drug such that there are no clinically meaningful differences in terms of safety, purity, and potency of the product. These drugs can only enter the market after completing the patent duration of the licensed first-generation drugs.
Faculty associated
Prof. Ashutosh Kumar,
Professor, Department of Biosciences and Bioengineering, IIT Bombay
Robust domain adaptation strategies for vibration condition monitoring of machines at the edge
In this project, we are investigating compact machine learning algorithms implementable on microcontrollers for diagnosing faults and anomalies in machines based on vibration sensing. The focus is on development of light-weight algorithms that are immune to domain shift and concept drift (i.e. scalable to large number of various types of machines)
Faculty associated
Siddharth Tallur,
Associate Professor, Electrical Engineering, IIT Bombay
Address
Technocraft Centre for Applied Artificial Intelligence,
A91 Eco Hub, IIT Bombay
Mumbai – 400076, INDIA
Contact Us
Tele:- 022 2159 6662
Email Address:- office[dot]tcaai[at]iitb[dot]ac[dot]in