Road safety affects everyone. In an effort to reduce accidents, we need to understand both the driving behavioural patterns that are predictive of accidents, and the environmental factors involved. In order to analysis risks, at first, collect a rich set of data: including Latitude/Longitude, engine RPM, accelerometer data in the X, Y, and Z plane, […]

The task of predicting salaries for a given job title and seniority in a specific region is challenging due to the complexity of various factors as well as the sensitivity of salary data. It’s hard to get an accurate sense of what people are getting paid in many regions in the world and getting harder […]

Ecomtent focuses on developing vertical-specific generative AI models for e-commerce brands, offering a self-service tool to allow customers to generate an unlimited number of high-quality images in any scenario. To this end, we leverage a textto- image model which will be trained to recontextualize any image via a simple text prompt. In particular, we seek […]

Traditional cancer treatments have followed a “one size fits all” approach, which limits efficacy and often results in significant side effects. This research project aims to develop an approach to predict the impact of cancer missense mutations on the drug-protein interactions of cancer treatments. The approach will use the patient’s own genomic profile and will […]

This research will explore machine learning methods in order to devise a control scheme for robotic manipulators(Candarm3) in the context of space exploration. The objective is to develop an early prototype for an autonomous learning agent which can carry out standard control tasks without any operator supervision. The primary machine learning methods that will be […]

Nowadays, many of the movie characters whose performances move us on screen are at least in part digital. From superhero stunts to de-aged beloved actors and actresses, visual effects artists have to create digital characters and painstakingly reproduce performances to convince audiences. New Deep Learning (DL) technologies are emerging to help alleviate the processes. For […]

As generative models become increasingly prominent in machine learning, the need for accurately detecting out-of-distribution data has become crucial. The primary objective of this research is to develop an approach that can identify when the program encounters data that is vastly different from what it was trained on. In machine learning, programs may make errors […]

The use of indoor location-aware applications such as augmented reality, social networking, health care monitoring, asset tracking, and inventory control is on the rise. However, accurately locating Wi-Fi based devices within buildings can be a challenge, particularly in areas where GPS signals are unavailable. This research project focuses on finding ways to locate indoor devices […]

With the evolution of unmanned aerial vehicles (UAVs) in recent years, more and more researchers are setting their sights on the application research of indoor environment. Indoor applications include industrial facility inspection, warehouse inventory management, health sector, search and rescue, among others. However, the use of UAVs in these applications requires continuous high-accuracy positioning and […]

This research project aims to develop a technique for detecting and analyzing security incidents in their early stages, reducing the potential impact on an organization’s operations. Conventional methods of deep packet inspection (DPI) and network monitoring solutions only identify frequently occurring traffic patterns, and security threats are often not detected until it’s too late. The […]

This project aims to improve recommendation systems by using advanced computer techniques called Auto Machine Learning and Meta Machine Learning. This involves automating parts of the machine learning process, like finding similar data and picking the best settings for the computer model. This project also aims to make it easier for others to set up […]

This project will be focus on developing a digital learning platform that is: grounded in the science of learning research; informed by established pedagogical approaches for supporting collaborative learning; responsive to principles of equity and inclusion; and based on principles of effective assessment to provide high-quality online and hybrid delivery modes of distance learning education […]