Tag: machine learning
Machine learning uses algorithms to build analytical models, helping computers “learn” from data. It can now be applied to huge quantities of data to create exciting new applications. Researchers at WID are developing new methodology and theory for extracting useful information from data which may be noisy or high-dimensional, contain missing elements, or come from a variety of different sensors or streaming input.
Machine learning at WID plays a key role in problems as diverse as understanding the immune system, finding the funniest cartoon captions, and developing driverless cars.
Machine learning is an important component of WID’s Data Science Hub.
Víctor Blanco
Visiting Professor
Mathematical Optimization with applications in different fields as Logistics, DS or Network Design.
Siddharth Suresh
Understanding how we acquire concepts using computational modelling.
Ivette Colón
Encoding of social and visual concepts in the brain and in deep learning models of human cognition
Woojin Kim
Construction of strong convex relaxation in integer optimization problem arising in machine learning
Elias DeVoe
Network biology approaches to understanding long-term survivors of metastatic breast cancer
Yash Sancheti
Building and developing interactive 3D Virtual Reality (VR) models using Unity and C#
Kris Sankaran
Assistant Professor
Statistical tools for exploring latent variation in microbiological and earth systems data
Ben Kizaric
Subspace Clustering for interpretable, semi-supervised machine learning tasks; Image Compression.
Xudong Tang
Neural network models on soil micobiome data to predict characteristics of potato growth.
Sushrut Karmalkar
Designing efficient estimators which are robust to aggressive noise models
Jasper Lee
Designing practical, data-efficient algorithms with rigorous guarantees for statistical applications
Jinsu Gim
Injection molding, Polymer processing, Process monitoring and optimization
Ahmet Alacaoglu
Continuous optimization for machine learning, reinforcement learning and other data science problems
