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Innovative Artificial Intelligence Lab
At Nothing, a highly collaborative Artificial Intelligence Lab that deals with human fully collaborative and research artificial intelligence patterns, You are guaranteed of a 100% correct result.
RESEARCH PROJECTS
Current Areas of Study
COMPUTATIONAL NEUROSCIENCE
October 25-2022 - Jan 25-2025
Our research focuses on understanding the brain using computational models and simulations,. The primary goal of this group is to discover the computational principles underlying the brain's remarkable ability to learn, process and store information. How does the brain learn efficient representations of objects and events occurring in the natural environment? What are the algorithms that allow useful sensorimotor behaviors to be learned? What computational mechanisms allow the brain to adapt to changing circumstances and remain fault-tolerant and robust?
COMPUTATIONAL BIOLOGY
October 25-2022 - June 03-2023
Our research focuses on developing machine learning algorithms that will enable the use of an individual’s comprehensive biological information to predict or diagnose diseases, and to find or develop the best therapy for that individual.
It has recently become possible to retrieve molecular-level information from an individual, such as DNA sequence, gene expression levels in various tissues, epigenomic profile and other information. While such data is increasingly available, we are still unable to understand the genetic and molecular mechanisms that cause diseases. The challenge is due to the multifactorial nature of disease. The same disease can be caused by mutations in different genes or different pathogenic pathways. Unfortunately, current data analysis approaches fail to capture the complex relationship between disease and the vast amount of information in the molecular data.
The aim of our research is to resolve this challenge by developing machine learning algorithms that jointly model sophisticated interactions among many variables such as genetic variation, genes, pathways and disease, and robustly learn from vast amounts of data in order to better understand and treat disease. An approach that can robustly infer the pathways that can define disease processes will dramatically improve our understanding of diseases and advance personalized medicine in its treatment. We aim to realize this goal by using modern, advanced machine learning techniques.
ROBOTICS
September 13-2023 - Ongoing
We are engaged in ground-breaking work in mechanism design, sensors, computer vision, robot learning, Bayesian state estimation, control theory, numerical optimization, biomechanics, neural control of movement, computational neuroscience, brain-machine interfaces, natural language instruction, physics-based animation, mobile manipulation, and human-robot interaction. We are currently working to define large-scale joint initiatives that will enable us to leverage our multi-disciplinary expertise to attack the most challenging problems in field.