Professor Nitesh Chawla, professor of computer science and engineering and director of both the Interdisciplinary Center of Network of Science and Applications and the Data, Inference, Analytic and Learning Lab, was awarded the 2015 Early Career award by the Institute of Electrical and Electronics Engineers (IEEE) Computational Intelligence Society (CIS).
“I am very excited and honored to receive this award,” said Chawla. “Every year IEEE CIS selects one scientist or engineer working in computational intelligence area, under the age of 40, to receive the IEEE CIS Outstanding Early Career Award. "It is a recognition of the contributions to-date and the promise of the contributions that lay ahead.”
The IEEE CIS awarded Chawla the award for his groundbreaking research in data mining, machine learning, network science, and its numerous applications especially with inconsistent and difficult-to-read data.
“[My work involved figuring out] how to learn and develop algorithms to cater to data sets which have extreme events, rare events and distributions that are not consistent and stationary and how do you develop algorithms to react unique challenges and data,” said Chawla. “Some of my work is the most-cited work in learning from imbalanced data such as in a method called SMOTE [Synthetic Minority Oversampling Technique] … and some of the work we have done in developing machine-learning algorithms for non-traditional distributions and non-stationary data was also consideration for this award as well as awards have more recently earned for work I was doing in network science where we published groundbreaking work in link prediction.”
Chawla said he is applying that data to help healthcare systems provide personalized care that is more focused on treating the patient rather than care that is strictly focused on fighting disease.
“For a long time, we have been focused on a disease-centered approach. That’s when we have an individual who has a Disease A, we try to cure the disease not really looking at who the individual is, what are the more common diseases that individual has, or the circumstances that individual may be in. ... Our researched is focused on [thinking] about who that person is, how do you personalize medicine, personalize care or customize wellness strategies for that individual based on anatomical and health records of that individual.”
Chawla said his work is also adapted to suit roles in fields ranging from medicine to security.
"[In] the next couple of years the basic foundation of research is taking a big shift towards Big Data … So how do we calculate how much we trust in the data? ... How do we attach a veracity and reliability on that data? So that’s one area of research that will keep us busy for the next couple of years," he said.
