Our experimental and theoretical research includes many data science and systems research domains. These include but are not limited to time series mining, deep learning, NLP and large language models, graph mining, signal processing, and cloud computing. Our research aims to fully understand the dynamics of big data from complex systems, retrieve patterns to profile them and build innovative solutions to help the end user manage those systems. We have built several analytic engines and system solutions to process and analyze big data and support various detection, prediction, and optimization applications. Our research has led to award-winning NEC products and publications in top conferences.

Data science research is poised to transform substantially. First and foremost, there will be a continued emphasis on the ethical and responsible use of data. As data-driven decision-making becomes more pervasive across industries, organizations must prioritize data privacy, security, and transparency. Secondly, the field of data science will witness advancements in automation and AI-driven analytics.

Our team will remain vigilant in ensuring responsible data usage while harnessing the potential of these cutting-edge data science tools to fuel innovation for our clients, partners and collaborators.