What Drives Our Research?
Our research is primarily driven by three components, data science thinking, real world issues, and opportunities for innovation and exploration of theoretical gaps.
Data science thinking, a crucial skill in data science, drives us to dive deeper into scientific cognitive paradigms and thinking patterns, statistics, computational and analytical thinking and systems, analytics and design architectures, frameworks and processes.
We explore real world issues as they are relevant to open complex data and behavior and systems in many different fields including business, finance, education, the public sector, industrial industries, economies and more.
Opportunities for innovation and the exploration of theoretical gaps are explored and analyzed in existing systems of statistics, data and intelligence sciences and computing for distinct issues, gaps and challenges.
Our Current Data Science Research
Our research center has been exploring newfound broad and unique matters related to data science, artificial intelligence, analytics and machine learning such as the following.
Data science and intelligent science topics including original research, machine learning, artificial intelligence, document understanding, information retrieval, recommendations and complex systems.
X-complexities and X-intelligences such as behavior complexity/intelligence, domain complexity/intelligence, involving data complexity/intelligence, organizational complexity/intelligence, network complexity/intelligence, human complexity/intelligence, social complexity/intelligence and economic complexity/intelligence.
Complex data including multi-source and cross-domain data, non-IID data, high-dimensional data, imbalanced and inadequate data, incorrectly structured data, noisy and redundant data, outlying data and networking data.
Complex behaviors such as prediction, modeling, intervention, analysis and the management of individual and group occurring and non-occurring behaviors of humans, living systems and other related systems.
Complex systems such as design, modeling, analysis, evaluation, and the enhancement of artificial and natural systems by data science and artificial intelligence.
Enterprise Data Research
Enterprise data is being adopted at a rapid rate by decision makers, data managers, innovators and leaders in competitive fields among others. Data science and intelligence science are now more than ever playing an increasingly important role in this process to facilitate advanced decision-making to propel organizations and industry bodies ahead of competitors. The research center team at Ernesto.Net is highly effective in leveraging our findings for the benefit of those that work with us. We do this via:
Knowledge and support to design, apply, manage, review and streamline enterprise data for the benefit of decision-making, opportunity assessment, planning, processes and more.
Capabilities and skills to effectively plan, organize, implement and enhance enterprise data science systems, processes, models and the way it is applied.
Experience and qualification necessary for the up-and-coming data scientists and industry professionals via superior education in the form of courses, workshops and training to advance the field and its applications.