Professor Andriy Miranskyy directs research on the many possible risks associated with the software engineering process, with a special focus on complex systems that analyze big data. If not detected and mitigated, any such risks could result in poor business decision-making, overburdening of customer support services, unplanned and prolonged outages, overshot budgets and project schedules. Risks may include improper testing of big databases, system failure associated with non-scalable algorithms, late-stage requirements introduced into the development cycle, and spikes in consumer-discovered product defects. By exploring how to quantify and mitigate risk, our lab aims to make the computing world a safer place.
This vibrant area of exploration blends the inter-relation of software engineering, machine learning, and data science. To reach our aim, we leverage technologies, such as
- Data mining
- Deep learning
- Cloud computing
- Quantum computing
- High performance computing
Industrial Collaborations: we validate our research on real-world projects with the help of industrial partners, such as Environics Analytics, eSentire, and IBM.