The Laboratory has four major goals.
- To foster research activities in the area of Applied Probability and Data Analytics
- To provide opportunities and facilitate
its members to apply for research projects and to work together
- To foster collaboration between the Lab members and the industry to demonstrate how this applied science can contribute to higher efficiencies
- To enhance the learning and teaching of these subjects
Our work involves modeling business and industry systems that function in the
presence of uncertainly, in order to provide practical scalable algorithms that
make possible the efficient operation of such systems
- Machine Learning
- Adaptive clinical trial design and management
- Clinical trial simulations in silico
- Catastrophic mechanisms for biological populations
- Web-systems and internet protocols
- Communications and traffic systems
- Maintenance schedule and design
- Inventory control, Production planning, Revenue management
- Health care management
- Financial analysis, Executive compensation, Taxes
- Price competition
- Competitive product positioning, Quantitative models in marketing
- Statistical Data Mining
- Network Analysis in Neurology and Imaging
- Data Privacy and Confidentiality
- Service Systems and Queues
- Matching Algorithms
- Applied probability methods (Transforms and special techniques:
Successive Lumping, Matrix Analytic, Compensation)
- Optimization methods
- Dynamic Programming and Markovian Decision Processes
- Data Analysis
- Financial Time Series
- Forecasting
- Simulation
- Game Theory