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Biography

Research

• Information Fusion and Complex Event Detection

• Efficient Computation of Social Network Metrics

• Optimal Resource Allocation for Spacial Analysis

• Causal Inference with Observational Data

• Social Network Analysis of Online Smoking Cessation Communities

• Stochastic Modeling of Hospital Readmission Process

Teaching

• IE 374: Systems Modeling and Optimization: Operations Research II

• IE 575: Stochastic Methods

• IE 411/511: Social Network Behavior Analysis

Teaching Interests

IE 575: Stochastic Methods

Course Overview

Catalog Description     This course teaches the fundamentals of applied probability theory, emphasizing the development of problem-solving skills. Topics include algebra of events, sample space representation of the model of an experiment (any non-deterministic process), random variables, derived probability distributions, discrete and continuous transforms and random incidence. The course introduces elementary stochastic processes including Bernoulli and Poisson processes. Course Overview     This course teaches the foundations of probabilistic analysis, providing graduate students with the necessary toolbox for handling uncertainty in their subsequent coursework. With the aid of illustrative examples, the applied aspects of probability theory are emphasized. The material builds from the ground up, including the review of random variables, standard distributions, and advancing to events, conditional expectations, moment-generating functions, convolutions, law of iterated expectations, Poisson process, etc. It is a core operations research course, and its material is included into the scope of the entrance exam into the Ph.D. program. Course Objectives     Students completing this course will be able to understand and apply probability theory concepts to model and solve problems, and express and evaluate uncertainty.

Staff

Instructor: Dr. Alexander Nikolaev, Ph.D. Assistant Professor Department of Industrial and Systems Engineering University at Buffalo (SUNY) 409 Bell Hall Buffalo, NY 14260-2050 U.S.A. Telephone: (716) 645-4710 FAX: (716) 645-3302 E-mail: anikolae@buffalo.edu Teaching Assistant: TBD

Basic Requirements

Algebra and advanced calculus General understanding of modeling in engineering

Required Work, Grading Policy, References

1.  Exam I    -  Basic Probability, Event Operations    25% 2.  Exam II    -  Distribution Functions, Transforms    25% 3.  Exam III    -  Bernoulli and Poisson Processes    25% 4.  Homeworks    -  Weekly/Bi-Weekly Assignments    25% Course Text [1]   Introduction to Probability (2nd Edition) by D.P. Bertsekas and J. N. Tsitsiklis (Athena Scientific) .