Alexander Nikolaev

I am an Associate Professor and Director of Social Optimization Lab (SOLLAB) at the Department of Industrial and Systems Engineering at University at Buffalo. I received a Ph.D. degree in Industrial Engineering from University of Illinois in 2008. My dissertation adviser was Dr. Sheldon Jacobson

     My interests and expertise are in social network analysis, resource allocation under uncertainty, causal inference, healthcare and educational data mining. My research group employs the techniques from both applied operations research and computer science. I have authored about thirty journal and about ten peer-reviewed conference papers, with the citation count of around 500, and won three National Science Foundation Awards, among others. I am an Associate Editor of "Socio-Economic Planning Sciences", and have served as an ad-hoc reviewer for about 20 other high quality journals.



    At the time I started working on my dissertation at Illinois, the existing literature on aviation security modeling was divided into two streams: work on security devices and optimal system design, and work on optimal passenger screening. My key contribution to this field lies in designing models that allow for treating both of these decision-making problems simultaneously. While working on this application, I also made methodological advances in sequential decision-making under uncertainty and local search algorithm design.

    My expertise in designing and applying optimization algorithms then led to methodological developments in causal inference with observational data. The conventional observational causal inference approaches employed over the past forty years have exploited matching of treated and untreated (control) units, with the quality of matching evaluated using covariate balance measures. The two approaches I have worked on, Balance Optimization Subset Selection and Mutual Information-based Matching, directly optimize balance to achieve accurate and fast inference.

    The research in social network analysis addresses strives for prescriptive rather descriptive advances. My methods for understanding human behavior based on static and longitudinal data combine models of communication with models of information exchange. The projects on influence maximization, opinion formation and strategic distribution of incentives and social capital are done with the help of my Ph.D. students and in collaboration with colleagues across multiple disciplines.

    My work on program/policy evaluation highlights the importance of "reach" dimension in the studies with connected human subjects. I argue that reach can be quantified and show that it can be manipulated via incentives and recommendations, informing targeted interventions in online pro-health forums and for fostering environmentally conscious behavior.

   Finally, my most recent interests are in the areas of educational data mining and collaborative learning. I am working to develop environments and practices that would make students more motivated and excited about learning, by letting them work in groups, challenging and helping each other.

   See the descriptions and products of my recent research projects at

Top Publications


Zulqarnain Haider, Alexander Nikolaev, Jee Eun Kang, & Changhyun Kwon, "Inventory Rebalancing through Pricing in Public Bike Systems", European Journal of Operational Research, forthcoming

Sabrina Casucci*, Li Lin, Sharon Hewner, & Alexander Nikolaev, "Estimating the Causal Effects of Chronic Disease Combinations on 30-day Hospital Readmissions based on Observational Medicaid Data", Journal of the American Medical Informatics Association, forthcoming

Abhinav Perla*, Alexander Nikolaev, & Eduardo Pasiliao, “Workforce Management under Social Link Based Corruption”, OMEGA, forthcoming

Mohammadreza Samadi*, Rakesh Nagi, Alexander Semenov, & Alexander Nikolaev, “Seed Activation Scheduling for Influence Maximization in Social Networks”, OMEGA, 77, pp. 96-114, 2018.

Rahul Gopalsamy*, Alexander Semenov, Eduardo Pasiliao, Scott McIntosh, & Alexander Nikolaev, “Engagement as a Driver of Growth of Online Health Forums: Observational Study”, Journal of Medical Internet Research, 19(8), 2017.

Lei Sun, & Alexander Nikolaev, "Mutual Information Based Matching for Causal Inference with Observational Data”, Journal of Machine Learning Research, 17(199), pp. 1-31, 2016.

Alexander Nikolaev, Shounak Gore, & Venu Govindaraju, “Engagement Capacity and Engaging Team Formation for Reach Maximization of Online Social Media Platforms,” the 22nd ACM SIGKDD Conference, pp. 225-234, 2016.

Mohammadreza Samadi, Alexander Nikolaev, & Rakesh Nagi, “A Subjective Evidence Framework for Influence Maximization in Online Social Networks”. OMEGA, 59(B), pp. 263-278, 2016.

Anshuman Kumar, Jamie Kang, Chang Kwon, & Alexander Nikolaev, “Inferring OD-Pairs and Utility-Based Travel Preferences of Shared Mobility System Users in a Multi-Modal Environment”, Transportation Research B: Methodology, 91, pp. 270-291, 2016.

Alexander Nikolaev, Raihan Razib, & Ashwin Kucheriya, "On Efficient Use of Entropy Centrality for Community Detection in Social Networks". Social Networks, 40, pp. 154-162, 2015.

Alexander Nikolaev, Sheldon H. Jacobson, Wendy K. Tam Cho, Jason Sauppe, & Edward C. Sewell "Balance Optimization Subset Selection (BOSS): An Alternative Approach to Causal Inference with Observational Data". Operations Research, 61(2), pp. 398-412, 2012.

Alexander Nikolaev, & Sheldon H. Jacobson "Stochastic Sequential Decision-Making with a Random Number of Jobs". Operations Research, 54(4p1), pp. 1023-1027, 2010.

Alexander Nikolaev, Matthew J.D. Robbins, & Sheldon H. Jacobson "Evaluating the Impact of Legislation Prohibiting Cell Phone Use While Driving". Transportation Research A: Policy, pp. 182-193, 2010.

Alexander Nikolaev & Sheldon H. Jacobson "The Theory and Practice of Simulated Annealing" in Handbook on Metaheuristics, vol. 146. (Ed.), New York: Springer, pp. 1-40, 2010.

Alexander Nikolaev, Sheldon H. Jacobson, & Laura A. McLay "A Sequential Stochastic Security System Design Problem for Aviation Security". Transportation Science, 41(2), pp. 182-194, 2007.



My approach to teaching is simple. I enjoy the time in the classroom, find it gratifying, and strive to make sure that those who spend this time with me feel the same. With this goal in mind, I see the challenge of teaching in creatively reminding students of the value of education, its fundamental importance in life. First and foremost, a true teacher helps students learn to think and work so that they could live a life they would enjoy.   


My teaching motto is: keep the students engaged, keep it modern, and be sincere.


The cornerstones of my teaching methodology are structure and continuity. With a huge amount of free online teaching material now available online, why would a student still want to be physically present in a classroom? I answer this question by working hard to build intuition for what I teach, and present the ideas from separate topics within a system, explicitly linking these ideas together. I teach students to appreciate, build and maintain a comprehensive logical structure around the course. Logical thinking is an art. Mastering this art is a trait that distinguishes graduates of the best educational programs.


I am convinced that innovations in teaching are absolutely necessary, especially those that combine advances in technology with advances in social and cognitive aspects of learning. The collaborative learning paradigm Crowdlearning that I am developing and using in my classrooms is my attempt to make a difference. 



University at Buffalo, Industrial and Systems Engineering, 2010 – Present

ISE 575, Stochastic Methods

ISE 555, Programming for Operations Research Applications (developed from scratch)

ISE 551, Simulation and Stochastic Models

ISE 411/511, Social Network Behavior Modeling (developed from scratch)

ISE 374, Introduction to Operations Research and Probabilistic Modeling


University of Jyväskylä, Finland

IS1, Social Network Behavior Analysis (Jyväskylä Summer School, August 2014)

IS1, Social Media Analytics (Jyväskylä Summer School, August 2016)


ITMO University, Russia

Natural Language Processing and Linked Data (Intensive Social Media Weeks, May 2015)


Northwestern University, Industrial Engineering and Management Sciences (2009 – 2010)

IEMS 415, Simulation

IEMS 372, Introduction to Probability Theory and Statistics

IEMS 310, Introduction to Operations Research