Demetrios V. Papazaharias
Ph.D. Candidate, Operations Research
University at Buffalo
Biography
I am a fifth year PhD student studying operations research at the University at Buffalo. I am a member of the Group for Applied Mathematical Modeling and Analytics (GAMMA), led by my advisor Jose L. Walteros. My research is focused on integer programming techniques for solving network interdiction and graph partitioning problems.
- Network Interdiction
- Graph Partitioning
- Integer Programming
- Algorithms & Data Structures
- Parallel/Distributed Processing
- Statistical Learning
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PhD in Industrial Engineering, 2022*
University at Buffalo (attending)
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MS in Industrial Engineering, 2019
University at Buffalo
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BSc in Applied Physics, 2016
SUNY College at Geneseo
Experience
Project: Managing Exponential Decision Spaces (MEDS)
We model the decision space of an analyst involved in military conflict on networks. Develop exact and heuristic approaches for recommending courses of actions. Funded by the Office of Naval Research.
Software & Tools: C++, Python, Gurobi
Scope of Work:
- Incorporated physical models to understand damage signatures in wind turbines.
- Utilize SCADA and customer operational data to estimate failure risk in wind turbine components.
- Applied survival analysis techniques to estimate risk of failure for wind turbine components
Software & Tools: Python (numpy, scikit-learn, pandas, lifelines), Git, AWS
Four years of experience of teaching as either an assistant or instructor. Created instructional content and software tutorials for courses at the undergraduate and graduate level. See “Teaching” for more information.
Software & Tools: Python, R, Gurobi, LaTeX
Talks
Presentations & Workshops
Scalable Branch-and-Price Implementation for the CVRP with SCoOL
UBCSE Demo Days, May 2021
Branch-and-Cut Approach for Simple Graph Partitioning on Sparse Graphs
INFORMS Annual Meeting, November 2020
UB INFORMS: Gurobi Seminar Series
UB INFORMS Workshop: Fall 2019
Teaching
Assistantships
University at Buffalo
IE573: Discrete Optimization (Spring 2020, Spring 2019)
Teaching assistant for a PhD level course which covers the topics of computational complexity, algorithms and integer programming. A programming component with a commercial optimizer was included as well.
IE500: Data Analytics & Predictive Modeling (Fall 2019)
Interim course instructor (33%) and teaching assistant (67%) for a masters level data analysis and statistical learning course.
IE504: Facilities Design (Fall 2018)
Teaching assistant for a masters level course which provides analytical tools necessary for solving the problem of facility layout design and management of warehouse storage space.
IE306: Statistics for Engineers (Spring 2018)
Teaching assistant for a course which introduces undergraduate students to methodology behind statistical inferences.
IE373: Introduction to Operations Research (Fall 2017)
Teaching assistant for a course which introduces undergraduate students to topics in linear programming and deterministic optimization. A programming component with a commercial optimizer was included as well.
SUNY College at Geneseo
PHYS114: Physics Lab I (Fall 2014)
Instructor for an undergraduate physics lab course which focused on experiments testing Newton’s laws, kinematics and energy conservation.