Dimitrios Hristu-Varsakelis
Professor, Optimization and Decision Making
Department of Applied Informatics
University of Macedonia

Dimitrios Hristu-Varsakelis

is a Professor in the Department of Applied Informatics. He received his Ph.D. in Engineering Sciences and M.S. in Applied Mathematics from the Division of Engineering and Applied Sciences at Harvard University. He has held faculty positions in the Department of Mechanical Engineering and the Institute for Systems Research at the University of Maryland, College Park. He is a senior member of the IEEE and a member of SIAM.

His research interests are in the areas of optimization; signal processing and related smartphone-based applications in medicine; decision and control; and dynamics of socio-economic systems. He is also involved in the mentoring and advising of innovators in these and related areas.






Dimitrios Hristu-Varsakelis

received his Ph.D. in Engineering Sciences ('99) and M.S. in Applied Mathematics ('97) from the Division of Engineering and Applied Sciences at Harvard University. Prior to that, he was a student at Rensselaer Polytechnic Institute (M.S. EE '94) and at U.C. Berkeley (B.Sci. EECS '92). He joined the University of Maryland, College Park, in 1999 as a post-doctoral fellow with the Institute for Systems Research. During 2000-2005 he was a faculty member in the department of Mechanical Engineering and held a joint appointment with the Institute for Systems Research from 2002-2005. Since 2005 he is a faculty member in the Department of Applied Informatics at the University of Macedonia, in Thessaloniki, Greece.

Dr. Hristu-Varsakelis is a Senior Member of the IEEE and a member of SIAM. He is a co-recipient of the 1999 Eliahu Jury award from the Division of Engineering and Applied Sciences, Harvard University, and a co-recipient of the 2005 IFAC Young Author Prize.

Some of his research has dealt with problems of stability and optimal control in Networked Control Systems, bio-inspired cooperative optimal control, and provably secure cryptographic protocols. His current interests are in the areas of optimization, signal processing and related smartphone-based applications in medicine, decision and control, and dynamics of socio-economic systems. He is also involved in the mentoring and advising of innovators and startup companies in related areas.




Research

The goal of this work is to produce smartphone- and tablet-based tools and metrics for measuring the presence or progress of Parkinson's disease based on standardized hand postures and drawing patterns. Using a phone's acceleration and gyroscope sensors we are able to classify patients with good accuracy, and to assist physicians in remotely assessing a patient's condition.
We are developing stochastic and Markov-based models of the process via which economic agents (e.g. small businesses or corporations) make tax-related decisions, including whether or not to keep from disclosing income, where conditions allow. The goal is to arrive at a set of tools for evaluating tax policy and for examining the effects of proposed changes in the tax code, before they are adopted.
As concerns over global warming, pollution and resource usage keep mounting, the economy's environmental footprint is becoming an increasingly important consideration. The goal of this work is to examine a series of optimization problems which connect economic production, pollution, energy, and economic growth, and to develop computational decision-making tools which are informed by empirical data.
Using the process via which ants optimize their trails when traversing previously unknown terrain, we are exploring a progression of optimal control problems involving a collection of control systems which are attempting to discover optimal trajectories via pair-wise cooperation among neighboring agents.


















Publications

Current Teaching

Fall semester

Introduction to Mathematical Analysis.Sequences and Series.Convergence.Taylor series. Derivatives. Differentiation of multi-variable functions. Multivariable optimization.Optimization with an equality constraint.Optimization with interval bounds. Introduction to differential and difference equations. Solving linear ODEs and difference equations. Second-order systems.
Course website (COMPUS).
Introduction to Decision Making in structured and semi-structured settings. Tools and techniques from applied mathematics and optimization. Decision Trees. Utility Theory. Multicriteria Decision-making. Introduction to discrete-time dynamical systems. Dynamic Programming. Markov-based models. Value iteration. Policy iteration. Real-world decision making and factors that affect our decisions.
Course website (COMPUS).
Introduction to advanced topics in mathematical modeling and decision making through case studies and selected papers from the current literature. The course will examine problems (and their solutions) from a series of scientific fields such as bioinformatics, image processing, social networks, auctions, tax policy optimization and others.
Course website (COMPUS).

Spring semester

A tour of mathematical models, techiques and algorithms for the purpose of making rational or optimal decisions in areas ranging fromeconomics and management science, to engineering and bio-informatics, to name a few.Linear vector spaces, multi-variable optimization,  Lagrange multipliers,  KKT problems, Integer programming, Branch-and-Bound method.
Course website (COMPUS).
Algorithms used for the solution of optimization problems, as well as their applications in  scientific problems and decision making. Definitionsand concepts of Optimization, Ellipsoid Algorithm, Scaling Techniques, Interior Point Methods (path following, barrier methods, affine scaling), Exterior Point Algorithms, Presolve Techniques, Advanced Optimization Techniques in dynamic decision problems, Differntial equations with inputs, Calculus of Variations, Euler-Lagrange equations, Linear-quadratic regulators, the Maximum Principle, Hamilton-Jacobi-Bellman equation.
Course website (COMPUS).








Student Advising

Students who are in the process of selecting a thesis topic and would like to discuss a possible collaboration should first take a look in the Research (and perhaps Publications) section of my web page to get a sense of the areas I am involved in, and then contact me to discuss their background, preferences and possible topics.

Students pursuing their Bachelor Thesis (Πτυχιακή) should idealy be at the end of their 6th semester and have completed most of their coursework from past semesters. Those interested in selecting a MS Thesis topic should ideally make contact after they have completed their first semester in the Department's MSci program. Ph.D. candidates should have a mathematically rigorous background, with a BS/MS in CS, Engineering, or related field, and strong analytical ability.










Contact Details

  • (+30) 2310-891-721
  • Dimitrios Hristu-Varsakelis
    Department of Applied Informatics
    University of Macedonia
    156 Egnatia St.
    Thessaloniki, 54249, GREECE

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