ORNL Features Profile of ME alumnus, Andreas Malikopoulos

Malikopoulos

The Oak Ridge National Laboratory (ORNL) has recently highlighted the career of ME alumnus, Andreas Malikopoulos, PhD. Malikopoulos is a part of the Research and Development Staff in the Energy and Transportation Sciences Division at the lab. He graduated in 2008 with a PhD, under the supervisor of his advisor, ME Professor Panos Papalambros, the Donald C. Graham Professor of Engineering.

ORNL, today, carries out projects for the U.S. Department of Energy. The lab’s goal, in summary, is to increase the availability of clean energy, preserve the environment, and aid efforts in national security.

Amidst other projects, Malikopoulos currently observes functionalities of the human brain, and investigates how they can be used to develop biologically inspired control systems.

Malikopoulos began his career with ORNL after the company honored his early-career leadership ability and break-through research findings with the Alvin M. Weinberg Fellowship. The Fellowship funds research for two years, but recipients have the option to further their career with the lab afterward.

Since ORNL recognized Malikopoulos’ potential with the company, he has not only continued his research there, but has also become the president of the new ORNL Postdoc Association (ORPA), which focuses on creating a sense of community, making necessary resources available, and representing the Postdoctoral Researchers in the ORNL community.

Malikopoulos shared his research from ORNL with other leading scientists and engineers at the American Control Conference, held in Washington D.C. last month. The premier scientific and engineering conference focuses on the advancement of control theory and practice, and its research presentations have lent to its international prestige.

At the conference, Malikopoulos presented two research papers, titled, “Stochastic Optimal Control for Series Hybrid Electric Vehicles” and “Power Management Control of HEVs and PEVs: State of the art and future opportunities.”

He addressed the problem of optimizing online the supervisory control in a series hybrid configuration by modeling its operation as a controlled Markov chain using an average cost criterion to create an equilibrium control policy.

In addition to these efforts, Malikopoulos’ work has made him a leading figure in enabling automobile engines to function as their own autonomous intelligent system. This system has the ability to learn its optimal calibration in real-time, operating autonomously even when someone is in the driver’s seat.

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