Curriculum Vitae

Aerospace Engineering PhD candidate at the University of Texas at Austin and Mechanical Engineering graduate (BS/MS with highest honors) from the National Technical University of Athens with a wide mathematical and programming background in control theory, computational engineering, and machine learning. I am currently working on ML for model reduction and control of high-dimensional, nonlinear systems, with an emphasis on turbulent flows.

Some of the topics that I have worked on include stochastic optimal control, high-performance computing, deep learning models for trajectory prediction, reinforcement learning, fluid dynamics, adjoint-based aerodynamic shape optimization, and computational geometry. I have also worked extensively on environment perception and estimation problems in the industry for automotive applications, such as Radar-based localization and mapping, computer vision/HD map fusion, and deep learning for radar-only object detection. My coding skills include an advanced grasp of object-oriented languages, such as C++ and Python, as well as Fortran, and Matlab. I am also comfortable with parallel computing on high-performance computing clusters.

Education

The University of Texas at Austin Austin, TX
MS/PhD in Aerospace Engineering May 2023

• Master’s and Doctoral student in the Department of Aerospace Engineering and Engineering Mechanics.
• GPA: 4.00/4.00
• Relevant Coursework: Reinforcement Learning, Robot Learning, Stochastic Optimal Control, Autonomous Robots, Statistical Estimation Theory, Linear Systems, Optimal Control, Nonlinear Dynamics, Dynamics of Turbulence, Multivariable Control Systems, Fluid Mechanics

National Technical University of Athens Athens, Greece
BS/MS, Mechanical Engineering February 2018

• Bachelor of Science & Master of Science; 5-year joint degree; 300 ECTS
• GPA: 9.06/10.00 (early graduate with highest honors; top 10 among undergraduate class of 180 students)
• Concentration: Air and Ground Transport Vehicles
• Relevant Coursework: Computational Fluid Dynamics, Optimization Methods in Aerodynamics, Computational Methods in Turbomachines, Flight Dynamics, Control Systems, Microprocessor-Based Control
• Thesis: “Deformation of Computational Meshes Using Delaunay Graph Parameterization – Applications in the Adjoint-Based Aerodynamic Shape Optimization”

Work Experience

Aptiv Agoura Hills, CA
Radar Machine Learning Intern May 2022 - August 2022

• Worked on deep learning for object detection from low-level radar data.
• Trained and compared the performance of object detection models with different backbones, detection heads, and loss functions, leading to improved detection precision over the previously-used models.
• Created MMRadar: an extension of MMDetection & MMRotate libraries for radar-only object detection.

Remote, USA
Environment Perception Engineering Intern June 2021 - August 2021

• Remote internship with the Road Model Team.
• Developed a Radar-based Simultaneous Localization and Mapping (SLAM) framework that uses pose graphs and loop closures to create a Radar occupancy gridmap from scratch.
• Integrated occupancy gridmap updates from multiple visits of the same area in the SLAM framework.
• Developed ROS pipeline in Python and C++.

Remote, USA
Environment Perception Engineering Intern June 2020 - July 2020

• Remote internship with the Road Model Team.
• Developed a sensor fusion framework for lane marker estimation from vision, HD maps, GNSS, and odometry information, along with necessary data pipelines and visualization tools in Python.

Research Experience

The University of Texas at Austin Austin, TX
Graduate Research Assistant August 2018 - Present

• Developing reinforcement learning algorithms for control of high-dimensional systems, with an emphasis on turbulent flows.
• Main contributor to two collaborative National Science Foundation grants worth a total of nearly $1M.
• Combining transformer models with dynamics-aware Gaussian processes for trajectory prediction.
• Developing large-scale numerical simulations of turbulent boundary layers.
• Designing model-predictive control algorithms and reduced-order models for control of coherent structures in turbulent flows.
• Developed sparse dynamic mode decomposition for control and estimation of high-dimensional systems.
• Proposed a multiple-model dynamic mode decomposition framework for flowfield and parameter estimation.
• Developing algorithms for stochastic optimal control of nonlinear systems using Gaussian processes.
• Contributed to the development of distributed covariance steering algorithms.

National Technical University of Athens Athens, Greece
Undergraduate/Associate Researcher May 2017 - July 2018

• Group: Parallel CFD and Optimization Unit
• Research interests:
  • Adjoint-based optimization of partial differential equations (e.g. aerodynamic shape optimization).
  • Grid generation and manipulation; computational geometry.
  • Computational fluid dynamics (CFD).
• Developed and programmed a fast dynamic grid morpher based on Delaunay triangulation parameterization for OpenFOAM in C++ and coupled it with the adjoint-based aerodynamic shape optimization software.
• Set up a fluid-structure interface between ANSYS and an in-house CFD software for simulating the deformation of an inflatable wing.
• Programmed an adjoint error-based grid refinement tool for the OpenFOAM environment for use in automatic mesh generation and for improving the accuracy of computing functionals of interest.

Skills

• Programming: Proficient in C/C++, Python, Matlab, Fortran, MPI, OpenMP, Unix Scripting
• Libraries/Tools: PyTorch, JAX, ROS, GPyTorch, GTSAM, Eigen (C++), SLURM, Git, OpenCV, CGAL
• Other Tools: LaTeX, MS Office (ECDL Expert), Solidworks, ANSYS, , OpenFOAM, Arduino
• Languages: English (fluent), Greek (native)

Publications

Journal Articles

• Tsolovikos, A., Suryanarayanan, S., Bakolas, E., Goldstein, D., (2020), “Model predictive control of material volumes with application to vortical structrues”, AIAA Journal, 2021.
• Tsolovikos, A., Bakolas, E., Suryanarayanan, S., Goldstein, D., (2020), “Estimation and control of fluid systems using sparsity-promoting dynamic mode decomposition with control”, IEEE Control Systems Letters.
• Gkaragkounis, K., Papoutsis-Kiachagias, E., Tsolovikos, A., Giannakoglou, K., (2020), “The effect of grid displacement methods on continuous adjoint-based sensitivity derivatives in aerodynamic and conjugate heat transfer problems”, Engineering Optimization.

Conference Papers

• Jariwala, A., Tsolovikos, A., Suryanarayanan, S., Goldstein, D. B., and Bakolas, E. (2022). On the effect of manipulating Large Scale Motions in a Boundary Layer. In AIAA AVIATION 2022 Forum.
• Tsolovikos, A., Suryanarayanan, S., Bakolas, E., and Goldstein, D. B. (2022). Multiple Model Dynamic Mode Decomposition for Flowfield and Model Parameter Estimation. In AIAA SCITECH 2022 Forum (p. 2427).
• Tsolovikos, A., Bakolas, E. (2021), “Cautious Nonlinear Covariance Steering using Variational Gaussian Process Predictive Models”, to be presented at the Modeling, Estimation and Control Conference 2021.
• Saravanos, A.D., Tsolovikos, A., Bakolas, E. and Theodorou, E.A. (2021), Distributed Covariance Steering with Consensus ADMM for Stochastic Multi-Agent Systems, Robotics: Science and Systems 2021.
• Bakolas, E., Tsolovikos, A., (2020), “Greedy finite-horizon covariance steering for discrete-time stochastic nonlinear systems based on the unscented transform”, American Control Conference 2020, Denver, CO, July 1-3, 2020.
• Tsolovikos, A., Suryanarayanan, S., Bakolas, E., Goldstein, D., (2020), “Toward model-based control of near-wall turbulent coherent structures”, AIAA SciTech 2020, Orlando, FL, January 6-10, 2020.

Talks

• “Control of Large-Scale Motions in Turbulent Boundary Layers”, Caltech, August 2, 2022, Pasadena, CA.
• “Control of Large-Scale Motions in Boundary Layers”, APS DFD 2021, November 22, 2021, Phoenix, AZ.
• “Model Predictive Control of Near-Wall Turbulent Coherent Structures”, UT Austin ASE Seminar, February 13, 2020, Austin, TX.

Teaching Experience

Teaching Assistant, The University of Texas at Austin

• Assisted in the Linear Systems course by grading and holding review sessions (Spring 2019, Fall 2020 & Spring 2021).
• Assisted in the Compressible Flow course by lecturing, grading and holding office hours (Spring 2019).
• Taught and supervised the Low-Speed Aerodynamics Lab; graded lab reports, and held office hours (Fall 2018).
• Assisted in the Applied Aerodynamics course by grading homework and holding office hours (Fall 2018).

Awards and Fellowships

• “Best ASE/EM Graduate Peer Mentor” award (Spring 2022).
• *“Graduate Dean’s Prestigious Fellowship Supplement” Fellow
• (September 2020)
• “A. Onassis Foundation Scholarship” for Ph.D. studies in Aerospace Engineering (September 2020 - May 2023, valued at over $40,000)
• “Hellenic Professional Society of Texas Scholarship” recipient (February 2020)
• “Gerondelis Foundation Graduate Study Scholarship” recipient (December 2019)
• “Graduate Continuing Fellowship” awarded by the Graduate School at the University of Texas at Austin (June 2019 – May 2020, $44,000 toward tuition and stipend)
• “KARY” award for the highest GPA in the Mechanical Engineering School during the academic year 2015 – 2016 (September 2017)
• “Thomaideio” award for the highest GPA in the $5^{th}$ and $6^{th}$ semesters in the Mechanical Engineering School (September 2017)
• “Christos Papakyriakopoulos” award for the highest score in mathematics courses (September 2015)
• “A Great Moment for Education” award for the highest score in University Entrance Examinations, Eurobank (2013)

Last update: September 17, 2022