招生信息美国佐治亚大学招收全奖博士

Four open positions are available for PhD students at Complex Systems Control Lab in the School of ECE at Univ. of Georgia. The positions are available as early as January 2019. The topics and the desired background are as follows:

1. Control-oriented Modeling and Predictive Control Design for Advanced Combustion Engines

The objective of this project is to develop fundamental tools for dynamic modeling and predictive control of nonlinear and stochastic systems and apply them to high-efficiency low-emission advanced internal combustion engines (ICEs) and in particular dual fuel natural gas engines. The modeling and control design will be done in the linear-parameter varying (LPV) framework.

Strong background in system identification, robust control and optimization theory is required. Prior knowledge of automotive engines modeling and control, MPC and machine learning is desired.

2. Coverage Control of Heterogeneous Multi-agent Systems in Unstructured Environments

The general goal of this project is to develop a robot-assisted field-based high throughput phenotyping system that integrates both ground and aerial vehicles to collect data and unmask plant responses that can inform a new level and quality of decision making in selection of crop genotypes for specific production conditions. A strong computational core of this research is to develop a suite of analytical tools aiming at successful deployment of teams of heterogeneous vehicles (ground and aerial) that can collaboratively collect different types of data, while minimizing energy consumption in a minimum time and meeting practical constraints pertinent to phenotyping.

Strong background in optimization theory is required. Prior knowledge of graph theory and statistical machine learning is desired.

3. Stochastic Control Design for LED Lights Intensity and Spectrum in Greenhouses

The general goal of the project is to develop models and stochastic control schemes to maximize the return on investment of lighting, based on physiological responses, crop value, energy prices, and weather in a network of greenhouses. PhD student will be working on developing a coordinated strategy for lighting control and the energy management system in a greenhouse microgrid.

Strong background in optimization theory and stochastic analysis is required. Prior knowledge of MPC and statistical machine learning is desired.

4. Anomaly Detection in Cyber-human-physical Systems using Statistical Learning

The general goal of the project is to develop distributed approaches for detecting anomalies (faults or attacks) in cyber physical systems, and in particular in smart energy systems. The development of theory and implementation of distributed real-time learning approaches is the goal, where the prior knowledge of the underlying physics-based models will be embedded in the appropriate data-driven method and used for the purpose of detecting anomalies.

Strong background in optimization theory is required. Prior knowledge of graph theory and machine learning is desired.

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A competitive research assistantship and full tuition waiver will be offered. Outstanding candidates will also be considered for other fellowships provided by the UGA College of Engineering and Graduate School.

To apply, please send an application package to javadm@uga.edu. The application should be submitted as a single PDF and include a cover letter (explicitly describing the candidate background and how they fit the open positions), a detailed CV (including the list of publications), and unofficial copies of their BS (and, if applicable, MS) transcripts.

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