Some of my research areas and interests

Optimization

A major part of the work currently carried out by engineers and researchers relies on designing, analyzing, operating, and optimizing systems, processes, and products. From building investment portfolios to determining the amount of fertilizer to be used on a plantation to defining the placement of components on a circuit board, optimization is a key tool for achieving performance and effectiveness. In my research, I seek to build solid expertise in optimization and its many techniques in order to recognize, formulate, and solve problems in different fields, especially in resource allocation for communication networks and in signal and image processing.

Wireless communications

Few recent technologies have had such a deep impact on modern society as wireless communications. Smartphones are now an integral part of daily life in many countries and, with the advent of 5G and the upcoming 6G, our reliance on wireless communications will only increase. For wireless communications to effectively fulfill their role, many electronic, signal processing, and communication technologies, ranging from digital modulation to Internet protocols to multi-antenna transceiver systems, had to be developed. Present and future wireless communications engineers continue to search for solutions to improve and evolve these networks. In my research, I strive to maintain an up-to-date understanding of modern wireless communications technologies while also investigating and developing new methods for this field.

Signal and image processing

In engineering and the applied sciences, signals and data that convey information from a wide variety of sources are key elements for the processing and understanding of that information and of the phenomena it describes. Signals can range from a financial time series to an audio signal captured by a microphone to a multispectral satellite image. The data carried by signals usually must be transformed or processed, for example through sampling and resampling, composition and decomposition, and filtering, in order to reveal the relevant information hidden in the signals or to generate another desired signal in response. In my research, I work to build expertise in signal and image processing techniques applied to different fields in order to extract relevant information from signals and data and support a better understanding and use of that information.

Machine learning

Machine learning is a thriving field with many practical applications, ranging from scene analysis in computer vision to book recommendation, game playing, and signal demodulation. With unsupervised, supervised, and reinforcement learning techniques, machine learning has recently excelled at solving problems that are intellectually difficult for humans but easy to describe to computers, and it has also become highly effective at tackling intuitive tasks such as voice and face recognition, especially with the growth in the computational power of modern computers and the advent of deep learning. In my research, I work to build solid expertise in modern machine learning tools, frameworks, and techniques and apply them to problems in different domains, especially wireless communications and video and image analysis.