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This article provides a glimpse into my career journey over the years, highlighting the valuable lessons I’ve learned. It summarizes 15 key career life lessons that I encourage our younger colleagues to embrace. By putting these lessons into practice, positive outcomes are sure to follow.

We introduce an optimization assisted by a neural network (ONN) predictor to the electromagnetic community. ONN belongs to the class of the surrogate model-based optimization approaches, and approximates the objective function using a nonlinear approximator—neural network. We provide a comprehensive description of the ONN algorithm and the details of its mathematical formulations. We apply ONN to optimize three popular benchmark functions and compare its performance with some commonly used optimization algorithms, namely particle swarm optimization (PSO), genetic algorithm (GA), and Bayesian optimization (BO). For the first time, we demonstrate ONN’s applicability and effectiveness in antenna design problems by optimizing a six-element Yagi-Uda antenna and by solving a challenging 10-D dual-band slotted patch antenna constrained optimization problem. To achieve this, ONN is linked with a full-wave electromagnetic simulation solver through an application user interface. The optimized slotted patch is fabricated and measured to demonstrate how ONN can be part of the full antenna design process. Our empirical results indicate that ONN requires less objective function evaluations to reach the same qualitative point and reaches better optimal points for the same number of iterations for the studied benchmark functions and antenna optimization problems compared to the aforementioned baseline optimization algorithms.

A high-priority next-generation satellite remote sensing mission necessitates a lightweight deployable antenna that can fit in the package of low-Earth orbit (LEO) small satellites. In this work, we present the development of a 7 m $\times1.5$ m aperture C-band parabolic cylinder mesh reflector along with a 1 × 32 element linear patch array feed. The detailed and tailored mechanical design, full-wave analysis, and measurements of the reflector are elaborated. The reflector is constructed with a mesh surface with unique deployment mechanisms for weight reduction and stowage. The linear microstrip patch array feed is designed with a lightweight honeycomb substrate and is used for the breadboard testing of the parabolic cylinder reflector. The antenna achieved the desired surface accuracy and a measured gain of 42.06 dBi at 5.357 GHz, with half-power beamwidths of 0.52° and 2.35° in the two principal planes.

We present the first development of a lightweight, monolithic, circularly polarized K-band horn antenna developed using a novel charge-programmed deposition (CPD) manufacturing process. The horn has a polymer body with metalized interior surface. The CPD process creates complex geometries with programmed charged surfaces via 3-D printing and allows the deposition of metallics anywhere within the 3-D layout. Intricate internal structures of the horn, such as the meandered waveguide transition and the septum polarizer, were successfully constructed. Measured patterns of the horn demonstrated great agreement with simulations, with an axial ratio below 2.5 dB in the range of 17.5–20.5 GHz. The total weight of the horn is only 11 g, marking a significant weight reduction of around 80% compared with traditionally fabricated horns of similar size and operating frequency. The low-cost and lightweight horn antennas enabled by this process can significantly benefit mass- and cost-sensitive applications, such as small satellite and CubeSat missions.