Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests by Kenneth V. Price (17877002)

“…<p>Non-parametric tests can determine the better of two stochastic optimization algorithms when benchmarking results are ordinal—like the final fitness values of multiple trials—but for many benchmarks, a trial can also terminate once it reaches a prespecified target value. …”

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…Correlation results align with the experimental data, affirming the applicability of our framework. Finally, the algorithm is employed in a CO₂ capture case study to generate and select the best-performing novel ILs, which exhibit behavior consistent with established ILs in the literature.…”

The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)

UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices by Samir, Moataz

“…Next, we propose an extension algorithm to further minimize the UAV’s flight distance for cases where the initial and final UAV locations are known a priori. …”
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Towards Resiliency Enhancement of Network of Grid-Forming and Grid-Following Inverters by Silvanus D'silva (19273852)

“…Finally, the proposed scheme is experimentally validated on a small-scale hardware testbed.…”