Emilly Pereira Alves
Papers
2
Total Citations
16
H-Index
2
About
Emilly Pereira Alves is a researcher at the intersection of machine learning and bio-inspired computing, with key contributions in predictive healthcare modeling and wireless network optimization. Her work on the "Elderly KTbot" project (2020, 9 citations) introduced a logistic regression model to predict renal function outcomes in elderly kidney transplant recipients, addressing a critical gap in geriatric nephrology by enabling personalized post-transplant care. This study highlighted how machine learning can improve risk stratification for aging populations, a growing public health concern. In parallel, Alves has advanced mobile ad hoc network (MANET) reliability through her 2023 paper (7 citations) on bio-inspired multi-objective algorithms for optimizing the AODV routing recovery mechanism. By applying evolutionary principles to network resilience, she demonstrated how nature-inspired strategies can enhance communication in dynamic environments like drone swarms and vehicular networks. Her interdisciplinary approach—bridging clinical prediction and adaptive network systems—reflects a commitment to solving real-world challenges through computational innovation. With a growing citation footprint, Alves stands out for translating complex algorithms into tangible tools for healthcare and telecommunications, making her work relevant to students and researchers in applied AI, bioinformatics, and network engineering.
Research Focus
Key Achievements
Top Papers
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