Serena Barile | Industrial Biotechnology | Best Researcher Award

Published on by Biotechnology Scientist

Dr. Serena Barile | Industrial Biotechnology | Best Researcher Award

Research Fellow at University of Bari Aldo Moro | Italy

Dr. Serena Barile, a postdoctoral research fellow at the University of Bari Aldo Moro, conducts advanced research in biochemical sciences, focusing on metabolomic profiling, mitochondrial bioenergetics, and molecular diagnostics. Her studies integrate cutting-edge techniques such as HPLC, LC-MS, and GC-MS to explore cellular metabolism and biochemical mechanisms underlying metabolic disorders. Dr. Barile’s research has led to notable publications in Acta Pharmacologica Sinica, Journal of Lipid Research, Biochimica et Biophysica Acta Bioenergetics, Bioresource Technology, and Scientific Reports, addressing critical issues related to mitochondrial transporters, lipid remodeling, and disease biomarkers. Her multidisciplinary expertise bridges molecular biology, biochemistry, and biotechnology, contributing to innovations in metabolic disease diagnostics and cellular bioenergetics. She has presented her findings at national and international biomembrane and bioenergetics conferences, showcasing her active engagement in the scientific community. With 8 citations, 5 indexed publications, and an h-index of 2 in Scopus, Dr. Barile exemplifies an emerging researcher with strong analytical capabilities, innovative scientific thinking, and a commitment to advancing biomedical and metabolic research through integrative experimental and computational strategies.

Profiles : Scopus | ORCID

Featured Publications

Cafferati Beltrame, L., Sgobba, M. N., Laera, L., Scaglione, V., Todisco, S., Barile, S., Francavilla, A. L., De Luca, D. I., Montaruli, M., Porcelli, V., et al. (2025). Combined in silico / in vitro approaches for identifying modulators of the activity of the p.Tyr110Cys Carnitine O-Acetyltransferase (CRAT) variant associated to an early onset case of Leigh syndrome. Acta Pharmacologica Sinica.

Porcelli, V., Barile, S., Capobianco, L., Barile, S. N., Gorgoglione, R., Fiermonte, G., Monti, B., Lasorsa, F. M., & Palmieri, L. (2024). The mitochondrial aspartate/glutamate carrier does not transport GABA. Biochimica et Biophysica Acta (BBA) – Bioenergetics.

Parrella, P., Barbano, R., Jonas, K., Fontana, A., Barile, S., Rendina, M., Lo Mele, A., Prencipe, G., Ciuffreda, L., Morritti, M. G., Valori, V. M., Graziano, P., Maiello, E., Copetti, M., Pichler, M., & Pasculli, B. (2024). Tumor suppressor miR-27a-5p and its significance for breast cancer. Biomedicines.

Castellaneta, A., Losito, I., Porcelli, V., Barile, S., Maresca, A., Del Dotto, V., Losacco, V., Guadalupi, L. S., Calvano, C. D., Chan, D. C., Carelli, V., Palmieri, L., & Cataldi, T. R. I. (2024). Lipidomics reveals the reshaping of the mitochondrial phospholipid profile in cells lacking OPA1 and mitofusins. Journal of Lipid Research.

Castellaneta, A., Porcelli, V., Losito, I., Barile, S., Maresca, A., Del Dotto, V., Guadalupi, L. S., Calvano, C. D., Carelli, V., Palmieri, L., & Cataldi, T. R. I. (2023). Methyl carbamates of phosphatidylethanolamines and phosphatidylserines reveal bacterial contamination in mitochondrial lipid extracts of mouse embryonic fibroblasts. Scientific Reports.

 

Ifza Shad | Industrial Biotechnology | Best Researcher Award

Published on by Biotechnology Scientist

Ms. Ifza Shad | Industrial Biotechnology | Best Researcher Award

PhD at University of Science and Technology of China | China

Ms. Ifza Shad is an emerging AI researcher specializing in computer vision, deep learning, and real-time object detection, with strong contributions to medical image analysis and intelligent automation. She completed her MS in Computer Science at Central South University, China, focusing on the development of real-time litter detection models for surface and aquatic environments, and previously earned a BS (Hons) in Computer Science from the University of Central Punjab, Pakistan, graduating as a gold medalist. Her professional experience includes serving as a Computer Vision Engineer at ITSOLERA Pvt, where she led research in medical image analysis for fracture detection and visual search systems for precision agriculture, and as a Data Analyst at Motive, USA, where she excelled in data annotation and analytics. Ifza has authored multiple research papers, including Deep Learning-Based Image Processing Framework for Efficient Surface Litter Detection (Journal of Radiation Research and Applied Sciences, 2025), Attention-Driven Sequential Feature Fusion Framework for Effective Brain Tumor Diagnosis (Significances of Bioengineering and Biosciences, 2025), and An Attention-Fused Architecture for Brain Tumor Diagnosis (Biomedical Signal Processing and Control, 2024). Her ongoing projects explore lightweight YOLO architectures for aquatic litter detection and driver distraction monitoring. With a growing Scopus profile demonstrating increasing academic visibility through 5 publications, citations, and an evolving h-index, she continues to advance AI-driven solutions that integrate sustainability, healthcare, and safety.

Profile: ORCID

Featured Publications

Shad, I. (2025). Deep learning-based image processing framework for efficient surface litter detection in computer vision applications. Journal of Radiation Research and Applied Sciences.

Shad, I. (2025). Attention-driven sequential feature fusion framework for effective brain tumor diagnosis. Significances of Bioengineering and Biosciences.

Shad, I., & Co-authors. (2024). An attention-fused architecture for brain tumor diagnosis. Biomedical Signal Processing and Control.

Shad, I. (2025). ALD-Yolov9c: Lightweight architecture for aquatic litter detection in dynamic environments. IEEE. (Submitted).

Shad, I. (2024). Overcoming misinformation: Advanced detection of fake news by integration of K-fold stacked ensemble. International Journal of Software Engineering and Knowledge Engineering (IJSEKE). (Under review).