Youngjoo Kwon | Design of Experiments (DOE) | Research Excellence Award

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Prof. Youngjoo Kwon | Design of Experiments (DOE) | Research Excellence Award

Ewha Womans University | South Korea

Dr. Youngjoo Kwon is a highly accomplished professor in the College of Pharmacy and Graduate School of Pharmaceutical Sciences at Ewha Womans University, where she has held influential leadership roles including Director of the Ewha Drug Development Research Core Center, Chair of the Graduate School, and Director of a major convergence education program. After completing her Ph.D. in Analytical Chemistry at the University of Houston and postdoctoral training at Baylor College of Medicine, she established a research laboratory that integrates advanced analytical instrumentation such as HPLC, GC-MS, LC-MS/MS, and NMR with computational modeling and diverse biochemical, molecular, and cellular biology platforms. Her interdisciplinary research spans metabolite profiling of endogenous and xenobiotic compounds, development of isozyme-selective enzyme inhibitors, and elucidation of the non-canonical cytosolic functions of the transcription factor ELF3/ESX, particularly its interaction with MED23 in driving metastasis and drug resistance in various cancers. Additionally, her laboratory develops and evaluates small-molecule modulators against challenging disease targets related to cancer, fibrosis, and neurodegeneration. Over her prolific scientific career, Dr. Kwon has published more than 175 peer-reviewed documents, accumulated over 5,053 citations, and achieved an h-index of 35, underscoring both the breadth and lasting impact of her contributions to pharmaceutical sciences and biomedical research. Her work has appeared in leading journals and has resulted in patents and successful licensing initiatives, demonstrating strong translational value. Dr. Kwon’s achievements have earned her numerous honors from major scientific societies, including awards from the Korean Society of Applied Pharmacology, the Pharmaceutical Society of Korea, and a ministerial award from the Ministry of Trade, Industry and Energy. She is also deeply engaged in national regulatory and scientific policy activities, serving on advisory committees for the Ministry of Food and Drug Safety, the Korea Drug Development Fund, and several national research and technology evaluation boards. In addition, she contributes to the global scientific community through editorial roles in multiple international journals. Her research philosophy-rooted in mechanistic understanding, analytical innovation, and therapeutic development-continues to drive advancements in areas such as KRAS-mutant colorectal cancer, hepatic fibrosis, and metastatic progression, solidifying her standing as a leading scientist shaping next-generation drug discovery and disease-targeted interventions.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Somayeh Bahramnejad | Survival Analysis and Reliability | Editorial Board Member

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Dr. Somayeh Bahramnejad | Survival Analysis and Reliability | Editorial Board Member

Sirjan University of Technology | Iran

Dr. Somayeh Bahramnejad is an accomplished Assistant Professor in the Department of Computer Engineering at Sirjan University of Technology, recognized for her scholarly impact and multidisciplinary contributions across reliability engineering, machine learning, image processing, computer architecture, and computer networks. She completed her B.S. degree in Computer Hardware Engineering at Ferdowsi University of Mashhad, earned her M.Sc. in Computer Architecture from Amirkabir University of Technology, and later obtained her Ph.D. in Computer Architecture from the University of Isfahan. With a steadily expanding academic portfolio, she has published influential research in reputable international journals, including Microelectronics Reliability, SN Computer Science, Computing, Computers & Electrical Engineering, and Scientia Iranica, contributing to a total of six peer-reviewed journal publications. According to her Google Scholar profile, she has accumulated 29 citations, an h-index of 3, and an i10-index of 1, demonstrating the visibility and growing influence of her research contributions. Dr. Bahramnejad has significantly advanced the field through innovative work on reliability improvement of SRAM-based FPGAs, reliability analysis of CR-VANETs, and the application of machine-learning methods for evaluating digital circuit reliability. She provides academic consultancy to seven M.Sc. students, supporting high-quality research, technical development, and scholarly productivity. Her professional presence on Google Scholar and ORCID ensures transparent documentation of her academic achievements and research outputs. Committed to interdisciplinary collaboration and impactful scientific inquiry, she focuses on designing robust, scalable, and reliable computing systems informed by both theoretical insight and practical need. With her dedication to excellence, mentorship, innovation, and long-term contributions to engineering research, Dr. Bahramnejad stands as a strong candidate for distinctions such as the Reliability Analysis Award, Best Researcher Award, Best Paper Award, Women Researcher Award, and Innovative Research Award, reflecting her potential for continued leadership within the global research community.

Profiles: Scopus | Orcid

Featured Publications

Bahramnejad, S. (2025). A fuzzy-arithmetic-based reliability assessment model for digital circuits (FARAM-DC). Microelectronics Reliability.

Bahramnejad, S., Movahhedinia, N., & Naseri, A. (2024). An LSTM-based method for automatic reliability prediction of cognitive radio vehicular ad hoc networks. SN Computer Science.

Bahramnejad, S., Movahhedinia, N., & Naseri, A. (2023). A deep learning method for automatic reliability prediction of CR-VANETs. Research Square.

Bahramnejad, S., & Movahhedinia, N. (2022). A fuzzy arithmetic-based analytical reliability assessment framework (FAARAF): Case study, cognitive radio vehicular networks with drivers. Computing.

Bahramnejad, S., & Movahhedinia, N. (2022). A reliability estimation framework for cognitive radio V2V communications and an ANN-based model for automating estimations. Computing.