Researcher at SHAHROOD UNIVERSITY of technology, Iran
Dr. Zeinab Mozafari is a Ph.D. holder in Analytical Chemistry from Shahrood University of Technology (2017-2022). Her expertise spans instrumental analysis π§ͺ (AAS, UV-Vis, ICP), drug design π (molecular docking, QSAR modeling), and chemometrics π (ANN, random forest). She leads chemistry and quality control labs in the copper mineral processing industry and lectures at Shahrood University. Dr. Mozafari has published extensively in QSAR modeling and computational chemistry, contributing to high-impact journals. Her research focuses on variable selection techniques in QSPR studies.
Publication Profile
Google Scholar
π Education
Dr. Zeinab Mozafari holds a Ph.D. in Analytical Chemistry (2017-2022) from Shahrood University of Technology, where she focused on applying penalized regression techniques for variable selection in QSAR and QSPR studies π§ͺ. Her research was supervised by Dr. Mansour Arab Chamjangali, with advisors Dr. Mohammad Arashi and Dr. Nasser Goudarzi. She earned her M.Sc. (2014-2016) in Analytical Chemistry, studying the QSAR of pyridine and pyrimidine derivatives as HIV inhibitors π¦ . Dr. Mozafari completed her B.Sc. in Pure Chemistry (2010-2014) at the University of Guilan, Rasht, Iran, building a strong foundation in chemical sciences βοΈ.
π Honors and Awards
Dr. Zeinab Mozafari has received several prestigious accolades for her outstanding academic and research achievements π. In 2021, she was recognized as the Best Ph.D. Student Researcher at Shahrood University of Technology for her contributions to analytical chemistry π§ͺ. She was also honored as the Best Ph.D. Student in Analytical Chemistry in 2018, showcasing her excellence in the field. Her academic brilliance was evident early on when she was named the Best M.Sc. Student in Analytical Chemistry in 2015. These awards highlight her dedication, innovation, and expertise in analytical and computational chemistry π¬.
Β π¬ Research Interests
Dr. Zeinab Mozafariβs research focuses on both instrumental and theoretical aspects of analytical chemistry. Her expertise in instrumental techniques π§ͺ includes Atomic Absorption Spectroscopy (AAS), Ultraviolet-Visible Spectroscopy (UV-Vis), Inductively Coupled Plasma (ICP), sample preparation, and titrimetric analysis. She is also deeply engaged in drug design π, specializing in molecular docking, molecular dynamics, and QSAR modeling, with proficiency in software like Autodock and Discovery Studio. Additionally, her work in chemometrics π involves variable selection methods, artificial neural networks, random forest, and QSPR modeling, utilizing advanced tools such as R, R-Studio, and MATLAB for predictive analytics.
Publication Top Notes
1οΈβ£ LASSO-BR-ANN for QSAR studies β Chemometrics and Intelligent Laboratory Systems, 22 citations, π
2020 π¬π
2οΈβ£ Ridge regression with new variable elimination in QSAR β Chemometrics and Intelligent Laboratory Systems, 12 citations, π
2023 π€π
3οΈβ£ Radial distribution functions in QSAR of 4-anilinoquinazoline derivatives β Structural Chemistry, 12 citations, π
2020 π§¬π
4οΈβ£ LAD-LASSO in ANN-based QSAR for potent inhibitors β Chemometrics and Intelligent Laboratory Systems, 9 citations, π
2022 π§ͺπ§
5οΈβ£ QSRR models for VOCs using ANN β Journal of the Iranian Chemical Society, 7 citations, π
2022 π‘π
6οΈβ£ SCAD as a variable selection method in ANN-based QSAR β Journal of Chemometrics, 7 citations, π
2021 πβοΈ
7οΈβ£ Ligandβreceptor interactions in QSAR using RF-ANN β Chemical Biology & Drug Design, 7 citations, π
2020 π₯π
8οΈβ£ QSAR model for 3CLPro inhibitors as anti-SARS-CoV-2 agents β SAR and QSAR in Environmental Research, 6 citations, π
2021 π¦ π
9οΈβ£ 1,2,3-triazoles-linked pyrazole carboxamides as anti-microbial and anti-cancer agents β Results in Chemistry, π
2024 π¦ π§ͺ
π LM-ANN-based QSAR model for NNRTI inhibitors β Network Modeling Analysis in Health Informatics and Bioinformatics, π
2020 π§¬π»