Resume

Personal Information

Name: Niloofar Rahmani

Data Scientist | Analytical Chemist | Expert in Statistical Modeling & Machine Learning
Place of Birth: Takestan – Qazvin, Iran
Date of Birth: January 25, 1993

Professional Summary
 

Ph.D.-level data scientist with over 6 years of experience in advanced statistical modeling, machine learning, and big data analytics. Proven track record in data quality assurance, data preprocessing, and developing robust analytical pipelines in Python, R, and MATLAB. Specialized in working with complex, unstructured data from the food and chemical industries, with a strong foundation in digital transformation, data integration, and quality monitoring. Adept at communicating analytical insights to stakeholders and cross-functional teams.

Core Skills & Technologies
 

Big Data & Data Engineering: Data preprocessing, integrity audits, feature engineering

Programming & Analytics Tools: Python, R, MATLAB, SQL

Statistical & ML Techniques: ANOVA, PCA, LDA, SVM, Sparse Modeling, Regression, Clustering

Data Quality & Governance: Data validation, quality metrics, data pipeline optimization

Visualization Tools: Matplotlib, Seaborn, ggplot2, Power BI (familiar)

Scientific & Business Writing: Research publications, project documentation, presentations

Platforms: Jupyter, RStudio, Linux environments

Soft Skills: Problem-solving, collaboration, attention to detail, multi-tasking

Education

Ph.D. in Analytical Chemistry – Chemometrics
Tarbiat Modares University, Tehran, Iran | 2018 – 2023

Dissertation: Sparse modeling methods for metabolomics data analysis
M.Sc. in Analytical Chemistry
Imam Khomeini International University, Qazvin, Iran | 2014 – 2016

Thesis: Cyclodextrin-modified zeolite nanostructure & spectroscopic analysis
B.Sc. in Pure Chemistry
Imam Khomeini International University | 2010 – 2014

Postdoctoral Research Project

Data-Driven Food Authenticity Detection Using Machine Learning
Tarbiat Modares University | Mar 2023 – Mar 2024

Built a big data pipeline to classify edible oil samples using chemometric techniques.
Applied supervised and unsupervised machine learning algorithms for anomaly detection.
Ensured data quality during spectral acquisition and preprocessing.
Delivered reproducible code and documented analysis for publication and knowledge sharing.
Relevant Experience
 

University Teaching – Data Analytics & Statistics
Tarbiat Modares University

Courses taught: Application of Statistical Methods in Analytical Chemistry (2020), Experimental Design (2024)
Data Science & Research Projects

Classification and authentication of Iranian rice using FT-IR and sparse methods
Metabolomics-based profiling of grape seed oil using GC-MS and machine learning
Development of statistical models for food quality assessment
Honors and Awards

Ranked 1st in B.Sc. graduation – Faculty of Basic Sciences, Imam Khomeini International University, 2014

Ranked 1st in M.Sc. graduation – Faculty of Basic Sciences, Imam Khomeini International University, 2016

Admission to PhD level through academic excellence, Tarbiat Modares University, 2018

Publications
[6] Niloofar Rahmani, Ahmad Mani-Varnosfaderani, Profiling volatile organic compounds of different grape seed oil genotypes using gas chromatography-mass spectrometry and chemometric methods, Industrial Crops and Products, 2024, 222, 119928.

[5] Niloofar Rahmani, Ahmad Mani-Varnosfaderani, Excitation-emission fluorescence spectroscopy and sparse chemometric methods for grape seed oil classification and authentication, Chemometrics and Intelligent Laboratory Systems, 2023, 241, 104939.

[4] Niloofar Rahmani, Ahmad Mani-Varnosfaderani, Quality control, classification, and authentication of Iranian rice varieties using FT-IR spectroscopy and sparse chemometric methods, Journal of Food Composition and Analysis, 2022, 112, 104650.

[3] Niloofar Rahmani, Shahin Amani, Amir Bagheri Garmarudi, Mohammadreza Khanmohammadi Khorrami, The β-cyclodextrin-modified nanosized ZSM-5 zeolite as a carrier for curcumin, RSC advances, 2020, 9, 55, 32348-32356.

[2] Niloofar Rahmani, Amir Bagheri Garmarudi, Mohammadreza Khanmohammadi Khorrami, Optimizing the Template Free Fabrication Approach for Synthesis of ZSM-5 Nanozeolite, Nashrieh Shimi va Mohandesi Shimi Iran, 2018, 37, 3, 27-36.

[1] Niloofar Rahmani, Amir Bagheri Garmarudi, Mohammadreza Khanmohammadi Khorrami, Fabrication and Evaluation of β-Cyclodextrin Modified Nano Zeolite as Carrier for Curcumin, Nanoscale, 2018, 5, 1, 57-66.

Conference Presentations
[4] Niloofar Rahmani, Ahmad Mani-Varnosfaderani, Rapid authentication and classification of grape seed oil using fluorescence spectroscopy combined with sparse classification and regression methods, 9th Iranian Biannual Conference of Chemometrics, Qazvin, Iran, Oct. 2023. (Speaker).

[3] Niloofar Rahmani, Ahmad Mani-Varnosfaderani, Untargeted metabolic profiling of volatile compounds of grape seed oil using gas chromatography coupled with mass spectrometry, 9th Iranian Biannual Conference of Chemometrics, Qazvin, Iran, Oct. 2023.

[2] Niloofar Rahmani, Ahmad Mani-Varnosfaderani, Classification of Iranian rice varieties using FTIR spectroscopy and sparse linear discriminant analysis, 8th Iranian Biannual Conference of Chemometrics, Tarbiat Modares University, Tehran, Iran, Oct. 2021.

[1] Niloofar Rahmani, Amir Bagheri Garmarudi, Mohammadreza Khanmohammadi Khorrami, Preparation and optimization of nano zeolite ZSM-5 using experimental design and spectroscopy and its modification with β–cyclodextrin as carrier for curcumin, 24th ISC Seminar of Analytical Chemistry, Azarbaijan Shahid Madani University, Tabriz, Iran, August, 2017.

Workshops and Training Courses
·       1st Winter School of Chemometrics – Sharif University of Technology, 2019

·       3rd Winter School of Chemometrics – Sharif University of Technology, 2021

·       4th Winter School of Chemometrics – Sharif University of Technology, 2022

·       2nd Chemometrics Symposium – University of Tabriz, 2022

·       MATLAB Programming Course – University of Tehran, 2018

·       R Programming Course – Maktabkhooneh, 2020

·       Python Programming Course – National Institute for Oceanography and Atmospheric Science, 2023

International Journal Reviewer
·       Chemometrics and Intelligent Laboratory Systems (Elsevier Publications)

·       Journal of Food Composition and Analysis (Elsevier Publications)

·       Journal of Chemometrics (Wiley Publications)

·       Journal of Chromatography A (Elsevier Publications)

·       Current Research in Food Science (Elsevier Publications)

·       Journal of Fluorescence (Springer Publications)