Data Science
Resume:
Nafiseh Mollaei
Chicago, IL
+1-312-***-**** *******.*******@*****.***
PROFESSIONAL SUMMARY
Experienced AI researcher with over 6 years of developing and deploying machine learning models in diverse applications. Demonstrated expertise in NLP, deep learning, and LLM-driven projects that extract actionable insights and drive production-level solutions. Proficient in designing innovative models and collaborating across teams to ensure data-driven decisions and responsible AI implementation.
KEY SKILLS
•Technical Tools: Python, TensorFlow, PyTorch, scikit-learn, Plotly, Numpy, Pandas, R, MATLAB, SQL, Git, GitHub
•Machine Learning & AI: Neural Networks, Deep Learning, NLP, Computer Vision, LLMs, Prompt Engineering, Multimodal analy- sis, Machine Learning, Explainability frameworks, Fairness testing, Bias detection, Privacy-preserving ML, Robustness evaluation
•Research & Domain Expertise: Statistics, Econometrics, Predictive analytics, Doctorate, Computer Science, Electrical Engineering, ML documentation frameworks
Work Experience
Northwestern University Nov 2024 - Present
Postdoctoral Scholar\ Research Scientist Chicago, IL
•Analyzed integration of VLLMs in healthcare applications using Python and deep learning frameworks to enhance cell detection efficiency by 10-20%, aligning with ML model prototyping and production deployment.
•Leveraged generative AI to process complex biomedical datasets, extracting actionable insights for treatment strategies and supporting data-driven decision-making across interdisciplinary teams.
University of Chicago Oct 2023 - Oct 2024
Postdoctoral Scholar\ Research Scientist Chicago, IL
•Evaluated clinical notes using LLMs to automate data annotation, enhancing accuracy and efficiency in information processing reflective of natural language processing applications.
•Applied NLP and predictive modeling techniques to streamline data processing, supporting efficient clinical decision-making and demonstrating effective collaboration with technical teams.
Loyola University Chicago Apr 2023 - Oct 2023
Postdoctoral Research Associate Chicago, IL
•Developed advanced AI methodologies using Large Language Models to improve accuracy in clinical phenotyping and disease subtyping by 10%, showcasing expertise in applied machine learning and model prototyping.
Volkswagen Autoeuropa Jul 2018 - Mar 2022
Research Assistant Setubal, Portugal
•Led an AI team to develop health monitoring systems for workplace safety, incorporating machine learning models that improved occupational profiles and predictive analytics.
•Implemented explainability techniques to deliver transparent insights from complex AI algorithms, aligning with fairness testing and bias detection methods.
•Collaborated with legal and ethics teams to ensure compliance with privacy regulations and industry standards, reinforcing a data-driven but secure approach.
•Deployed Python-based machine learning models in production environments using cloud platforms, enhancing diagnostic efficiency while meeting Microsoft security requirements.
Nova University Lisbon Jul 2018 - Mar 2022
Research Assistant Lisbon, Portugal
•Analyzed occupational health data using advanced AI methods to predict workers' Functional Work Ability (FWA) and generate Occupational Health Protection Profiles (OHPP), demonstrating robust applied analytics.
•Developed a recommender system model for industrial worker injury diagnosis using Association Rules, achieving 84% accuracy through targeted machine learning application.
•Created and deployed a real-time injury prognosis dashboard utilizing Dash and Plotly, reducing data processing time by 50% and supporting rapid, data-driven insights.
Centro ALGORITMI, University of Minho Feb 2017 - Jul 2018
Research Assistant Guimarães, Portugal
•Investigated multisensorial integration in gait and postural control for healthy subjects and patients with neurological diseases, contributing to applied research in multimodal analysis.
•Analyzed visual, somatosensory, and auditory systems' roles in postural control, ensuring precise central integration and reweighting mechanism evaluation.
•Identified distinctive postural patterns in neurological disorders and developed fall risk assessment markers that reduced fall incidents by 5.4%, reinforcing predictive analytics in applied settings.
MG Health Tech Jul 2024 - Feb 2025
AI Advisor Dallas, USA
•Developed a GIS-based clinical reference tool for Illinois using Python and Plotly, enhancing physicians' decision-making and aligning with a data-driven approach in applied AI solutions.
Value for Health CoLAB Jul 2019 - Apr 2021
Research Assistant Lisbon, Portugal
•Created explainable AI solutions for ICU patient risk assessment, increasing clinician trust and integrating privacy-preserving ML techniques.
•Designed secure data pipelines for handling sensitive medical information, ensuring compliance with data protection regulations and supporting ethical AI deployment.
•Collaborated with cross-functional teams to establish ethical guidelines for AI in hospitals, reflecting strong teamwork and mentoring in data-driven projects.
EDUCATION
• Generative AI with Large Language Models: DeepLearning.AI, 2025
• Structuring Machine Learning Projects: DeepLearning.AI, 2025
• Neural Networks and Deep Learning: DeepLearning.AI, 2025
• Improving Deep NNs: Hyperparameter Tuning, Regularization and Optimization: 2025
• Algorithmic Toolbox: University of California, San Diego via Coursera, 2025
• Product Management: An Introduction: IBM via Coursera, 2025
• Leadership and Management in Action Program: University of Chicago, 2024
• Foundations: Data, Data, Everywhere: Google, 2023
NOVA University Lisbon, Portugal
Jul 2018 - Jul 2022
Ph.D. Scholar, Biomedical Engineering
Islamic Azad University, Iran
Sep 2011 - Jul 2014
M.Sc., Electrical Engineering- Control
Islamic Azad University, Iran
Sep 2008 - Jul 2011
B.Sc., Electrical Engineering- Electronic
PROFESSIONAL CERTIFICATIONS
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