Machine Learning Artificial Intelligence

Experienced professional with dual master’s degrees in Artificial Intelligence and Organic Chemistry, combining over a decade of biopharma research with AI-driven problem-solving. Skilled in machine learning, data analysis, and robotics programming, with a passion for advancing medicine design through innovative technology. Successfully engineered bioadhesive hydrogels at UCLA, enhancing their mechanical properties and biocompatibility for medical applications.

Artificial Intelligence: Machine Learning, Neural Networks, Natural Language Processing (NLP), Predictive Modeling, Time Series Analysis, Data Mining

Programming and Development: Python, PyTorch, Robotics Programming, Mobile App Development Cloud Computing and IoT: AWS SageMaker, Cloud Computing, Internet of Things (IoT) Laboratory and Biopharma Expertise: Quality Control and Assurance, Protein Purification, Microbiological Analysis, Biomaterials Synthesis (bioadhesive hydrogels: chemical analysis using NMR, mechanical property evaluation including shear stretch, tensile pressure, adhesive strength, and toxicity testing through cell culture), Research and Process Optimization (UCLA-specific contributions). Project Management and Collaboration: Analytical Thinking, Problem-Solving, Teamwork, and Collaboration

SFO Air Traffic Passenger Prediction Using Machine Learning and Deep Learning Developed a time series forecasting model using Supervised Machine Learning (Linear Regression, SARIMAX, Prophet) and Deep Learning (LSTMs, Transformers) to predict monthly passenger counts at SFO. Conducted EDA and demonstrated that Linear Regression with seasonal adjustments outperformed advanced models. Featured in the 2024 Capstone Chronicles as one of the top projects in the MS-AI program. Tools: Python, TensorFlow, scikit-learn, Facebook Prophet, Jupyter Notebook House Price Prediction

Developed a Supervised Machine Learning system to predict house prices in the USA, utilizing Amazon SageMaker for real-time deployment and monitoring via CloudWatch. Conducted EDA on ~81,747 entries, implemented feature engineering, and trained models like Linear Regression, Random Forest, and Gradient Boosting, achieving RMSE within 10% of the average price. Deployed the model via a REST API using Flask. Tools: Python, scikit-learn, Flask, AWS S3, Kaggle Chatbot with BERT

Developed a chatbot using Natural Language Processing (NLP) and Deep Learning with the BERT model for context-aware, multi-turn conversations. Trained on the SQuAD dataset, the system adapted to contextual queries and was evaluated using F1 and BLEU scores. Tools: Python, TensorFlow, Hugging Face Transformers, SQuAD Bird Species Identification

Developed a deep learning system for bird species classification using CNN architectures like VGG16, EfficientNetB0, and AlexNet. Trained on the "Birds 525 Species" dataset (89,885 images) with techniques like Batch Normalization and Dropout to enhance accuracy and generalizability. Tools: Python, TensorFlow, Keras, scikit-learn, Birds 525 Dataset Music Classification

Developed a deep learning system using CNNs to classify musical pieces from spectrograms generated from MIDI files. Preprocessing included audio conversion, spectrogram creation with librosa, and data augmentation. Trained a custom CNN on labeled spectrograms and evaluated using accuracy and F1-score. Tools: Python, TensorFlow, librosa, MIDI, Keras

Sr. Pre-PCR TechPerkinElmer – Valencia, CA (11/2020 to 02/2021)

Evaluated potential software applications for compatibility with existing systems, recommending optimal solutions to enhance laboratory workflows.

Contributed actionable insights during strategy sessions, increasing team engagement and project efficiency.

QC Analyst in Microbiology ATARA Biopharmaceutical Co – Thousand Oaks, CA (11/2019 to 09/2020)

Developed and maintained comprehensive quality assurance procedure documentation, ensuring compliance with industry standards.

Authored and updated procedural checklists and job aids, reducing process errors by 15%. Postgraduate - Research Assistant at University of California Los Angeles (UCLA) – Los Angeles, CA

(10/2018 to 07/2020)

Engineered bioadvective collagen with improved adhesive properties

Independently maintained critical laboratory equipment, reducing operational costs by 10%.

Organized and streamlined research materials

Analyzed the mechanical and chemical properties of synthesized samples to support project objectives. QA/QC Micro AnalystDendreon Pharmaceutical Co – Seal Beach, CA (03/2019 to 11/2019)

Identified and implemented process improvements across cross-functional teams, enhancing operational efficiency.

Developed and standardized comprehensive documentation for standard operating procedures, fostering improved knowledge sharing.

Oversaw document management systems, enabling faster and more accurate data retrieval. Research TechnologistMayo Clinic – Rochester, MN (09/2016 to 09/2018)

Designed and executed research protocols, ensuring timely completion of advanced biopharmaceutical projects.

Cultured and analyzed aged cancer cell specimens, contributing to breakthrough project developments.

Managed laboratory operations and trained postdoctoral researchers in advanced experimental techniques.

Maintained 100% data accuracy and entering critical sample records. Supervisor/Specialist Pooyesh Daru Biopharmaceutical Co – Tehran, Iran (11/2010 to 02/2015)

Protein purification process optimization.

Led teams to consistently meet and exceed weekly and monthly production targets.

Collaborated on obtaining regulatory approvals for new production lines, driving company expansion.

Maintained contamination-free processes during sterilization shutdowns, ensuring uninterrupted operations.

Implemented waste reduction strategies, increasing output and minimizing costs. M.Sc: Applied Artificial Intelligence; GPA: 3.7/4.0 University of San Diego – San Diego, CA, USA (2023 to 2024) M.Sc : Organic Chemistry; GPA: 3.72/4.0

Azad University Tehran Central – Tehran, Iran (2012 to 2014) B. Sc: Applied Chemistry; GPA: 3.7/4.0

Azad University Tehran Central – Tehran (2006 to 2010)

LinkedIn: https://www.linkedin.com/in/jamilehjahangiry/

GitHub: https://github.com/jjahangiry

Department Leadership (Pooyesh Daru Biopharmaceutical Co):

Led departmental efforts to exceed weekly and monthly production targets.

Optimized methods and processes to achieve protein purification with 99.9% purity.

Collaborated with other departments to secure approvals for new production lines and foster organizational goals.

Hiring and training new staff

Team Management and Training at Mayo Clinic:

Supervised and trained postdoctoral researchers

Conducted staff training and facilitated new hire orientation sessions in various roles.

Enhanced team efficiency and organized workflows to minimize waste and maximize output.

Sorting samples and their data

7th Annual Workshop on Micro- and Nanotechnologies for Medicine: Emerging Frontiers and Applications

UCLA, Center for Minimally Invasive Therapeutics (2019)

Bioinformatics

Udemy, Instructor: Issac Alfred (2020)

Machine Learning Guide: Learn Machine Learning Algorithms Udemy, Instructor: Grid Wire (2020)

Complete Python Bootcamp: Go from Zero to Hero in Python 3 Udemy, Instructor: Jose Portilla (2020)

Droplet-Based Microfluidics in Biomedical Applications

Biofabrication, Volume 14, Issue 2, January 2022

DOI: 10.1088/1758-5090/ac39a9

Engineering Tough, Injectable, Naturally-Derived, Bioadhesive Composite Hydrogels

Advanced Healthcare Materials, Published April 24, 2020

DOI: 10.1002/adhm.201901722

Application of Methodological Analysis for Hydrocortisone Nanocapsulation in Biodegradable Polyester and MTT Assay

Polymer Science, Series A, Volume 60, Pages 770–776, February 6, 2019

DOI: 10.1134/S0965545X18070027

Contact this candidate