Machine Learning Mental Health

ARYAN PATIL

+1-217-***-**** *******@********.*** linkedin.com/in/patil-aryan/ github.com/patil-aryan EDUCATION

1. Graduate: Master of Science in Information Management Aug 2023 – May 2025 University: University of Illinois Urbana-Champaign. GPA: 3.94/4 Champaign, IL 2. Undergraduate: Bachelor of Engineering in Mechanical Engineering July 2019 – May 2023 University: Mumbai University. CGPA: 8.94/10 Mumbai, India WORK EXPERIENCE

Graduate Research Assistant, University of Illinois Urbana-Champaign Jan 2024 – May 2024 Project: Prediction of physical & mental health symptoms using wearable data for multiple sclerosis.

• Cleaned and preprocessed 10 GB+ of multi-modal wearable sensor data (100+ participants) from wearable sensors, ensuring data quality and consistency for subsequent analysis.

• Identified key patterns in heart rate variability across MS subtypes using EDA and visualization techniques, which guided feature selection, reducing the feature set by 20%.

• Evaluated and optimized machine learning algorithms (SVM, Random Forest) for hyperparameter tuning. Software Development Intern, Tata Consultancy Services Aug 2022 – May 2023 Project: Automate Identification and Recognition of Handwritten Text from an Image.

• Employed a Convolutional Recurrent Neural Network (CRNN) architecture to address both image-based sequence recognition and individual character recognition challenges present in OCR.

• Conducted extensive model training with a set of 7850 images and 876 validation images, refining the system for higher accuracy.

• Achieved a recognition accuracy rate of 91.72%, demonstrating the effectiveness of the implemented technologies. PROJECTS

Predicting Student Dropout Risk using Machine Learning Algorithms Jan 2024 – May 2024

• Developed a machine learning model for student dropout risk prediction, achieving 85.9% accuracy and surpassing the reference research paper by 43.26%.

• Significantly enhanced model performance by addressing class imbalance using SMOTE and ADASYN oversampling techniques. This resulted in a 10% increase in recall, addressing potential biases.

• Evaluated and compared the performance of multiple machine learning algorithms, including Logistic Regression

(L1 & L2), Random Forest, and XGBoost, based on accuracy, precision, recall, and F1-score. Analyzing the factors that have influenced the price of Cryptocurrencies over the years Jan 2024 – May 2024

• Developed a modular Python library of reusable functions for financial data analysis and ensured code clarity, maintainability, and robust testability with doctests.

• Performed Data Analysis and Data Visualization using Pandas & Matplotlib, to analyze diverse datasets, combining cryptocurrency prices with unemployment rates, inflation, US Dollar Index & federal interest rates.

• Leveraged NLP techniques and sentiment analysis libraries to analyze a dataset of over 100,000 tweets on Twitter, discovering a significant correlation between various cryptocurrencies. Chicago Crime Insights Aug 2023 – Dec 2023

• Conducted comprehensive ETL processes on three datasets (8 million+ records) to ensure data accuracy & quality.

• Leveraged Tableau's visualization capabilities, creating a variety of charts and maps to effectively communicate complex data, including line graphs, bar charts, heat maps, and spatial analysis.

• Redesigned the existing Chicago crime dashboard in Tableau, improving readability and usability by implementing a clearer color scheme, adding interactive features, and optimizing the dashboard layout. TECHNICAL SKILLS

• Languages: Python, SQL, R, C, HTML, CSS

• Developer Tools: PyCharm, Git, VS Code, Google Colab, Jupyter Notebook, Tableau, Power BI, Talend

• Libraries & Frameworks: NumPy, Pandas, Matplotlib, TensorFlow, Scikit, Flask

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