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Click here or scroll down to respond to this candidateCandidate's Name
PHONE NUMBER AVAILABLE EMAIL AVAILABLE LINKEDIN LINK AVAILABLE github.com/patil-aryan EDUCATION1. 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 EXPERIENCEGraduate 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. PROJECTSPredicting 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 |
