Deepak Nadipelly Email & Phone Number

Texas, United States

Boston, Massachusetts, United States

Teaching Assistant for the course DS 4420: Machine Learning • Facilitated office hours to provide student support for assignments involving the development of machine learning models from the ground up. Demonstrated the implementation of various algorithms during class sessions, showcasing practical code examples to enhance understanding and comprehension

Boston, Massachusetts, United States

• Trained a two-phase deep convolutional neural network to generate rotation values and classify button clicks for Joystick control using data from Inertial Measurement Units (IMUs) and Electromyography (EMG) signals• Collected streaming data over Lab Streaming Layer (LSL) and converted it into a tensor to feed into the neural network, enabling real-time inference and achieving an F1 score of 0.62. Utilized computer vision to capture rotation gesture control• Developed a pyqt5 tool for real-time visualization of EMG and IMU data recorded from a wearable device. Used electrode data from the wearable device to classify hand gestures in real-time using an LDA model• Fine-tuned the model by training it on data from different user sessions to minimize false positives and false negatives. Productionized the model by creating Kubeflow pipelines for feature engineering and model inferences

• Managed grading responsibilities and provided guidance to a cohort of 170+ students on their projects. Collaborated with the professor to establish comprehensive rubrics for assignments

Hyderabad, Telangana, India

• Orchestrated data extraction and transformation using SQL Stored procedures, PySpark on Azure Databricks, andautomated report and dashboard generation in Power BI for accurate insights and enhanced operational performance• Led REST API development for internal teams to access health insurance details of millions of CVS Health customers.Enhanced software quality with automated tests, reducing testing time by 40%• Successfully migrated applications to the cloud with Red Hat services and achieved a 15% monthly cost reduction.Integrated robust version control through Git and establishing seamless CI/CD pipelines with Jenkins• Implemented Kafka and Apache Airflow into data pipeline architecture, executing A/B tests to optimize data pipelines.This initiative resulted in a 25% reduction in data processing time and enhanced the overall efficiency of ETL workflows

Mysore, Karnataka, India

Designed and implemented a predictive workforce planning model using a time series forecasting approach using LSTM,achieving a Mean Absolute Error of less than 5% in predicting staffing needs• Utilized ensemble learning techniques, such as XGBoost and Random Forest, to optimize workforce allocation• Implemented clustering algorithms and hypothesis testing to segment the IT workforce and validate the effectiveness oftargeted talent development strategies

Hyderabad, Telangana, India

•Conducted in-depth exploratory data analysis on sensor data collected from agricultural fields, uncovering key patterns•Developed and implemented advanced machine learning algorithms such as RandomForest and CatBoost to accurately predict crop water requirements, leveraging data on humidity levels, temperature, previous rain data•Generated impactful dashboards using Tableau, effectively visualizing the predictions, and providing actionable information to stakeholders for optimized water management in crop cultivation.

Masters, Data Science, 3.96

Related Courses: Supervised Machine Learning and Learning Theory, Data Management and Processing, Unsupervised Machine Learning, Natural.

Bachelor Of Technology, Computer Science, 3.81

Related Courses: Data Warehousing and Data Mining, Neural Networks, Hadoop & Big Data Analy tics, Database Management Systems.