Master Thesis

• Analysis Of Data Synchronization Methods And Framework In Wire Arc Additive Manufacturing (WAAM)
  Developed methods for spatiotemporal synchronization of multi-source WAAM data streams to enable anomaly detection and process monitoring in metal additive manufacturing. The thesis combines data preprocessing, synchronization algorithms, and visualization techniques to improve process quality and control.
  Master Thesis, Thesis Presentation, Thesis Poster, Conference RatSiF Abstract, Conference RatSiF Presentation
  • Tools: Python, Pandas, NumPy, scikit-learn (KMeans, DBSCAN, AgglomerativeClustering, KernelDensity), Scipy (interp1d, find_peaks), Plotly (plotly.graph_objects, plotly.express), Dash, JupyterDash, Dash Table, Open3D, Matplotlib, Seaborn, Google Colab, Jupyter Notebook, Statsmodels, sklearn.metrics (accuracy_score, precision_score, recall_score, f1_score, jaccard_score)

Artificial Intelligence Group Project

• Adverse Media Monitoring And Client Risk Assessment System
  Led Step 3 by developing automated web search and analysis workflows for identifying reputational risks from online sources, while also serving as Project Manager responsible for team coordination, task assignment, and GitHub management. Reflective report
  • Tools: Google API, OpenAI GPT-4, Google Custom Search API, BeautifulSoup, Regex, spaCy, TextBlob, pandas, ThreadPoolExecutor, concurrent.futures

Machine Learning and Predictive Analytics

• Mushroom Risk Prediction and Grouping with Logistic Regression & K-Means
  Developed a complete ML pipeline to classify mushrooms as edible or poisonous using Logistic Regression and K-Means clustering. Report
  • Tools: pandas, scikit-learn, matplotlib, seaborn

Big Data

• Customer Behavior and Sentiment Analysis Using Structured and Unstructured Datasets
  Conducted data-driven analysis of customer transactions and musical instrument reviews to identify behavioral patterns and sentiment trends. Combined structured data (CSV) and unstructured data (JSON) with ontology modeling to extract insights and represent semantic relationships. Report, Project.
  • Tools: MongoDB Atlas, pandas, numpy, seaborn, matplotlib, dask, textblob, rdflib, RDF, ontology modeling, sklearn (LabelEncoder, MinMaxScaler), JSON, CSV, FOAF, XSD

Data Mining

• Exploratory Data Analysis on Auto MPG Dataset
  Conducted a comprehensive data exploration project on the Auto MPG dataset to analyze fuel efficiency trends and vehicle characteristics. Report.
  • Tools: pandas, matplotlib, seaborn
• Clustering Analysis of California Housing Dataset
  Performed clustering using K-means and hierarchical methods on standardized California housing data to identify distinct housing market segments based on economic and housing features. Report.
  • Tools: pandas, scikit-learn, matplotlib, seaborn
• Housing Price Prediction Project
  Developed regression models to predict housing prices using features such as size, number of rooms, and condition. Applied linear regression and random forest regression, including data preprocessing, feature scaling, and evaluation of model performance. Report.
  • Tools: pandas, scikit-learn, statsmodels, matplotlib, seaborn

Programming for Data Analytics

• Market Analysis Using Web Scraping and Data Visualization
  This project demonstrates scraping, cleaning, analyzing, and visualizing real estate garage ads data from a Latvian website. Report.
  • Tools: pandas, matplotlib, seaborn, numpy, BeautifulSoup, osmnx, folium

Business Intelligence and Data Visualization

• Large Scale North American Retailer Analysis
  Developed an interactive dashboard project using Tableau Public. Acted as a BI consultant to analyze sales trends, inventory management, and financial performance of a major North American retailer across multiple stores from 2017 to 2020. The project involved data cleaning, preparation, normalization, creation of calculated fields, visual design aligned with institutional branding, and publishing interactive dashboards for stakeholder use. Reflective Diary, Presentation.
  • Tools: Tableau Public, Tableau Desktop, Python (for data preparation), Interworks Color Tool, Adobe Color

Research Methodology

• Assignment