Computer Science Graduate

Shanker Lal
Meghwar

I build practical data, machine learning, and software systems.

Budapest, Hungarymeghwarshanker24@gmail.com
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Shanker Lal Meghwar
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About Me

Computer Science graduate focused on practical machine learning, data science, and software systems.

I build practical data, machine learning, and software systems that turn real-world problems into useful solutions.

I recently completed my Bachelor of Science in Computer Science at the University of Pécs, Hungary, with a focus on Data Science and Machine Learning.

My work combines machine learning, data analysis, software development, and practical automation. I enjoy taking a messy real-world problem, understanding the data behind it, and building a solution that can actually be used.

My final-year thesis focused on diabetes prediction on highly imbalanced datasets, where I focused on improving recall so that more potential diabetes cases could be identified.

0.85

Clinical Recall

0.88

BRFSS Recall

350K+

Records Analyzed

3

ML Models

Experience

My professional journey

April 2026 — June 2026

Remote

Data Science Intern

10Pearls

Remote

Worked on an end-to-end data workflow for environmental data and air-quality forecasting, taking the use case from raw data through to decision-ready output.

  • Built an end-to-end data pipeline transforming raw environmental data into a standardized 72-hour Air Quality Index (AQI) forecast, structuring the use case from raw data to decision-ready output.
  • Automated data ingestion, feature engineering, and model retraining workflows using Pandas and GitHub Actions, reducing manual effort and standardizing the end-to-end process.
  • Developed an interactive Streamlit dashboard and automated daily reporting for AQI forecasts, translating model output into actionable insights for non-technical stakeholders.

February 2026 — April 2026

Pécs, Hungary

Embedded Systems & Automation Intern

Computing & Education Technology Centre, University of Pécs

Pécs, Hungary

Worked on IoT integration, Linux automation, and cross-system troubleshooting in a live operational environment.

  • Designed an event-driven IoT system with reliable failure handling, applying structured, diligent problem-solving to a live operational environment.
  • Built an automated Linux-based file processing pipeline to standardize and scale a manual workflow into an end-to-end automated process.
  • Diagnosed a cross-system integration issue between two platforms, resolved the root cause, and documented the solution for future reference and knowledge sharing.

Education

Education

BSc, Computer Science

University of Pécs

Pécs, Hungary

Sep 2023 – Jun 2026

Relevant Coursework

Deep LearningArtificial IntelligenceData StructuresDatabase ManagementMachine LearningPythonJavaLinuxStatistics

Projects

Selected work and technical projects

Final Year Thesis

Diabetes Prediction Using Machine Learning

Developed machine learning models for diabetes prediction using large-scale, highly imbalanced datasets, with a focus on improving recall for potential diabetes cases.

  • Trained XGBoost, Random Forest, and Logistic Regression on approximately 100K clinical and 254K BRFSS records.
  • Addressed severe class imbalance with ADASYN, class weighting, and threshold optimization.
  • Achieved a Clinical AUC of 0.92 with 0.85 recall and BRFSS recall of 0.88.
  • Applied hyperparameter tuning and evaluation strategies focused on identifying more potential diabetes cases.
PythonXGBoostRandom ForestScikit-learnPandas

Data Science Internship

Air Quality Index Forecasting

Built an end-to-end data workflow for environmental data, transforming raw inputs into standardized 72-hour Air Quality Index forecasts and decision-ready outputs.

  • Built an automated data pipeline covering data ingestion, feature engineering, forecasting, and reporting.
  • Automated model retraining and daily AQI reporting using Pandas and GitHub Actions.
  • Developed an interactive Streamlit dashboard for forecast visualization and decision support.
PythonPandasXGBoostStreamlitGitHub Actions

Academic Project

University Administration System

Built a Java and Spring Boot-based backend system for university administration, supporting student records, data management, and API-based workflows.

  • Developed a RESTful backend using Java and Spring Boot.
  • Integrated MySQL for structured data storage and management.
  • Implemented SQL queries for data handling, analysis, and reporting.
  • Documented APIs with Swagger for easier testing and integration.
JavaSpring BootMySQLREST APISwagger

Skills

Technologies I work with

Programming

PythonJava

Machine Learning

XGBoostRandom ForestLogistic RegressionScikit-learn

Data Analysis

NumPyPandasSQLJupyter Notebook

Tools & Technologies

GitLinuxMySQLGitHub ActionsSFTP/SSH

Frameworks

Spring BootStreamlitPyTorchTensorFlow

Contact

Let's work
together.

I'm open to opportunities in data science, machine learning, software development, and related technical roles.

meghwarshanker24@gmail.com
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© 2026 Shanker Lal Meghwar. All rights reserved.

Based in Hungary