🎓 Master's Student @ The University of Aizu | 🤖 Data Engineer & AI Researcher
📍 Japan | 🌍 Open to global collaborations

I'm a results-driven Data Engineer & AI Researcher with a passion for distributed computing, geospatial analytics, and deep learning for time-series forecasting.
Currently pursuing my Master's at the The University of Aizu, Japan, I work on:

• 🚦 Traffic congestion prediction using encoder-decoder Bi-LSTM + attention
• 🛰️ One-class classification of raster images & PM2.5 forecasting
• 🌍 Open-source contributions to geoAnalytics, PAMI, and rasterMiner

🏆 Best Poster Award @ The University of Aizu Graduate Forum 2025
🎤 Invited Speaker @ ETLTC2026 Conference
📚 Reviewer for international conferences in computational intelligence

Multi-criteria scoring (safety + rainfall + congestion) vs Google Maps

• Score: 0.1897 (ours) vs 0.1937 (Google)
• Tech: Yahoo Weather API, Soramame API, PostgreSQL, Dask, Python

• Built oneClassClassifiers, CSV-to-Raster, QGIS plugins
• Co-authored paper at IEEE Space Conference 2025

• Distributed ML pipeline (Dask) across heterogeneous cluster
• GRU outperformed ARIMA, RNN, ETS, LR, RF, KNN

• Tkinter + geoAnalytics + PyInstaller → macOS DMG
• Made one-class classification accessible to non-programmers

• Compared Linear Regression, XGBoost, and Random Forest models
• Produced UML class diagrams for publication

• Built modular pipeline using Yahoo Weather & Soramame APIs
• Fetched, merged, and saved weather-augmented road/station CSV data

[C1] Charan Teja Marrimanu, Arjun Chakravarthi Pogaku. - A Novel Multi-Task Learning Framework for Predicting Traffic Congestion. Big Data & AI Conference, 2024.

[C2] Vanitha Kattumuri, Rage Uday Kiran, Charan Teja Marrimanu, Yoshiko Ogawa, Ohtake Makiko. - geoAnalytics: An Open Source Python Library for Geospatial Data Analytics. IEEE Space Conference, 2025.

Research Assistant @ The University of Aizu (Oct 2024 – Present)

• Built distributed ML pipeline for PM2.5 time-series forecasting using Dask across heterogeneous cluster (Jetson Orin aarch64 + AMD EPYC x86_64, 128 CPUs)
• Developed Route Recommendation System integrating real-time traffic & rainfall data
• Engineered geoAnalytics Python library modules: oneClassClassifiers (Correlation, FuzzyTSC), CSV-to-Raster conversion, QGIS plugins
• Benchmarked ARIMA, ETS, LR, RF, KNN on PM2.5 data via Dask, GRU outperformed all on traffic forecasting
• Contributed test cases & documentation for PAMI open-source pattern mining library
• Processed Moon/Mars multi-band TIFF spectral data - applied spatial interpolation
• Researching distributed mining of Partial Periodic Patterns using Dask across multi-node clusters
• Developing fuzzy geo-referenced pattern mining algorithms for PM2.5 and environmental datasets
• Applied fuzzy geo-referenced pattern mining to uncover spatial co-occurrence trends in PM2.5, rainfall, and road congestion
• Implemented optimized 1-NN classifiers using MaxNorm, Manhattan, and Hausdorff distances in single-threaded, parallel, and CUDA modes

Teaching Assistant @ The University of Aizu (Oct 2024 – Present)

• Undergraduate Courses: C++, Big Data Analytics, Software Engineering, Data Structures & Algorithms, Intro to Data Science (Python), AI, Calculus, Dynamics

Student Intern @ The University of Aizu, Japan (Jan 2024 - Mar 2024)

• Performed knowledge discovery in real-time Japan traffic congestion data
• Documented PAMI library

Virtual Intern @ MathWorks (AICTE), India (May 2023 - Sep 2023)

• Applied AI in domain-specific technical intelligence under AICTE-sponsored MathWorks program

• 🥇 Best Poster Award – 4th Graduate Forum 2025, The University of Aizu
• 🎓 Best Thesis Award – MITS University 2024 (Japan Traffic Congestion Internship)

• Probabilistic forecasting for sparse spatiotemporal data
• MLOps at production scale
• Japanese (N5 → N4)

• Distributed computing (Dask)
• Geospatial data mining
• Open-source pattern mining libraries
• Intelligent transportation systems

• Pattern mining algorithms
• Geospatial raster processing in Python
• Traffic forecasting with DL
• Contributing to open-source ML libraries

• 🌍 Cultural Ambassador – Taught Kho-Kho, Lagori & Bollywood dance to Japanese school children
• 🎤 Invited Speaker – ETLTC2026 Conference: "Discovering Hidden Knowledge in Raster Images"
• 📝 Reviewer – International conferences on computational intelligence and data engineering
• 🧑‍💻 Volunteer – SAISUA Events, Contributor to 2025 Fukushima World Wide Learning HS Summit
• 🎯 Technical Volunteer & Question-Panel Member – ETLTC Conference Series
• 📊 Poster Presentations – Postgraduate Forum 2024 & 2025, The University of Aizu (UBIC)

“Bridging cultures through technology, one commit at a time.”