Christian Yudistira Hermawan

Bridging Code & Theory.

AI Research Assistant @ETH Zürich | Ex-AI Engineer Intern @RTI Infokom | Teaching Assistant @University of Indonesia | Silver Medalist GEMASTIK 2025

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Some Notebooks worth Read About

My Data science projects, AI Works, etc

Estimated Time Arrival approach and analysis for UI's Bis Kuning

A data-driven approach to predicting the Estimated Time of Arrival (ETA) for Universitas Indonesia's campus shuttle (Bis Kuning). This notebook analyzes travel patterns and route efficiency to improve campus mobility.

TransportationETA PredictionData Analysis

Radar-Based Human Detection with ERASENet

Segments human presence from millimeter-wave radar heatmaps using a custom ERASENet-style model. The notebook covers radar tensor visualization, weighted pixel scoring, and a 30-epoch PyTorch training run that reached a best validation score of 0.9733 and a test score of 0.9394.

PyTorchRadarSegmentation

Crowd Counting and Head Localization

Builds a slice-based crowd analysis pipeline that predicts both head counts and head-center coordinates in dense scenes. It combines density-map regression, SAHI-based patching, and localization evaluation, with a best validation loss of 0.0002 across the training run.

PyTorchCrowd CountingLocalization

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Honors & Awards

Recognition for excellence in data science competitions

Silver Medalist & Best National Paper

Kemendikbudristek2025

GEMASTIK 2025: Data Mining Division

Engineered a high-precision computer vision pipeline combining OCR and deep learning for automated Javanese script classification.

1st Candidate & Finalist

Kemendikbudristek2025

Satria Data BDC 2025

Architected a multimodal video analytics system using OpenAI Whisper, FFmpeg, and FFT-based acoustic shift detection across 200+ hours of video.

Google Developer Group x Amartha Hackathon 2025

3rd Place, Professional League

GDG Jakarta x Amartha2025

Google Developer Group x Amartha Hackathon 2025

Engineered a Gemini-2.0-Flash extraction pipeline and LangGraph ReAct agent for financial predictive analytics in Kubuku.

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Publications

Peer-reviewed research contributions

S-TEA: Sequential Slow Transfer Learning untuk Pemetaan Kemiskinan dengan Citra Satelit

R. Salim, C. Yudistira, V. D. L. Tjoeng, A. F. Wicaksono • Buletin Pagelaran Mahasiswa Nasional Bidang TIK (Gemastik) (2024)

Pemantauan kemiskinan yang akurat dan granular di Indonesia merupakan prasyarat fundamental untuk perencanaan pembangunan yang efektif, namun terhambat oleh keterbatasan data survei konvensional yang mahal. Penelitian ini bertujuan mengembangkan kerangka kerja inovatif S-TEA (Sequential Slow Transfer Learning) untuk memprediksi tingkat kemiskinan kecamatan menggunakan data citra satelit dan geospasial yang tersedia publik. Metodologi mengadopsi strategi sequential fine-tuning berdasarkan konsep slow learner pada tugas proksi klasifikasi intensitas Night-time Lights, NDVI, dan LST. Hasil penelitian menunjukkan kerangka kerja S-TEA mampu memitigasi catastrophic forgetting dengan penurunan CPCF relatif hingga 81,5% dibanding baseline, menghasilkan peta kemiskinan beresolusi tinggi yang lebih akurat.

SCENT: Semantic Chaptering dengan Exponential-Decay dan Neural Taxonomy

C. Yudistira, Tim Suika • Satria Data 2025 - Big Data Challenge (2025)

Pertumbuhan masif konten video pendek di platform media sosial memicu kebutuhan mendesak akan sistem otomatis yang mampu mengekstraksi pengetahuan dari himpunan data video tersebut. Penelitian ini menawarkan pendekatan modular untuk mengoptimalkan video understanding multi-modal dengan efisiensi sumber daya. Utamanya adalah pipeline multi-modal berbasis chaptering yang mengintegrasikan ekstraksi keyframe, scene detection, dan transkripsi audio. Pipeline efisien ini menghasilkan empat output simultan: penyusunan taksonomi, peringkasan hierarkis, dan analisis konten multi-dimensi (content scoring), mencapai pemahaman video yang seimbang tanpa memerlukan infrastruktur GPU enterprise yang mahal.

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Experience

Professional journey and expertise

AI Research Assistant

ETH Zürich

Oct 2025 - Present

Engineered micro-accurate Ground Truth datasets for Egocentric Video analysis, focusing on complex human-object interactions. Provided core datasets instrumental in securing publications at top-tier AI conferences like CVPR and ICCV.

Computer VisionData AnnotationResearchVideo Analysis

AI Engineer Intern

RTI Infokom

Jun 2025 - Aug 2025

Developed and deployed an intelligent RAG-based AI Agent system for RTI Business. Led research in stock market automation by integrating NLP-driven sentiment analysis with financial indicators for improved equity predictions.

RAGNLPLangChainSentiment AnalysisFinancial Tech

Teaching Assistant - Intro to AI & Data Science

University of Indonesia

Jan 2025 - Present

Mentored over 300 undergraduate students in foundational programming, Machine Learning basics, and AI concepts. Developed course materials, assisted in lectures, and provided personalized tutoring to ensure strong student comprehension.

TeachingMachine LearningPythonData ScienceMentoring

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