Building intelligence system that create impact.

Statistics and Data Science student at Universitas Negeri Semarang with hands-on experience building real-world AI applications. I specialize in LLM-based systems, AI agents, and end-to-end machine learning solutions, with experience developing and deploying machine learning and deep learning models for practical use cases. I have contributed to SINTA- and Scopus-indexed research publications and have been recognized through multiple national AI and data science competition awards. Passionate about building scalable, production-ready AI systems that deliver measurable real-world impact.

7+ Research Papers
4 National Awards
2+ Years of Experience

Open to collaboration

Galih Kusuma Wijaya
GK

AI Engineer Intern

Flyrank AI

FlyRank is an AI-powered SEO platform built to automate and scale content intelligence. I joined as an AI Engineer intern working across the full backend stack, from spinning up REST API endpoints and containerizing services with Docker to building AI decision flows using React Flow and Inngest, integrating LLM APIs into production pipelines with guardrails, cost observability, and eval frameworks, and shipping features like a PDF report generator, secure webhook receiver, and background job system. Capstone work extends into building an autonomous interlinking engine, an image relevance and auto-tagging system, and a usage metering and billing service, translating AI capabilities into real product features.

Leader

Data Champion Society UNNES

When I took over, I rewrote the vision and mission from scratch, restructured all divisions, and replaced the existing program with a 9-month project-based capstone where members produce publishable outputs every month, supported by 3 sessions per month with practitioners, lecturers, and partner communities. I also designed and led the internal Satria Data selection pipeline to surface the campus's top data talent.

Research Assistant

Universitas Negeri Semarang

Embedded in an active publication pipeline, I co-authored a Scopus-indexed paper on optimized LSTM and BiLSTM for electricity load forecasting, developed the full NLP and K-Means methodology for a SINTA 4 journal on food program prioritization, and helped co-initiate the One Action One Mangrove program that secured Rp25,000,000 in government funding from Kemendiktisaintek.

001

Conjify: Anemia Screening via Conjunctival Imaging

Built the full AI pipeline for Conjify, a mobile-first web app for non-invasive anemia self-screening via smartphone camera. I designed and trained a dual-head EfficientNet-B0 that simultaneously classifies anemia presence and estimates hemoglobin levels quantitatively, trained on CP-AnemiC dataset (710 images) using multi-task learning with progressive unfreezing. Integrated Grad-CAM to extract spatial activation statistics for structured Llama 3.3 70B clinical interpretation in plain Indonesian. Model achieved 84% accuracy, AUC-ROC 0.902, and Hb regression MAE 1.515 g/dL. Deployed on Hugging Face Spaces via Gradio API.

Computer VisionEfficientNet-B0Multi-task LearningGrad-CAMLLMGradio
View Repository →
002

NutriVision

Built as the AI component of a cross-path capstone at Coding Camp DBS x Dicoding. I implemented EfficientNetV2 as the backbone with BiFPN for multi-scale feature fusion and FCOS as the detection head, a fully anchor-free approach using stride-based convolution instead of predefined anchor boxes. The app identifies fast food items from major brands and estimates their exact nutritional content.

Computer VisionEfficientNetV2FCOSBiFPNAnchor-Free Detection
View App →
003

NALAR: Media Literacy Simulation

Built an agentic AI simulation platform where specialized LLM workflows autonomously generate scenario briefings, audience personas, editorial assets, network propagation, and post-incident analysis. Designed a multi-stage AI orchestration pipeline with structured JSON outputs, prompt specialization, and multi-model routing across Gemini 2.5 Flash and Groq, monitored through Langfuse observability. Engineered a real-time AI-driven propagation engine that recursively simulates branching social interactions on a force-directed graph, alongside token-budget guardrails, hybrid rule-based + LLM evaluation, and secure server-side orchestration using Next.js App Router and Supabase.

Next.jsTypeScriptAIGroqGeminiSupabasereact-force-graph-2d
View App →
004

Personal AI Agent (WhatsApp)

Built and deployed a personal AI agent directly into my own WhatsApp, handling automated responses, task assistance, and context-aware interactions through a bot pipeline running on personal infrastructure.

AI AgentWhatsAppAutomationPython
005

PyGrind

A browser-only, 100% AI-driven coding practice platform for AI/ML and backend engineers. Every task, curriculum path, and code review is generated dynamically by an LLM (Groq or Gemini) using the user's own API key, with no backend and no database. Built an adaptive tier system where problem difficulty scales per topic, a Monaco-based practice loop with real-time AI code review gating progression, and an owner-maintained HTML handbook synced as reference material for every problem.

ReactTypeScriptMonaco EditorLLM IntegrationZustandTailwind CSS
View App →
007 2nd Place · DIMAS-TI Data Mining

LexiLSTM: Campus Complaint Classifier

The real challenge was not the model, it was the absence of labeled data. I used weak supervision with a domain lexicon and fuzzy string matching to auto-generate pseudo-labels across six complaint categories from informal Indonesian social media text. I compared standard BiLSTM, BiLSTM + self-attention, and BiLSTM + multi-head attention. The key finding: added complexity does not consistently win when training labels are noisy. The hybrid approach still delivered +18% accuracy over baseline, with attention weights providing interpretable token-level insight.

NLPBiLSTMSelf-AttentionWeak SupervisionPython
View Deck →
2026 Scopus

Comparative Study of LSTM-Based Models with Hyperparameter Optimization for Short-Term Electricity Load Forecasting

Iqbal Kharisudin, Insyiraah Oxaichiko Arissinta, Sabrina Aziz Aulia, Muhamad Abdul Qodir Dani, Galih Kusuma Wijaya

BAREKENG: Jurnal Ilmu Matematika dan Terapan

A comparative study of LSTM-based architectures with systematic hyperparameter optimization for short-term electricity load forecasting, evaluating which configuration best captures temporal dependencies in consumption data across varying load patterns.

DOI →
2026 Proceedings

Pemodelan Navigasi Adaptif Tunadaksa dengan Integrasi Indeks Aksesibilitas dan Algoritma A*: Studi Kasus di Kampus FMIPA UNNES

Adaptive Navigation Modeling for the Physically Disabled with Accessibility Index Integration and A* Algorithm: A Case Study at FMIPA UNNES Campus

Galih Kusuma Wijaya, Muharima Sahara, Tsalisa Chulaili Syahri Nova, Muhammad Abdul Qodir Dani, Ratna Nur Mustika Sanusi, Iqbal Kharisudin

PRISMA: Prosiding Seminar Nasional Matematika

An algorithmic model integrating a Physical Disability Accessibility Index (IAT) using fuzzy logic with the A* search algorithm to identify optimal and inclusive navigation routes for individuals with physical disabilities.

DOI →
2026 Proceedings

Prediksi IHSG Berdasarkan Sentimen Publik terhadap Kebijakan Ekonomi Nasional Menggunakan Model IndoBERT–LSTM

IHSG Prediction Based on Public Sentiment towards National Economic Policies Using the IndoBERT–LSTM Model

Galih Kusuma Wijaya, Maulana Anandyta Narayana, Muhammad Akbar Anugrah Syafa, Muhammad Alifian Yusuf, Iqbal Kharisudin, Virgania Sari

PRISMA: Prosiding Seminar Nasional Matematika

A study developing a predictive model for the Indonesia Composite Index (IHSG) by integrating public sentiment from social media using IndoBERT alongside a Long Short-Term Memory (LSTM) time-series model to improve forecasting accuracy.

DOI →
2025 SINTA

Regional Prioritization for Free Nutritious Food Programs through Social Data Integration and Public Sentiment Analysis Using K-Means and NLP

Ratna Nur Mustika Sanusi, Galih Kusuma Wijaya, Nur Achmey Selgi Harwanti

UJM: UNNES Journal of Mathematics

An integrated approach combining K-Means clustering on socioeconomic indicators with NLP-based sentiment analysis from social media to build a context-aware regional prioritization model for Indonesia's Free Nutritious Meal program.

DOI →
2025 Proceedings

Comparative Study of Autoencoder and LSTM-AE for Extreme Temperature Anomaly Detection in Semarang

Galih Kusuma Wijaya, Aliyya Anggraeni, Tsalisa Chulaili Sahri Nova, Muhammad Alifian Yusuf, Iqbal Kharisudin

ICDSOS - POLSTAT STIS International Conference

A comparison of standard Autoencoder and LSTM-Autoencoder for detecting extreme temperature anomalies in Semarang's historical climate data, evaluating which architecture better captures temporal dependencies in anomaly patterns.

DOI →
2025 Proceedings

Dinamika Sentimen Publik dalam Suksesi Pemerintahan Indonesia berdasarkan Analisis Data Media Sosial

Public Sentiment Dynamics in Indonesian Government Succession Based on Social Media Data Analysis

Galih Kusuma Wijaya, Adelia Venie Diniar, Shata Alwan Jalaluddin, Iqbal Kharisudin

PRISMA: Prosiding Seminar Nasional Matematika

A sentiment analysis of Indonesian social media across the presidential succession from Jokowi to Prabowo, mapping how public sentiment shifted across key political milestones and what it reveals about digital discourse and public trust.

DOI →

1st Place

GRAVITASI Essay Competition

Universitas Sumatera Utara · Oct 2025

2nd Place

DIMAS-TI Data Mining Competition

AMLI (Asosiasi MIPA LPTK Indonesia) · Nov 2025

1st Place

Lomba Esai Nasional Rumah Disabilitas

Rumah Disabilitas Indonesia · Dec 2025

Special Honor: Distinction

FPCI Global Impact Day 2025 Essay Competition

President University · Jul 2025

Hard Skills

Python SQL RAG LangChain MCP LLM Deployment LangGraph n8n Agentic AI Vector Databases TensorFlow

Soft Skills

Leadership Teamwork Critical Thinking Research Writing Data Storytelling

Certifications

Let's build something.

Open to research, collaboration, and full-time or hybrid roles.