Julian Sidik

Julian Sidik

M.S. in Computer Science @ Georgia Tech. Interested in ML, health informatics, and software systems.

CV

Julian Sidik
github.com/jsidik | julianksidik@gmail.com | jsidik@gatech.edu
Mobile 650 898 3993 | U.S. Permanent Resident | Sunnyvale, CA

Education

Georgia Institute of Technology — Atlanta, GA
Master of Science in Computer Science — Dec 2026
• Relevant Courses: Health Informatics, Artificial Intelligence, Software Development

University of California, Davis — Davis, CA
Bachelor of Science in Computer Science & Engineering — Jun 2025
• Relevant Courses: ECS 171 – Machine Learning, EEC 172 – Embedded Systems, Data Structures & Algorithms, Computer Architecture, Software Engineering, Operating Systems, Computer Networks

Experience

Software Engineer Intern — May 2025 – Sep 2025
PT Telindo Nusantara — Jakarta, Indonesia
• Developed and deployed backend services supporting TN-CLOUD cloud-based telephony platform, implementing SIP call event logging, user provisioning APIs, and call detail record (CDR) processing pipelines for enterprise clients
• Built internal provisioning dashboard (React + Node.js) to automate IP-PBX configuration and user onboarding workflows, reducing manual configuration time per client deployment and improving deployment turnaround across 5+ enterprise accounts

Undergraduate Student Researcher — Mar 2025 – Jun 2025
Visualization and Interface Design Innovation Lab, UC Davis — Davis, CA
• Architected and implemented Graph Neural Network (GNN) system processing 10K+ node heterogeneous graphs from EHR datasets, improving cancer patient survival prediction accuracy using attention-based embeddings
• Built interpretability framework using graphlet frequency analysis to explain model predictions on Cancer Genome Atlas (TCGA) datasets, enabling clinicians to understand feature importance

Computer Science Tutor — Jan 2024 – Jun 2025
Department of Computer Science, UC Davis — Davis, CA
• Delivered technical instruction to 50+ students on advanced algorithms (graph traversal, dynamic programming, divide-and-conquer) and data structures (BSTs, hash tables, heaps)

Projects

(ECS 193 Senior Design Project) AI-Powered Surgical Instrument Counting System — PyTorch, Swift, REST APIs
• Engineered end-to-end ML system detecting 30+ surgical instrument types, processing 600+ instruments/hour to eliminate counting errors in OR workflows
• Built scalable RESTful API backend with PostgreSQL, implementing caching layer to serve 500+ concurrent users at <100ms latency for real-time inference
• Developed and published iOS and Android app with CoreML model compression, enabling offline prediction and auto-syncing discrepancy alerts to hospital inventory systems

Multi-Modal LLM Benchmarking Framework — InstructBLIP, CLIP, Transformers
• Fine-tuned 4 vision-language models (InstructBLIP variants, CLIP, custom ResNet-LSTM) on MS-COCO dataset, achieving state-of-the-art 145.8 CIDEr score with improved inference speed
• Implemented comparative evaluation pipeline using SPICE, CIDEr, BLEU, and METEOR metrics across 10K+ image-caption pairs, identifying optimal model for medical image description tasks

Technical Skills

Publications

Talks

Teaching