Artificial Intelligence Engineer
PT Pertamina Patra Niaga
Building a secure procurement platform with document ingestion, OCR, permission-aware retrieval, and reliable AI serving.
Muhammad Faris
El Hakim.
Machine learning. Data engineering. Applied AI.
I study how data becomes understanding, and build the systems that make it useful.
Informatics Engineering · Universitas Brawijaya
Abstract. I’m a Computer Science undergraduate at Universitas Brawijaya, working at the intersection of machine learning research and practical engineering. From forecasting and computer vision to data pipelines, I care about useful systems, careful validation, and results that hold up beyond a notebook.
Areas of interest: Machine learning; data engineering; intelligent systems; reproducible research.
I. Career & organizations
A continuing education, in research and in practice. Current roles first, followed by earlier experience.
- Sep 2026 – PresentCurrent
- Sep 2026 – PresentCurrent
Lead Teaching Assistant
Faculty of Computer Science, Universitas Brawijaya
Coordinating teaching assistants, grading standards, and lab sessions. Helping students develop clear algorithmic thinking.
- Mar 2026 – PresentCurrent
Information Technology Developer
HMDTIF FILKOM UB
Developing and maintaining the student association’s Link Hub and Product Catalog with Go and Next.js.
- Oct 2025 – PresentCurrent
Associate Researcher
Intelligent Systems Laboratory, Universitas Brawijaya
Exploring machine learning and deep learning, including satellite image segmentation and reproducible research workflows.
- Jun – Sep 2026
Data Science Problem Setter
HOLOGY, Universitas Brawijaya
Designed machine learning challenges in computer vision, natural language processing, and geospatial AI for HoloMine.
- Sep – Oct 2025
Research Intern
Intelligent Systems Laboratory, Universitas Brawijaya
Studied Yelp review sentiment with SVM and BERT, building data preparation pipelines and validating experiments.
II. Achievements
Milestones from building, experimenting, and learning together.
JOINTS x Inspire Data Science Competition
Universitas Gadjah Mada · Oct 2026
Datathon RISTEK UI
Universitas Indonesia · Aug 2026
Sebelas Maret Statistics Fair
Data Science · Universitas Sebelas Maret
FIT Data Science Competition
Team Tembok Ratapan Solo · UKSW
Football Score Prediction
Honorable Mention · Most Creative Approach
FIND IT! Data Analytics
Face anti-spoofing · Universitas Gadjah Mada
COMPFEST Data Analytics Dash
Data engineering · Universitas Indonesia
III. Certifications
Professional learning and the credentials along the way.
Certified Palantir Foundry Aware Professional
Palantir Technologies · Issued Apr 2026 · Expires Apr 2028
Verify credential ↗
Asia Tech x Singapore Conference
STIE Indonesia Malang · Issued Jun 2023
IV. Selected projects
An exploration of models, methods, and the infrastructure between them.
Bengawan Solo Water-Level Forecasting
1st Place · SSDS 2026
A non-recursive seasonal mixture of experts for a 242-day forecasting horizon, combining recency-corrected seasonal forecasts with leakage-aware chronological validation.
View repository : Bengawan Solo Water-Level Forecasting (opens in a new tab)Website Desa Sumberarum
A public digital village platform
Citizen services, news, UMKM, transparency, and CMS workflows for Desa Sumberarum, built with Next.js and Laravel.
Visit website : Website Desa Sumberarum (opens in a new tab)Clinical Decision Support System for Breast Cancer Screening and Prognostic
Clinical research · FIT finals
A research prototype combining tabular prognosis and survival analysis with mammogram classification, leakage auditing, explainability, and latency evaluation.
View repository : Clinical Decision Support System for Breast Cancer Screening and Prognostic (opens in a new tab)Sipadi
Flood-resilient rice supply chains
An interactive decision-support prototype for West Java, combining flood hazard analysis, supply-chain vulnerability, deterministic stress testing, and Latin Hypercube Sampling.
View repository : Sipadi (opens in a new tab)Hybrid Dual-View and Artifact-Aware Framework for Multi-Class Face Anti-Spoofing
Finalist · UGM Data Analytics Competition
A reproducible pipeline combining global and face-crop views, DINOv3, FSFM, and artifact-aware machine learning for six-class face anti-spoofing.
View repository : Hybrid Dual-View and Artifact-Aware Framework for Multi-Class Face Anti-Spoofing (opens in a new tab)V. Let’s start a conversation.
Have a research question, a project in mind, or something interesting to build? I’d love to hear about it.
Contact me on WhatsApp ↗+62 851 0164 0140