I study how machine learning, administrative data, and analytic infrastructures reshape decision-making in public institutions, especially in customs and international trade. My work sits at the intersection of technical systems, institutional authority, and policy implementation.
Across customs operations, fiscal analytics, and regional digital trade integration, I am interested in how evidence becomes trustworthy, accountable, and usable once it enters real organizational workflows.
The work below reflects where I currently spend time: international advisory work, graduate teaching, research development, and building bridges between academic inquiry and institutional practice.
Serve as a World Customs Organization representative advising customs administrations on integrating data analytics into institutional practice across Asia-Pacific, Latin America, and Europe.
Studying how data systems, classification standards, and analytics reshape customs and international trade governance.
Worked closely with Professor Mary Ellen Benedict to support graduate students in an intensive spring 2026 course on economic analysis, quantitative reasoning, and applied problem-solving.
Chair the Advisory Board at the Center for Customs and Excise Studies, connecting academic research with policy practice in international trade and mentoring young researchers working at that intersection.
This section highlights published research across customs analytics, trade policy, and environmental governance. Together, these pieces show how technical methods can inform public institutions and real policy choices.
These projects translate research and analytical thinking into usable tools: applications for policy exploration, dashboards for monitoring and interpretation, and interfaces designed to support clearer decisions.
An interactive policy tool that pairs trade agreement materials with LLM-assisted navigation, helping users move faster across treaty content, implementation questions, and decision-relevant references.
A policy analysis app for exploring H-1B, OPT, and CPT responses under cost and incentive shocks, designed to make scenario-based labor and immigration analysis easier to inspect.
A live analytical environment for investigating trade mirroring patterns, possible rerouting behavior, and circumvention risk through comparative trade statistics.
An interactive Tableau view on expert acquisition and mobilization policy, structured to surface allocation patterns, program design questions, and implementation priorities.
A regional economic dashboard focused on current conditions and potential patterns for micro, small, and medium enterprises across West Java.
A customs-facing dashboard for monitoring shipment goods activity, supporting quicker interpretation of operational movement and exception patterns.
A multi-view dashboard for examining trade mirroring gaps, comparative reporting asymmetries, and signals relevant to circumvention analysis.
A spatial dashboard on incidents and issues in Indonesia, designed to make geographic risk patterns easier to scan and compare.
These recognitions reflect work that has been valued across research, public service, scholarship, and applied analytics. Taken together, they mark a record of building evidence that is useful both academically and institutionally.
Accredited as a WCO Expert in Data Analytics after an international assessment recognizing the ability to bridge technical analytics with operational customs practice across national contexts.
Awarded Best Paper for research on machine learning support for Harmonized System code classification in international trade.
Selected for Indonesia's flagship government scholarship to pursue graduate study at Carnegie Mellon University, with a public-service commitment tied to national development.
Recognized for initiating and leading the Customs Data Culture program, a nationwide effort that changed how the Indonesian customs administration uses data in operations and decision-making.
Recognized in a Ministry of Finance analytics competition focused on applying data mining and analytical methods to real institutional problems.
Awarded 5th place for the XBNet customs fraud detection paper on machine learning for customs risk management.
Won second place for a risk-mapping tool that used data analytics and spatial methods to support early warning of collective violence.
Recognized for a dashboard on Free Trade Agreement impacts, trade balance monitoring, and provincial export opportunity mapping.
Received a full tuition scholarship for ICAEW coursework and certification, awarded on the basis of the highest GPA among eligible students at PKN STAN.
Recent workshops, mentoring sessions, and institutional engagements offer a more immediate view of how this work travels beyond publications: into classrooms, customs administrations, and professional communities.
Co-facilitated a five-day workshop in Lima for SUNAT on customs analytics, risk management, customs valuation data, and evidence-based decision-making under the WCO-SECO programme.
Contributed as co-facilitator and WCO Data Analytics Expert in Hanoi, supporting a workshop that connected hands-on training in Python, fraud analytics, and HS classification with longer-term institutional readiness.
Presented Indonesia Customs' approach to embedding integrity through data-driven controls, institutional design, and measurable operational outcomes in a global forum with delegates from nearly 100 WCO members.
Delivered a practical session on data exploration, visualization, and decision-oriented storytelling, aimed at helping staff move from spreadsheet-heavy workflows toward clearer and more actionable use of evidence.
Contributed to a PSKC writing boot camp on persuasive structure, clarity, coherence, and research storytelling while mentoring PKN STAN students as emerging researchers.
Joined the academic and advisory community around PSKC at PKN STAN, reinforcing ties between customs practice, research, and scholarly writing.
Shared practical steps for learning data science, emphasizing that responsible decision-making requires not just access to data, but the knowledge to read and use it well.
Shared a personal learning journey in data analysis, focusing on motivation, consistency, and the discipline required to build expertise as an independent learner.