Derry Wijaya
Data Science
Using AI to protect languages, communities, and digital spaces
Derry helps students build AI systems that are responsible, culturally aware, and grounded in real‑world impact.
What do you teach?
I teach in the areas of Data Science and AI. My subjects include Machine Learning, Data Analysis for Semi‑structured Data, and Introduction to Data Science.
What qualifications or professional experiences are most central to your work as an academic?
I hold a PhD in Language Technologies from Carnegie Mellon University's School of Computer Science, and conducted postdoctoral research at the University of Pennsylvania. I also hold Bachelor's and Master's degrees in Computer Science from the National University of Singapore.
What are you doing differently in your field that you believe is driving real change?
I'm helping build AI‑powered language technologies for low‑resource languages - languages spoken by Indigenous and marginalised communities that often have little digital presence. What makes my work different is that in collaboration with my colleagues, we design these tools with clear, practical uses that directly support the communities themselves: improving access to information, detecting misinformation and toxic content, and reducing harm online. At the same time, we’re advancing safer, more reliable AI by reducing bias, hallucinations, and safety risks, so these communities benefit from technologies that are accurate, trustworthy, and equitable.
My goal is to build AI that genuinely improves people’s lives — especially for communities often overlooked in technology design. ”
Tell us about a specific moment when you saw a student transform. What happened, and what role did you play?
A moment that stands out is when my students presented their research at ACL 2025 in Vienna - one of the world’s top AI conferences. Watching them confidently explain ideas they had developed through their master’s theses and pre‑doctoral work, I could see a shift: they no longer saw themselves as students, but as researchers contributing to global conversations. My role was to guide them through the full research journey - from shaping questions to navigating setbacks to preparing for publication and professional presentations.
I’ve also seen powerful transformation through our collaborations with civil society organisations.
Students worked with investigative journalists, SAFEnet, and UN agencies to document hate speech targeting vulnerable groups, including Rohingya refugees, using AI tools we developed. They delivered talks to journalist associations and contributed to the ASEAN–UNESCO Forum on digital platform governance. Seeing them use AI not just to solve technical problems, but to protect communities, was a profound moment of growth.
What’s something about Monash University, Indonesia that would surprise people in a good way?
Monash University, Indonesia is far more research‑intensive than many people expect. We conduct world‑class, multidisciplinary research with real‑world impact, where students are active contributors, not just learners. Because AI evolves so quickly, our teaching is constantly refreshed by the research shaping the field right now. Students experience a learning environment that is dynamic, current, and deeply connected to real challenges.
What industry partnerships, research collaborations, or real‑world projects are you and your students currently involved in?
NusaAksara — AI for Indonesian Traditional Scripts
Students worked with Indigenous language communities and researchers from MBZUAI and the University of Edinburgh to digitise eight traditional scripts, creating a new dataset and publishing at ACL 2025. This work preserves cultural knowledge and expands access to information for communities using non‑Latin scripts.
Climate–TikTok — Understanding how climate messages spread
In collaboration with Boston University, we analysed over 7,000 TikTok videos to understand how emotions shape engagement with climate content. The project won Best Paper at the NLP for Positive Impact workshop and informs how climate communication can be more effective.
Generative AI for Women’s Sexual & Reproductive Health
Working with Google Research, UN partners, and women annotators across Indonesia, we evaluate how LLMs respond to sensitive health questions in regional languages. The goal is to improve accuracy, safety, and cultural alignment so women can access reliable information privately and safely.
ToxicSpeech Monitoring — Protecting vulnerable communities during elections
In partnership with AJI and the Monash Data and Democracy Hub, we built a community‑informed toxic speech detection system and a public monitoring dashboard used during the 2024 Indonesian elections. This work strengthened civil‑society's capacity to track online harms and informed responses from election oversight bodies.
What's one thing you're working on right now that doesn't fit the traditional "academic" mould?
I'm co‑directing the Monash Data and Democracy Research Hub, funded through a Monash Incubator Boost grant. The Hub looks at how data and AI shape democracy in the digital age, in a non-traditional way. We collaborate directly with civil society organisations, journalists, and marginalised communities to co‑design tools that support real‑world reporting and advocacy, not just academic publications.
This has shifted my work from studying problems at a distance to building technologies with the people most affected by them. It’s changed how I think about research success: not only in papers, but in whether the work becomes usable, trusted, and genuinely helpful to communities.
If you had to explain your research’s impact and/or teaching philosophy to a prospective student's parents over coffee, what would you say?
My research focuses on creating AI systems that genuinely improve people’s lives, especially for communities who are often overlooked in technology design. That means building language and data technologies that help people access trustworthy information, reduce online harms like misinformation and toxic speech, and make AI systems fairer, more interpretable, and safer.
In the classroom, I prepare students to use AI responsibly and effectively. I don’t just teach theory, I teach students how to design and test AI models, evaluate their impact, and think critically about how technology affects people and society. My goal is for students to graduate with strong technical skills and the judgment to build AI that makes a meaningful difference.
What achievement, qualification, or milestone in your academic or professional journey are you most proud of, and why?
What I’m most proud of is seeing students develop a genuine passion for learning and research. Watching them grow from having no research experience to producing rigorous work, publishing papers, and creating outcomes with real‑world impact is incredibly meaningful. It reflects the kind of mentoring environment I aim to create, one that builds confidence, curiosity, and a sense of purpose.
What advice would you give a student who hopes to build a similar career or level of expertise?
Find what genuinely excites you, and pursue it consistently. Passion matters because research and innovation come with moments of frustration, failed experiments, and ideas that don’t go anywhere. What makes the difference is staying curious and persevering: learning from setbacks, revisiting ideas, and being willing to pivot.