prospective students

(Last update: Sep.28, 2025)

Welcome to the Causal Data Science Lab!

Our lab is founded on a single guiding principle: causal inference is our central mission. We are motivated by intellectual curiosity and inspired by the challenges that arise in real-world, practical settings. We seek students whose passion for causality aligns with ours and who are eager to contribute to a collaborative community dedicated to advancing the frontier of causal inference. If you find yourself doing your best work when fully immersed in a problem, and if you aspire to spend the coming years living and breathing causal inference, you will find a natural home in this lab.

Who We Are

We are the Causal Data Science Lab. Our goal is simple: push forward and expand the frontier of causal inference. We build rigorous theoretical frameworks and computational methods to uncover causal relations and answer the core “why” and “what-if” questions. We develop and use statistical and computational tools, and we apply them to high-stakes domains where getting causality right matters. What drives our work is full immersion in causal inference and relentless curiosity about causality itself.

Our current research agenda is organized around five main pillars:

1. Identification and Estimation under Real-World Imperfections — advancing frameworks that reliably infer causal effects despite challenges such as unmeasured confounding, limited overlap, or complex data-generating processes.
2. Robust and Scalable Estimation — designing variance-stable, computationally efficient methods that scale to high-dimensional and large-scale datasets.
3. Trustworthy Inference — developing methods to ensure transparent, reliable, fair, and interpretable inference in high-stakes scientific and societal settings.
4. Causal Decision-Making — creating algorithms that leverage causal reasoning to support efficient, robust, and generalizable decision making in complex, high-stakes environments.
5. Causal AI for Diverse Modalities — integrating causal reasoning with modern AI to enhance trustworthy causal inference methods, enabling richer analyses of images, text, temporal data, and other complex modalities.

How We Work

Our Attitude: Curiosity-Driven Consistency

Research doesn’t thrive on raw hours. It thrives on curiosity, immersion, and passion. The best researchers don’t just work on projects; they sleep with them, eat with them, and live with them. They carry their problems because they believe deeply in the importance of their field. Curiosity makes it impossible to stop exploring, and joy in the process makes progress flow naturally.

Our Rhythm: Synchronize with the Sun

I encourage students to synchronize with the Sun – beginning with daylight and winding down as the sun sets. This rhythm naturally aligns with the human circadian rhythm, supports physical and mental health, strengthens communication within the lab, and fosters consistent, sustainable progress together.

Our Focus: Causal Inference First

Our sole mission is to advance causal inference. While we employ tools such as Large Language Models (LLMs) or Generative AI when they serve this goal, they are not the main focus of our work. Applicants should bring a genuine curiosity about causality itself—not just an interest in chasing fashionable domains.

Lab Culture

• Shared Success — A student’s success is my success. I am committed to investing in your growth and helping you become an independent researcher in the causal inference community.
• Excellence in Every Dimension — Success is not only about technical excellence. It largely depends on the rigor of our methods, the depth of our analysis, the professionalism of our communication, and the kindness we show one another. We aim for excellence in all these dimensions.
• PhD is Earned — A PhD is not awarded for time served, but for demonstrating the ability to conduct independent, impactful research. It is a high-risk, high-reward endeavor, and I am committed to helping you reach that bar.

Our Mindset

A PhD is a marathon, not a sprint. Success in this lab takes curiosity, passion, and immersion that fuel unstoppable effort. It takes initiative and ownership to push research forward. It takes a strong coach–athlete relationship built on trust, coachability, and resilience. And it takes growth beyond technical skills—clear communication, sharp critical thinking, and professionalism. Above all, it requires kindness and respect toward colleagues, teammates, and peers.

• Curiosity, Passion, Immersion — The best researchers do not just work on problems; they live with them. Curiosity drives effort, immersion sustains focus, and passion carries the work forward.
• Proactivity and Ownership — Take initiative. Explore boldly. Push projects forward with momentum.
• Coachability — Actively seek feedback, absorb it fast, and put it into practice.
• Mental Resilience — Setbacks, disagreements, and rejections are part of research. What matters is maintaining steady momentum, sustained motivation, and the ability to learn from challenges without being derailed by them.
• Growth Beyond Technical Skills — A PhD is an apprenticeship in becoming a professional researcher. Technical expertise is only part of success; communication, critical evaluation, and professional conduct are equally important.
• Respect — Research thrives on respect. Supporting one another builds the foundation for long-term success.

Who We Are Looking For

A Genuine Passion and Curiosity for Causal Inference

We look for colleagues whose passion and deep curiosity for causal inference drive their research. The ideal candidate can explain clearly why causality excites them and why they want to dedicate their PhD journey to advancing this field. We want people whose immersion and relentless curiosity push them to take on important problems in causal inference, guided by both passion and commitment.

Strong Foundations in Math and Statistics

Our work is grounded in mathematical formality and statistical rigor. You should be comfortable with statistical inference and mathematical analysis. If your background is still developing in these areas, you must have a proactive willingness to strengthen it early in your program and embrace learning new technical skills without hesitation.

A Mindset for Growth

Doing a PhD isn’t just about learning more facts. It’s about growing in every direction. The people who do best are the ones who actively seek feedback, absorb it in fast, and use it to get better. They’re tough enough to take hits, and still keep going. They’re full of energy and passion.

Kindness, Respect, and Faithfulness

Mentee–mentor relationships last a lifetime. Lab-mate relationships endure long after graduation. Joining this lab means entering the broader causal inference community. We choose colleagues as if we are picking partners for life, not coworkers for a few years. That is why kindness, respect, and faithfulness to long-term relationships matter so much. Energy, passion, and curiosity are the baseline. But without kindness and respect, none of it works. We are not research machines. We are not research machines; we are a team of humans. And what sustains a team is kindness and respect.

If you do your best work when you’re obsessed with a question, and if you want to spend the next few years living and breathing causal inference, this is the place for you.