prospective students

(Last update: Sep.1, 2025)

Welcome to the Causal Data Science Lab!

Our lab is built on one principle: causal inference is our central mission. We are curiosity-driven and inspired by problems that emerge from real-world, practical settings. We are always looking for students whose excitement about causality matches our own and who are eager to contribute to a collaborative causal inference community that pushes the frontier forward.

Who We Are

We are the Causal Data Science Lab, dedicated to advancing the theory and practice of causal inference. Our goal is to develop rigorous theoretical frameworks and computational methods that uncover causal relations and answer fundamental “why” and “what-if” questions using statistical and computational tools.

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 thrives not on raw hours, but on curiosity and passion that fuel sustainable and consistent effort. The most successful researchers are those who deeply believe in the importance of their research and field, who are driven by a curiosity that makes them unable to stop exploring, and who find joy in the process of research, so that steady and consistent progress comes 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 itself. 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 be able to articulate a genuine, intrinsic curiosity about causality itself—not simply an interest in applying AI techniques to fashionable domains.

Our Standards and Commitments

• 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.
• High Standards — 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 that advances causal data science. 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 requires cultivating a mindset that supports long-term growth and strong relationships with your advisor and colleagues:

• Curiosity and Passion — The most successful researchers are driven by curiosity, which fuels natural, unstoppable effort and genuine passion for their work.
• Proactivity and Ownership — Tackle your research with initiative and drive. Engage actively, explore directions boldly, and move projects forward with momentum.
• Coachability — Growth requires not only accepting direct and frequent feedback, but also actively seeking it, reflecting on it, and implementing it quickly.
• Mental Resilience — Research inevitably brings setbacks, disagreements, rejections, and failed experiments. The key is to maintain steady momentum and sustained motivation, keeping your energy focused on learning from challenges rather than 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.
• Respectful Professionalism — Treating others with professionalism and respectfulness is essential for building lasting relationships and thriving in research. Our lab grows when we support one another, and cultivating these qualities can be one of the most important foundations of long-term success.

Who We Are Looking For

A Genuine Passion and Curiosity for Causal Inference

As emphasized in Our Focus: Causal Inference First, we seek colleagues who have a genuine passion and deep curiosity about causal inference itself. The ideal candidate can clearly articulate why causality excites them and why they want to dedicate their PhD journey to advancing this field.

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

Pursuing a PhD is fundamentally about growth—becoming a professional and independent researcher. An ideal candidate will already embody the qualities described in Our Mindset and show a strong commitment to cultivating them throughout their training, with the mentality to accept feedback openly and reflect on it promptly without feeling burdened.

Kindness and Respect Joining this lab as a PhD student means not only being part of our group in the short term, but also becoming a colleague in the broader causal inference community for the long term. We therefore seek students who share the principle of kindness and respect—treating others with consideration, fostering a supportive and collaborative environment, and helping to build a lab culture where mutual respect is the foundation of our shared success.

If you are deeply curious about causality, grounded in strong foundations, and eager to grow as an independent researcher and colleague, you will find a supportive home in the Causal Data Science Lab.