Liftoff: New lab alerts

Learn about early-career scientists starting their own labs.

Are you a new principal investigator? Email Francisco J. Rivera Rosario at [email protected]. Selected new labs may be featured in our Launch monthly newsletter.

Interviews have been lightly edited for length and clarity.

February 2026

Daniel Levenstein, assistant professor of neuroscience, Yale University

Lab start date: August 2025

What do you study? What part of your research are you most excited about?

The overarching aim of my lab is to understand offline learning in the sleeping brain. While you sleep, your brain is home to a zoo of self-organized activity patterns, which it uses to change itself—to learn from things that happened during the day and set itself up to learn new things tomorrow. My lab will try to mimic that process in artificial neural networks to better understand how it works, develop new approaches to artificial intelligence and, hopefully, understand how it can go wrong in psychiatric conditions. We’ll start by tackling two major questions: How does the rest of the brain extract generalized knowledge from hippocampal replay, and how does the hippocampus itself change during replay such that it can form new memories in the future without forgetting the old ones? 

Are there any traditions or practices from the labs you trained in that you will implement in your own lab?

I did my Ph.D. in György Buzsáki’s lab. Whenever anyone left the lab, György would give an awkward speech about the story of the person’s time in the lab. The person leaving would, in turn, give their own speech from their perspective and talk about what they learned from György and the other lab members. It was all quite touching, and I think it really helped the lab feel like a community that valued the people who came through and the time they spent there. It also showed new lab members just how nonlinear research can be—no one ended up doing the project they had planned when they joined. I’ve seen a lot of amazing speeches, and I hope to have a similar “celebration of the time in the lab” practice in my own group. The other thing I’d like to carry forward is that the lab always has lunch together. Both my Ph.D. and postdoc labs did this, and it’s quite nice for building a sense of community.

Qihong Lu, presidential assistant professor, City University of Hong Kong

Lab start date: January 2026

What do you study? What part of your research are you most excited about?

In my lab, we aim to use neural network models as model organisms to understand what cognitive architecture is effective for the kind of computational problems the brain must solve, including the processes behind the strategic use of episodic memory. Episodic memory enables us to rapidly encode information upon a single exposure and retrieve it later, which is essential for adaptive memory-based behavior in humans. Yet many fundamental questions remain unclear. Moreover, EM might be an important missing piece in advancing modern artificial intelligence. How does the brain use EM to support cognition? How does the brain coordinate EM with other memory systems? What is the optimal coordination strategy, and to what extent does the human brain implement this optimal strategy? I’m excited by the synergy between AI and human cognition. A better understanding of human cognition could inspire future AI algorithms, especially in the domain of memory.

Are there any traditions or practices from the labs you trained at that you will bring over and implement in your lab?

I plan to use a “slide stack”—a practice that worked well for me when I was a trainee. Basically, every trainee will maintain a running Google Slides document, and every week, the trainee can add updates about their projects. This allows me to preview everything before one-on-one meetings, making them more efficient. For the trainee, the slide stack will act as an archive of checkpoints—which is helpful for “debugging” things throughout the projects—and as a template for making polished materials for talks and papers.

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