Niv Lab

Research in the Niv lab focuses on the neural and computational processes underlying reinforcement learning and decision-making.

We study the ongoing day-to-day processes by which we learn from trial and error, without explicit instructions, to predict future events and to act upon the environment so as to maximize reward and minimize punishment. In particular, we are interested in how attention and memory processes interact with reinforcement learning to create representations that allows us to learn to solve new tasks so efficiently. [read more]

Important Note

If you received an email solicitation for an available position in my lab asking you to call a phone number to apply — that is a phishing attempt. We currently do not have positions available, and if we did, they would be advertised at and would not involve calling by phone, or sending any information outside the formal application process on the Princeton website. 

A scammer is impersonating me, sending forged emails to students falsely advertising a position with lucrative pay, and obtaining information about them through a fake application process. Do not contact the scammer or give them personal information or money!

Lab News

August 2023: Welcome to our three new RAs, Kepler Palacio-Soto, Jialing Ding and Seohyun Moon. We're excited to have you join us!

August 2023: Congratulations to our summer interns, Hollen Knoell, Isabella Fernandez, Julie Abaci, Andrea Mullin, and Andrew Kyo for completing their summer internships! We're excited to see what you do next and can't wait to see your posters!

August 2023: Goodbye to Nastasia, we will miss you! Good luck with grad school! 

July 2023: Congratulations to everyone who participated in the 2023 Computational Psychiatry Conference! Isabel Berwian gave a talk on 'Using computational models to understand psychotherapy interventions effects' and Yael Niv gave a tutorial on 'Reinforcement learning and bayesian approaches' and a keynote. Dan-Mircea Mirea presented a poster on 'Computational psychiatry in the wild: depression affects reinforcement learning on social media,' Sashank Pisupati presented a poster titled 'Real-world evaluation of a machine learning decision-support system for mental health assessments,' and Oded Bein presented a poster on 'The relationship between mental health symptoms and event segmentation.'

May 2023: Rachel Bedder's conference paper "Modelling Rumination as a State-Inference Process" will be presented as a talk at CogSci 2023 in Sydney in July! Congratulations Rachel, we're excited to see you share your work!

April 2023: Congratulations to Oded Bein, who presented a poster at LEARNMEM 2023, titled “Altered event segmentation in anxiety and schizotypy"!

March 2023: Rachel Bedder and Dan Mirea both presented at the Society for Affective Science conference! Rachel was part of the Reinforcement Learning as an Approach to Understanding Basic Affective Processes symposium, and presented a talk titled, "Modelling Rumination as a State Inference Process." Dan presented a flash talk, titled "Computational psychiatry in the wild: how depression affects reinforcement learning on social media." Congratulations to both!

December 2022: Congratulations to Sashank Pisupati at his new job at Limbic! We will miss you, and please come visit!

November 2022: Jamie Chiu has a poster at SfN Neuroscience 2022, titled "How does sadness influence effort-based decision making?"!

August 2022: Sev Harootonian will give a talk at CCN 2022, titled "The best advice you can give"! Sev will also present his work as a poster, and additionally received a travel grant for this conference. Congratulations Sev! We are excited to see you share this interesting work.

August 2022: We are excited to welcome Nastasia Klevak to the lab as the lab manager!

For news older than 2022, see the lab news archive.