Welcome

I am a postdoctoral researcher at New York University with Cate Hartley.

My work examines both how and why different processes (e.g., memory, attention, development, context) impact learning. I am particularly interested in how learned representations – neural, cognitive, and computational – change with time and affect adaptive behavior.

In my research, I use computational models of reinforcement learning to simulate learning scenarios, analyze behavioral data, and generate hypotheses for experiments. I also draw insights from neural network models of the brain.

I completed my Cognitive Science PhD at Brown University, working with Michael J. Frank. I received my Bacherlor’s in Computer Science and a minor in Cognitive Science from Princeton, during which time I worked with Yael Niv.

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Select Publications

Jaskir, A., Frank, M.J. (in preparation.). “Discovering analogous structure supports transfer in human reinforcement learning”.

Gallo, M., A.A. Hamid, A. Jaskir, J. Bretton, T. Pan, D. Ofray, M.J. Frank, C.I. Moore, K.G. Bath (in preparation.). “Early life adversity alters dopamine signaling underlying diminished reward sensitivity and slowed reinforcement learning in mice”.

Jaskir, A. & M.J. Frank. 2022 “On the normative advantages of dopamine and striatal opponency for learning and choice.” eLife.

Media spotlights

“Carney’s Brainstorm Program Hosts Its Second Annual Brainstorm Challenge Awards”

“Five Brown Ph.D. students receive 2023-2024 Graduate Awards in Brain Science”

“Recent discoveries in computational neuroscience hold important implications for how humans learn and make decisions”