Subhojeet Pramanik

Subhojeet Pramanik is a researcher at Softmax with an MSc from Alberta’s RLAI lab whose work focuses on reinforcement learning and representation learning. He introduced the Recurrent Linear Transformer (AGaLiTe, TMLR 2024), previously worked at IBM Research, and is the author of OmniNet, a unified architecture for multi-modal multi-task learning.

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