• [Spring 2021] Research Intern at Microsoft, Redmond, WA. [virtual due to Covid]
    Project: Inspired by recent advances in SSL for audio, we proposed an augmented contrastive learning framework that learns invariant features using unlabeled data. In this approach, the embeddings are learnt by comparing multiple augmented audio segments from the same or different recordings in a contrastive fashion. We incorporate various types of perturbations to the input data and minimize a contrastive loss to learn representations robust to such perturbations. Our results show remarkable improvement in the generalization of supervised downstream tasks.

  • [August 2017] Summer student at Methods in Computational Neuroscience Summer Course. At campus of the Marine Biological Laboratory in Woods Hole, MA.
    Project: Worked with Uri Eden on temporal coding for place cells and decoding position. Using data recorded from hippocampalneurons in rats, I analyzed the discrete-time point process likelihood function of spike history in a generalized linear model (GLM) framework and compared decoding under various models.

  • [Summer 2015] Intern at Array Processing Lab.
    University of Tehran, Tehran, Iran.
    Project: Worked on the simulation and implementation of a communication system with digital modulations, demodulations, and synchronization using a PC sound card.

  • [Spring 2015] Student at Ericsson ICT Professional Foundation Program, Tehran, Iran