Shariq Mobin Email & Phone Number

California, United States

Oakland, California, United States

* Solving #1 complaint in hearing industry — Difficulty hearing in noisy social situations.* Raised money from YCombinator, Xoogler, and National Institute on Aging (grant).* Developed team of contractors across hardware, machine learning, acoustics, and hearing difficulty.* Collaborated with Stanford, John Hopkins, & University of the Pacific on clinical benefits.* Designed an acoustic ray-tracing engine to generate tens of gigabytes of highly accurate acoustic training data for training our deep learning models using 16 AWS GPUs simultaneously.

Oakland, Ca

Developed a novel patented thesis for solving the cocktail party problem - Enhance voices nearby patients and suppress ones further away.* Method: Develop a synthetic acoustic dataset of voices from different distances and train a deep learning model on it.* Developed an acoustic ray tracing engine from scratch that could generate binaural room impulse responses (BRIRs) 80% as accurate as ones from the real world using 16 GPUs on AWS.* https://www.youtube.com/playlist?list=PLTJbNpfeLPSgiFzJaD6fzFT20L6Qf_ZBc

Oakland, California, United States

Clinical Research into the benefits of our technology including increased interest in socializing, noise tolerance, and word recognition in noise.* Set up audiology booth for 2-channel testing of QuickSIN and Acceptable Noise Level (ANL) with two researchers.* Researchers found 2-3X better noise tolerance with our technology.* Applied & Awarded A2 Pilot Grant from the NIA & John Hopkins University for our research.* Collaboration with Dr. Jiong Hu at University of the Pacific & Professor Fitzgerald at Stanford

Oakland, California, United States

Deployed deep learning model onto a embedded board for testing with patients.* Hardware Components: BatAndCat Behind-The-Ear Hearing Aid + Variscite Embedded board (VAR-SOM-MX8).* Wrote C++ code for real-time full-duplex audio streaming (mic->speaker), short-time fourier transform (STFT), weiner filters, resampling, etc.* Built an Audio Lab at Circuit Launch for testing patients in, refined the design through 3 iteration cycles.

Berkeley, Ca

At the Redwood Center for Theoretical Neuroscience I created* Robust statistical models of audio signals,* Neural Networks which replicate human auditory attention, and* Theories of how brain areas use feedback for computation.

Mountain View, Ca

Working with the Machine Perception team at Google we experimented with running deep learning models in real-time on android phones using a new framework, TFLite.

Mountain View, Ca

Working with the Magenta team at Google Brain we built Generative Adversarial Networks (GANs) for improving the quality of our RNN-based generative models of music.

Uc Berkeley

* Autonomous learning, Information-driven actions, sensorimotor learning (NeurIPS 2014)* Dynamic Image Models with Sparse Coding and Linear Dynamical Systems

San Francisco Bay Area

Directed development of our distributed query optimizer engine and worked on data recovery.* Implemented statistical estimates of different SQL operations to improve JOIN performances.* Led design and implementation of a project for insuring data integrity under power failures

Ruby on Rails support application for editing large amounts of data (SQL, Git, MongoDB, Javascript Linux)

Doctor Of Philosophy (Phd), Computational Neuroscience

Bachelor'S Degree, Eecs