Soheil Esmaeilzadeh

I am a Ph.D. researcher at Stanford university with a background in direct numerical modeling, computational science, and machine learning. I'm interested in using computational science, applied mathematics, numerical modelling, optimization, deep learning, and AI for solving real world sceintific problems.

Career

Netflix

Detection of Suspicious Streaming Behaviors - Security & Machine Learning

June-Sept. 2020, Los Gatos, CA
Machine Learning Intern

Visa Research, Visa Inc.

Adversarial Machine Learning - Security & Computer Vision

June-Sept. 2019, Palo Alto, CA
Deep Learning Research Intern

Technology Group, Quantum Rerservoir Impact

Un-supervised machine learning, spatio-temporal clustering, code development, numerical simulations, and history matching

June-Sept. 2018, Houston, TX
Data Science Intern

Ph.D.

GPA 4/4                            Stanford Graduate Fellowship (SGF) winner

Sept. 2016-Now, Stanford Universty, CA

TAF Lab, UC Berkeley

Software development, complex 3D geometry generation, gradient-free shape optimization, hyperformance computing

Jan.-Oct. 2016, UC Berkeley, CA
Research Scholar

Innovation Center, ABB

Data analysis and code development for numerical simulations

Aug.-Dec. 2015, Zurich, Switzerland
Software Engineering Intern

M.Sc.

GPA 6/6                              Distinct graduate (top 1%) and nominee for the ETH gold medal   ETH Excellence Scholarship & Opportunity Award (ESOP) winner

2014-2016, ETH Zurich, CH & UC Berkeley, CA

B.Sc.

GPA 4/4                    Graduated as 1st rank student

Aug. 2010-Aug. 2014, University of Tehran, Iran

Selected Publications