Iman Nabiyouni Sunnyvale, CA 914-***-**** add8j1@r.postjobfree.com

Deep Learning Scientist/ Engineer with over 5+ years of experience in Machine learning across multiple domains including Computer vision, Signal processing, eHealth, and Sensor Fusion. Experienced in building deep learning models for practical deployment in complex environments. TECHNICAL SKILLS .

● Programming Languages: C/C++, Python, Matlab, SQL, C#, JavaScript, Visual Basic, SAS

● Machine Learning: Data Mining, Convolutional Neural Network, Computer vision, Image Processing, Deep Neural Networks, Classification, Clustering, Linear and Logistic Regression, SVM, Random Forest, Decision Trees, EM, AdaBoost, Kmeans, K Nearest Neighbors, Gaussian Process, Naive Bayes, Reinforcement Learning, Recommendation Systems

● Deep Learning:NN, CNN, RNN, LSTM, GRU, Seq2Seq, GAN, Autoencoder

● Libraries: Pandas, SciPy, NumPy, Scikit-Learn, Opencv

● Data Visualisation: Tableau, Matplotlib, D3.js (familiar)

● Packages: Tensorflow, Keras, Pytorch, Hadoop, Spark, MapReduce (Distributed Systems, parallel processing)

● Statistics: Hypothesis Testing, Classical Regression Analysis, ANOVA, Sample t-tests, Interaction Test, Matrix Math

● OS: Linux (Redhat, Ubuntu 18), Windows Server

● Cloud Services: AWS, EC2, S3, Load Balancers, API Gateway etc.

● Script: Unix Bash, Windows PowerShell/DOS (Deep Linking URL)

● Version Control: Source Gear (Vault), GIT

EXPERIENCE .

Mercedes-Benz Research & Development, Sunnyvale CA Sep 2019 – Present Machine Learning Software Engineer

A car manufacturer company providing Autonomous Driving services for variety of products Skills used: Machine Learning, Computer Vision, Image Processing, C++, Python, ROS, GIT, Distributed Systems

● Implementation of computer vision on filtered images for state prediction

● Deployed chosen neural network for model selection using various input parameters

● Implementing Hidden Markov Model for temporal denoising

● Using Bayesian Networks for Sensor Fusion (from Multiple Sources)

● Automated the model evaluation Pipeline Using Bash Script Mercedes-Benz Research & Development, Sunnyvale CA Jan 2019 – Sep 2019 Software Engineer Intern

A car manufacturer company providing Autonomous Driving services for a Variety of products Skills used: Machine Learning, C++, Python, ROS, GIT

● Sensor fusion for Environment planning data stream

● Implemented KPIs for Environment Planning Department

● Enabled Handling ROS-bags of Recorded Data

● Achieved Message Publishing in ROS Environment

Indiana University Grand Challenge Precision Health Initiative, Bloomington IN Aug 2018 – Dec 2018 Research Assistant

A Health-related institute that provides funding for relevant researches Skills Used: Machine Learning, Image Processing, Point Cloud, C++, Python, Matlab, JavaScript, C#

● Applied an End-to-End CNN model with parameter learning approach for noise detection in time series

● Implemented CNN methods for text classification (sentiment analysis)

● Employed transfer learning on VGG16 network for emotion detection

● Analyzed point cloud data (LIDAR/Kinect) for tracking a dynamic object with searching algorithms

● Deployed Machine Learning Classification Algorithm for event detection in time series

● Applied Speech Recognition techniques as a data cleaning tool in time series

● Developed software to assist clinicians in their diagnosis which benefits from wireless measurement Indiana University School of Public Health, Bloomington, IN Aug 2016 - May 2018 Associate Instructor

A Health-related school

Skills Used: Machine Learning, IOT (Internet of Thing) in IDE (Arduino boards coding) and embedded systems, C++, Python, Matlab, Statistical Analysis

● Analyze health-related data like the center of pressure with machine learning tools

● Develop a customized program in multi-device communication and synchronization

● Design a user interface for collecting and recording patient information

● Reprogram Kinect software for wireless communication

● Code bootloader of Arduino (Python) that wirelessly transfer(bridge) board serial data

● Design and develop a body motion tracking system (a point cloud analyzer) using multiple Kinects West Virginia University School of Engineering, Morgantown, WV Aug 2015 - May 2016 Teaching Assistant

Department of Industrial Engineering

Skills Used: Machine Learning, C++, Python, Statistical Analysis, Java Script, OpenSim

● Implementing Deep Neural Network for predicting the effect of button colors and touching method on accuracy of dialing

● Develop a script in C++ for creating controller models with specific cost function in OpenSim

● Reformat motion tracking data for OpenSim software

● Examine motion data to simulate the motion tracker with a machine learning model Navard Aluminium Company, Arak, Iran Sep 2009 - July 2015 Senior Engineer

Department of Engineering

Skills Used: Machine Learning, C++, Python, Java Script, Statistical Analysis, Microsoft Excel

● Employing machine learning models for predicting the chance of a product being defective

● Computer modeling on the waste of the company for examining the efficacy of a hydraulic press

● Designing and motion analyzing of a furnace door for determining the best values in design EDUCATION .

Indiana University, Indiana, United States 2017-2019 M.Sc. in Computer Science (Machine Learning),

Amirkabir University of Technology, Tehra, Iran 2007-2009 M.Sc. in Mechanical Engineering, Tehran.

Iran University of Science & Technology,Tehran, Iran 2002–2006 BSc. in Mechanical Engineering, Tehran.

PATENTS .

● Issued a patent for Balance Evaluation (Measuring Dynamic Center of Pressure by using Force Insoles), School of Public Health, Indiana University (Serial No. 62/799,297). HONORS AND AWARDS .

● Awarded Student Scholarship (Cooper Scholarship, Davies, Jones, and Mosely Scholarship) for the 2017-2018 academic year through the School of Public Health, Indiana University.

● Selected as an exceptional student among Iranian students by the Ministry of Science, Research and Technology, Iran.

GRANT PROPOSALS .

● John Shea, Iman Nabiyouni, “Research Equipment Fund for Upgrading Motor Control Research Laboratory Equipment”, FY16 Research Equipment Fund (REF), Indiana University, 2016

● John Shea, Iman Nabiyouni, YMCA Training Equipment Fund from the Department of Kinesiology, Indiana University, 2016

PUBLICATIONS .

● Iman Nabiyouni “Parameter-learning in an End-to-End Convolutional Neural Network for Time-Series Classifications”, Submitted, 2020

● Iman Nabiyouni, John B. Shea, Donald Williamson, “ A Supervised Learning Approach Using Multi-resolution Features for Artifact Detection in EEG Recordings ”, Submitted, 2019

● Hossein Motabar, Esther Raub, Ashish D. Nimbarte, Iman Nabiyouni, “Safe Loading Thresholds for Rotator Cuff Muscles”, 2016, Occupational Ergonomics and Safety Conference, Chicago, Illinois

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