Parsa Hosseini Ph D
About
Parsa Hosseini Ph D is from San Francisco Bay Area. Parsa works in the following industries: "Electrical/Electronic Manufacturing". Parsa is currently AI/ML Adjunct Lecturer, Bioengineering at Santa Clara University. Parsa also works as Senior Lead Data Scientist, AI/ML at Tesla, a job Parsa has held since Aug 2017. In Parsa's previous role as a Machine Learning Research at Apple, Parsa worked in until Aug 2017. Prior to joining Apple, Parsa was a Data Scientist, Research Scientist at Henry Ford Health System and held the position of Data Scientist, Research Scientist at Detroit, MI. Prior to that, Parsa was a University Lecturer + Teaching Assistant at Rutgers University from Aug 2013 to May 2017. Parsa started working as Research Assistant in Machine Learning at Rutgers University in New Brunswick, NJ in May 2013. From May 2016 to Oct 2016, Parsa was Cloud Computing at Externetwork, based in New Jersey. Prior to that, Parsa was a Research Assistant in Machine Learning at Wayne State University from Jan 2012 to Jan 2013. Parsa started working as Adjunct Assistant Professor at Azad University (IAU) in Jan 2008.
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Parsa Hosseini Ph D's current jobs
Machine Learning, Deep Learning
Product Management and Project Management Communicate insights to engineering, product management, and executive projects Drive product decisions with data Developing Python codes for Database queries Developing ML to analyze Marketing Data Database queries, big data visualization, and ML production models Research and development on deep learning models to analyze big data projects Leading data science and analytics projects to deliver enterprise level solutions Working with business teams to provide reporting infrastructure Developing data & BI solutions for business like Operations, Finance, Accounting, Growth Data modeling and database developments Agile software development, Jira and confluence Research and development in data science, machine learning, and deep learning Developing machine learning tools for analyzing the large-scale dataset Programming, Algorithm development, Data Structure modeling for Car-log dataset Development and implementation of supervised/unsupervised Machine Learning and Deep Learning models for data processing and analyzing Programming, analyzing and simulation in Python, Matlab, R Python programming and work with Pandas, NumPy, Scikit_Learn, Tensorflow, etc. Relational Database design and management in mySQL and Microsoft SQL server Large-scale data processing with Apache Spark, Apache Spark's scalable machine learning Big data visualization and analysis ETL; Evaluating and analysis product failure modes or symptom from associated Car Signals and alerts
Parsa Hosseini Ph D's past jobs
Signal Processing and Analysis Machine Learning Studies Deep Learning for Apple Watch
• Research and development in machine learning, data science, data mining • Developing Brain-Computer Interface for neurological diseases • Statistical pattern recognition and data analyzing of medical data • Research and development in biosignals (EEG, ECG) and medical imaging (MRI, fMRI) • Developing statistical pattern recognition models such as SVM, KNN, ANN • Research and development in deep learning (CNN, auto-encoder, GAN) • Publications in leading biomedical engineering conferences such as IEEE Engineering in Medicine and Biology Society (EMBC), The International Society for Magnetic Resonance in Medicine (ISMRM)
• Independent Instructor for MATLAB Programming & Simulations, (3 Credits) • Teaching Assistant for graduate/undergraduate courses such as Software Engineering, Matlab Programming, Network Security, Digital Logic Design, Engineering Ethics, Advanced Topics System Engineering
• Research and development in machine learning, data science, big data with healthcare applications • Developing deep learning (CNN, auto-encoder, GAN, LSTM) • Multi-modal analysis using deep learning via cloud computing • Work on cloud computing (EC2), IoT and wireless communications • Developing signal processing, image processing, and computer vision projects • Analyzing and processing medical dataset (fMRI, MRI, EEG) • Developing a brain-computer interface for computational neuroscience and epilepsy • Developing autonomic computing for brain disorders in seizure detection and prediction • Coding with Python, Matlab, R, and MySQL • Modular design of software and documenting the design using symbolic representations, i.e., UML diagrams using relational database programming (using SQL). • Software engineering projects includes customer statement of requirements, system requirements, functional requirements specification, user interface specification, domain analysis (domain model, system operation contracts, mathematical model) , interaction diagrams, class diagram and interface specification, system architecture and system design, algorithms and data structure, user interface design and implementation, design of tests. • Developing random subspace ensemble learning for big data real-time processing • Publications and presentation in leading computer science journals/conferences such as IEEE Transactions on Big Data, IEEE Communications-Frontiers, International conference on autonomic computing, ICAC 2016 (acceptance rate:27%), and ICAC 2017 (acceptance rate:19%) • Publications in leading biomedical engineering journals such as Artificial Intelligence in Medicine, Medical Physics
• Research and development in Big Data • Work on Cloud Computing, Internet of Things (IoT), and wireless network • Part of NOC responsible for round-the-clock Level 1 system administration
Data Analysis, Pattern Recognition, Image Processing • Research and development on computer-aided diagnosis systems
Research and teaching at Electrical Engineering, Computer Engineering, and Computer Science Departments Teaching: “Machine Learning”, “Artificial Intelligent”, “Expert Systems”, “Programming Languages”, “Modelling and Simulations”, “Numerical Analysis”, “Fuzzy Control Systems", “Electronic Circuits”, “Communication Systems”, “Pulse Techniques”, “Statistics”, “Mathematics”, “Webpage Designing”, etc. Research Areas: Artificial Intelligence + Signal/Image Processing + Computer Networks