Data Scientist Software Developer

Hossein (Hudson) Naseri, Ph.D.

Senior Data Scientist Software Developer

Address: Chicago, IL, 60615

Work Status: H-4 [Eligable for TN]

Telephone: +1-815-***-****

Email: *******.******@****.******.**

Websites: naserih.github.io linkedin.com/in/hnaseri/

PROFESSIONAL SUMMARY

Senior data scientist and software developer with over 15 years of experience in developing scalable machine learning solutions, data pipelines, and web applications. Proven expertise in cancer research, data modeling, image processing, and natural language processing. Adept at project management, team leadership, and multidisciplinary research. Published author with a track record of impactful contributions across various domains.

HIGHLIGHTS

●12+ years of experience in data science and software development.

●Ph.D. in Medical Physics with 8+ years of industry expertise.

●Published extensively in fields such as cancer research, NLP, and machine learning.

●Proficient in Python, Matlab, Fortran, R, and cloud platforms like Google Cloud.

●Strong leadership skills with experience in managing and mentoring teams.

EDUCATION

Ph.D. in Medical Physics, McGill University, Montreal, Canada (2018 – 2023)

Thesis: The use of radiomics and natural language processing to detect pain in simulation-CT images of patients undergoing radiotherapy for bone metastasis Supervisor: Dr. John Kildea GPA: 3.9/4.0

M.Sc. in Computational Physics, University of Lethbridge, Lethbridge, Canada (2012 – 2015)

Thesis: Numerical solutions of the inertial modes of the earth’s fluid core

Supervisor: Dr. Behnam Seyed-Mahmoud GPA: 4.0/4.0

M.Sc. in Applied Physics, IASBS, Zanjan, Iran (2007 – 2010)

Thesis: Using soft-lithography for making microfluidics channels and studying fluid diffusion and mixing at microscale Supervisor: Dr. Mehdi Habibi GPA: 3.5/4.0

B.Sc. in Physics, University of Mohaghegh Ardabili, Ardabil, Iran (2002 – 2007)

GPA: 3.3/4.0

SKILLS

●Programming: Python, Matlab, Fortran, R, JS [+15 years]

●ML & NLP: PyTorch, Spark, TensorFlow [+8 years]

●Big Data & MLOps & CI/CD: Google Cloud, Azure [+7 years]

●Databases: SQL, NoSQL, JSON, XML [+10 years]

●Data Visualization: BI tools, dynamic data visualization [+10 years]

●Project Management: Agile, Scrum, team leadership [+8 years]

EXPERIENCES

Lead Data Scientist Farmers Edge Jun 2022 - Jan 2024

●Successfully led a team of six developers to create sustainable forecasting ML tools for precision agriculture. Leveraged Python, AutoML and VertexAI, to support real-time decision-making, enabling growers to optimize costs and boost productivity.

●Developed automated techniques for data ingestion and monitoring using Google Cloud, BigQuery, and Dataflow, ensuring efficient and reliable data processing and preventing data loss or data drift.

●Pioneered the implementation of a patented, state-of-the-art transformer-based deep learning model for image and time series analysis using Dataproc, Spark, and PyTorch. Achieved 90% accuracy in real-time multi-class crop classification, a breakthrough in the industry. Implemented additional functionalities such as automated field border detection, cloud removal, and crop season start and end date detection.

●Developed tools for optimal seeding and harvest date estimation with an accuracy of 2 days, and created crop yield prediction tools using satellite imagery. These tools provided valuable insights for farmers and insurance companies to optimize their operations and boost productivity and revenue.

●Implemented XGBoost and KNN machine learning models to develop a virtual farm-level soil sampling system, resulting in a 20% reduction in soil sampling costs.

Lead Software Engineer Farmers Edge Jun 2016 - Aug 2022

●Directed a team of four developers to design and implement Python scripts for automated data processing, machine learning, and statistical analysis. This initiative resulted in significant cost savings and accelerated processing times, greatly enhancing data-driven decision-making capabilities.

●Built advanced decision support tools by processing CANBus data from over 20 types of farming equipment. Successfully deciphered and calibrated more than 500 machine attributes, including speed, seeding rate, and crop yield, covering 98% of farming equipment in the US, Canada, and Brazil. This achievement enabled real-time precision agriculture recommendations for optimized planting, harvesting, and operational time management.

●Enhanced telematics data packaging and transmission by implementing in-device data processing, achieving a tenfold reduction in data transfer size and storage, and optimizing machine data utilization for precision agriculture.

●Improved data management by automating the transfer of telematics data to Azure databases using Azure IoT and Blob storage techniques.

●Developed in-house data monitoring and quality improvement pipelines in Python, ensuring reliable data processing and high-quality outputs.

●Designed and deployed RESTful APIs using Python Django and Elasticsearch, facilitating seamless interactions with databases and improving system integration.

●Integrated PowerBI tools to provide advanced data visualization, enabling real-time monitoring of machine data and diagnostics. This integration enhanced interaction with technicians, farmers, and stakeholders, facilitating efficient troubleshooting and better decision-making.

Graduate Researcher McGill Medical Physics Unit Sep 2018 - May 2022

●Engineered state-of-the-art NLP pipelines to summarize health records and extract pain severity from consultation notes, advancing healthcare data analysis with TensorFlow, MetaMap, BERT, LLM, Generative AI, ICD-10, and UMLS.

●Implemented advanced image processing techniques with Python, PyTorch, radiomics, DICOM, and scikit-learn to extract tumor features from CT images of cancer patients, contributing to cutting-edge cancer research.

●Created innovative web applications for text annotation and image processing using Python Flask, PostgreSQL, and React, boosting note reviewing efficiency by tenfold and image reviewing by fifteenfold.

●Pioneered the implementation of FHIR and HL7 standards to securely transfer hospital data to a patient portal, ensuring complete and centralized patient records. Utilized Mirth Connect, Node.js, Google Firebase, and GitLab.

●Designed and instructed comprehensive graduate-level courses on Python, SQL, DICOM image processing, and project management skills using Jira, Confluence, and Scrum, enhancing students' organizational capabilities. Received outstanding feedback from students and the university over four years.

●Published influential research in Biomedical Informatics and Nature Scientific Reports, garnering significant citations and recognition within the cancer AI community.

Research Assistant University of Lethbridge May 2015 - Jun 2016

●Created Arduino-based signal generators for brain stimulation studies, and developed MATLAB algorithms for signal analysis, streamlining experimental procedures and saving costs with a novel, efficient design.

●Designed statistical models for real-time satellite image processing, enabling accurate flood mapping. Successfully integrated remote weather stations with databases, overcoming complex technical challenges single-handedly.

●Engineered and deployed full-stack Web APIs for weather data collection and visualization using Python, Django, and PostgreSQL, improving data accessibility.

●Developed machine learning algorithms to identify stress biomarkers using Python and scikit-learn, leading to a highly cited publication in a leading journal.

●Organized data science workshops for graduate students in science, teaching ML concepts to non-computer professionals and receiving outstanding feedback.

SELECTED CERTIFICATES

●Good and Bad AI in Cancer research, 20 hrs, 2023, McGill University

●Deep Learning and LLM in Healthcare, 120 hrs, 2020, Udemy

●Fluent Python, 180 hrs, 2018, Google Career Certificates

●Machine Learning, 60 hrs, 2016, Stanford Online

●RESTful Web Application Development, 40 hrs, 2015, Farmers Edge University

SELECTED AWARDS

●Fonds de Recherche du Québec - Santé (FRQS), 2023

●NSERC/Laval CREATE Scholarship, 2022

●Ruth & Alex Dworkin Scholarship, Faculty of Medicine, McGill University, 2021

●MITACS Training Awards, Canada, 2019

●Farmers Edge, Employee performance Award, 2017

●Microsoft imagine cup Innovation Competition Award (Image Processing), USA, 2014

MEET ME

Thank you for reviewing my resume. For further discussion, book your one-on-one appointment here: https://calendly.com/hnaseri/networking_nook. I look forward to connecting with you!

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