Joseph Siryani, Ph.D.

McLean, VA, *****

http://www.linkedin.com/in/josephsiryani/

703-***-****

adgom6@r.postjobfree.com

Summary

Forward-thinking and results-driven Healthcare Information Technology Leader & Data Science Evangelist; who helps Healthcare enterprises drive innovation through data science and AI applications; with a mission to democratize Decision Intelligence, reliable and safe applied AI; so they can accelerate medical discoveries, augment patients’ care, increase revenues, and reduce costs. I am passionate about 1) transforming or building data science teams & AI Center of Excellence from the ground up, 2) promoting a data-assisted culture and harvesting key insights by fingerprinting the business data to maximize ROI, and 3) creating and delivering innovative machine learning solutions to accelerate medical discoveries, value-based care, and power business leaders. I bring a unique combination of advanced analytics leadership within Healthcare and Wireless Telecom, hands-on expertise, and ability to drive Operational Excellence through leading and empowering team members to deliver on Enterprise data strategy and goals to maximize impacts. At Inova, I led agile teams and provided technical leadership and guidance on more than 100 projects, leveraged real-world data such as EMR/EHR, EDC (operational, clinical, & research), Patient Forms, Medical Notes, Medical Claims, Biospecimen, WGS, mRNA, Patient Surveys, Payment, Business Apps, and Tickets, developed rapid prototyping, Minimum Viable Products (MVP), Proof Of Concepts (POC) and deployed products including advanced analytics solutions for clinical trials, research studies with publications, collaboration initiatives, operations, and financials which accelerated discoveries and improved operations. Primary skills: Data science, digital transformation, innovation, business development, operational excellence, engineering, strategy, agility leadership, project management, data monetization, R&D, and leading high-performing cross-functional agile teams Healthcare skills: Research Informatics, clinical and translational research, service lines: heart & vascular, cancer, neurosciences Innovation skills: Hackathons, applied Machine Learning and AI program development, agile practices, CI/CD, DevSecOps Technologies: Applied machine learning, Python, R/Shiny, SQL, Tableau, Plotly/Dash, Bokeh, Streamlit, AWS & Azure Services, Redshift, Athena, MongoDB, RDS, MySQL, SQL Server, Big Data Architecture, Hadoop/Spark (Cloudera, Databricks), Confluent, Kafka streaming, Delta Lake, SAS, TensorFlow/Keras, PyTorch, Flask, CNN, RNN, LSTM, Hierarchical Clustering, Spark NLP, NLP, pytessseract, PyMyPDF, CoreNLP, OpenCV, Docker, Kubernetes, MLflow, Kubeflow, Jira, EPIC, REDCap, Laboratory Information Management System, HL7/FHIR

Regulatory & Compliance knowledge: HIPAA (certified), GDPR, PCI-DSS, SOX, CCPA, GxP, NIST security and privacy standards My Ph.D. study (2018) was in Systems Engineering & Machine Learning (ML) where I used sophisticated open source tools for data mining, and machine learning techniques to model and develop an intelligent Decision Support System (iDSS) for lowering the costs of Service Calls for smart meters.

Professional Experience

Kinometrix Inc, Washington D.C. 2020

KinometriX is a startup that focuses on preventing falls in hospitals. Chief Data Scientist [Consultant] [2020 - present]

• Owning and driving the Data and Advanced Analytics Department vision, strategy, roadmap, and execution.

• Defining and overseeing how the Organization captures, maintains, and applies data in order to support business strategy.

• Architecting and developing the machine learning model to analyze the time-series data, predict Inpatient Fall Risks and provide specific actionable care plans for nursing staff to manage risks, protect and minimize patient falls; and increase ROI.

• Using Python, Jupyter Notebook, Docker, and AWS Services for the development and deployment of the model.

• Succeeded as Sub-Investigator on the Inpatient Falls study to get the Institutional Review Board (IRB) approval to extract datasets from EPIC Clarity and Nurses’ database in a safe way. Cornell University - Instructor & Advisor, Data Science (DS) Professional and Executive Programs 2020

• Teaching Python Programming, Python for Data Science, and Machine Learning Certificates’ courses within the DS program.

• Taught over 526 graduate students and professionals to date with > 96% success rate.

• Evaluating and advising on Visualization, Data Analytics SQL, and Tableau courses to be newly introduced at Cornell University. Inova Health System, Washington D.C. 2018 - 2019

Inova Health System is a leading non-profit healthcare provider in Northern Virginia with a mission to provide world-class healthcare

– every time, every touch – to each person in every community it has the privilege to serve. The system is a network of hospitals, outpatient services, and healthcare centers; with Inova Fairfax Hospital ranked #1 hospital in the Washington, D.C. metropolitan. Director, Research Informatics [2018 – 2019]

• Oversaw the Research Informatics department’s strategy, roadmaps, technologies, solutions, and daily operations and delivery.

• Led, coached, and developed agile teams who delivered state-of-the-art Research Data Infrastructure, Data Management & Governance, Data Science, and Advanced Analytics services in hybrid on-premise and cloud environments to maximize ROI.

• Automated and led the data modeling and data management flawless execution of the VICTORIA program which is a large phase III, drug development program supported by Merck & Bayer to investigate the safety and efficacy of Vericiguat, a novel soluble guanylyl cyclase stimulator in the treatment of systolic heart failure; and delivered safely and successfully 20,000+ biomarkers samples and 4,000+ genotyping samples with high customer satisfaction at IHVI Service Line & Merck.

• Developed an MVP to extract information from scanned PDF files, Acroform and XFA based PDF files and classified content. Joseph Siryani Page 2

• Developed a rapid prototype and MVP for the deep learning model for 3D DICOM image analysis to predict anomalies in dense breast tissue using Kubeflow to orchestrate the complete machine learning process, from data acquisition to model serving.

• Leveraged real-world data such as EMR/EHR, EDC (operational, clinical, & research), Patient Forms, Medical Notes, Medical Claims, Biospecimen, WGS, mRNA, Patient Surveys, Payment, and Tickets, and deployed products including innovative data science solutions across multiple Research and Clinical Lines of Services such as Translational Medicine, Genomics Laboratory, Heart & Vascular, Spine & Neuroscience, Cancer and Oncology, Operational Research, Pediatrics, and Pharmacy.

• Architected and oversaw the end-to-end data management lifecycle: Data Sources, Data Acquisition & Disposal, Data Storage, Data Processing & Enrichment, Data Analytics & Discovery, Data Visualization & Distribution, and overall Data Governance.

• Reviewed business processes, identified & approved opportunities where AI improved the operations efficiency & automations.

• Led the research informatics analytics program that enabled accelerated patient and drug discoveries and insights at scale.

• Introduced Innovation culture by implementing recurrent Team Hackathons which resulted in idea generation pipeline and implementation of automated financial solution that replaced paper and spreadsheet manual work and maximized ROI.

• Championed innovation initiatives to implement the next generation Data Lake with a holistic data governance, system level and service line ready to consume business data and data science framework to introduce applied AI and machine learning.

• Provided expert feedback and guidance on visualizing analytics and developed data story telling for non-technical audiences.

• Collaborated with my Analytics counterpart leaders (CAO, CIIO, CDO) at Duke Health, Intermountain Healthcare, Mount Sinai, Children’s Hospital of Orange County, and Rush Medical Center; to understand their Adoption Model for Analytics Maturity journey, encountered challenges and how they overcame them, and to understand their Machine Learning tools for Clinical Applications, in order to leverage predictive analytics’ best practices to augment the value of care at Inova.

• Established and maintained relationship with George Mason University where I serve on their Innovation DataLab Working Group as a Board Member to advance Data Science, AI, Analytics, and Computing Strategic Initiatives.

• Led the High-Performance Computing cloud transformation initiative which resulted in saving $470K in 2019.

• Evaluated the landscape of tools and Artificial Intelligence based technologies to understand what will unlock new capabilities.

• Developed Standard Operating Procedures that ensured operational and patient data integrity, and optimized workflows.

• Developed internal operating reports that quantified departmental projects performance & visualized via Tableau dashboards.

• Built and maintained data systems including but not limited to decision support, business intelligence, scaled data warehousing, data lakes for petabyte genomics data, metadata repositories, data catalogs, and Enterprise data storage. Digigo LLC, Washington D.C. 2017

Digigo is a digital and analytics business transformation enterprise that provides the Federal Government & Partners with highly effective advanced analytics and cloud modernization solutions to enriching customer experience. Senior Director – Data Science & Decision Intelligence [2017]

• Developed machine learning based solutions, advanced analytics portfolio, and digital transformation framework.

• Provided guidance and support to a Health Information Exchange (HIE) research to map complex relationships among healthcare systems, and to estimate financial performance trends, and the HIE adoption rate. Ericsson, Multiple Locations Worldwide

Ericsson is the driving force behind the Connected Society and a world leader in information communications technology & services. Ericsson, Washington D.C. 2011-2016

Director, Data Science & Cloud Transformation [2015-2016]

• Led programs to standardize advanced analytics, data visualization techniques, automation, and cloud transformation.

• Developed real-time machine learning models for detecting anomalies in wireless equipment and providing automated decision support. Director of Operations & Business Development - Sprint Customer Unit / Key Account [2011-2015] In a client-focused role, oversaw the entire Consulting & Systems Integration [CSI] business portfolio P&L, with an operating budget of $16.1M, operations, business development and sales support towards Sprint customer.

• Grew the CSI Services by 25% to $61M business with new streams revenues and solid profitability.

• Led analytics programs and data governance leveraging the massively collected data through the OSS System. Previous Experience Summary

• Line Manager, Ericsson (Global Services – IPTV & MSDP Centers of Excellence), Montreal, Canada

• Senior Project Manager, PMP [2003-2006] – Ericsson, Montreal, Canada

• Program Manager, Software Supply – Ericsson, Dallas, TX Education

PhD [2018] in Systems Engineering (Research - Machine Learning), George Washington University, Washington D.C. FinTech Certificate Program [2020], Cornell University Executive Management Program [Mini-MBA], McGill Desautels Institute, Montreal, QC Ericsson Executive Development Program - Leadership Core Curriculum (LCC) Master of Science, Major in Computer Engineering, Chalmers University, Gothenburg, SE Bachelor of Science, Major in Computer Engineering, Gävle University, Gävle, SE Publications

• Internet of Things Ecosystem - Healthcare Applications. CIO Applications (2019)

• intelligent Decision Support System for lowering the costs of Service Calls for smart meters. ProQuest (2017)

• Siryani, J. (2017). A Machine Learning Decision-Support System Improves the Internet of Things’ Smart Meter Operations. IEEE IoT Journal.

• Siryani, J. (2015). Framework using Bayesian Belief Networks for Utility Effective Management and Operations. 2015 IEEE First International Conference on Big Data Services and IoT.

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