CIO of Integrated DNA Technologies, Inc. (IDT). IDT has been empowering genomics laboratories with an oligonucleotide manufacturing process unlike anyone else in the industry, with the most advanced synthesis, modification, purification, and quality control capabilities available. Since its founding in 1987, IDT has progressed from a leading oligo manufacturer to a genomics solutions provider supporting key application areas such as next generation sequencing, CRISPR genome editing, synthetic biology, digital PCR, and RNA interference. IDT manufactures products used by scientists researching many forms of cancer and most inherited and infectious diseases.

Leica Biosystems is a $1B+ cancer-focused diagnostics operating company in Danaher’s $30B diagnostic and life sciences portfolio. • Defined global AI Go-To-Market strategy - what to build, who to partner with, who to buy/invest in• Directed all aspects of pioneering a new AI & ML Strategic BU from inception to first customer ship• Hired, inspired, & mentored a team of 25+ Computer Vision Scientists, Biologists, and Pathologists• Managed a network of 40+ external pathologists as part of our Ground Truth collection effort• Nurtured & managed all AI & Digital Pathology partnerships, KOLs, & early adopters company-wide• Collaborated with RA/QA & Med. Science Affairs to define annotation protocol for Ground Truth collection• Collected 6000 3x annotated Ground Truth images for a supervised breast tumor Computer Vision model • Built Multi-Class Computer Vision models in Breast and Prostate cancer to detect & subtype disease state• Started Ground Truth collection for mitotic count segmentation model• Designed plans to imbue next generation tissue scanner with AI to differentiate product offering• Built & integrated an AI viewer to render the results from our inference engine• Developed UAT protocols, engaged KOLs, & enrolled early adopter customers for feedback on 1st AI model• Achieved 40% productivity gains in early-adopter pathology labs using our AI Suspicious Area Finder• Preparing a Class II FDA submission for SaMD for Suspicious Area Finder on Breast tissue• Invented/Co-invented 13 inventions & 6 provisional patents in machine learning & Computer Vision• Reviewed & presented 100+ Research Papers on AI/ML & DigiPath (LinkedIn #HeroesInHealthcareAI)

• Built approved prioritized Roadmap & AI New Product Development Innovation Funnel of $62M• Designed, planned, & executed AI use case input from Voice of Customer & top global pathology KOLs• Synthesized disparate MaxDiff & Frequency/Frustration maps into actionable AI Use Cases• Elevated organizational knowledge around which use cases are actually addressable by current AI, ML, DL, & Computer Vision technologies• Developed & continuously tailored AI Partner, Buy, & Build Plans for US, Europe, & China markets• Designed & executed on AI Resourcing Plan identifying/attracting/retaining PhDs in Bio/Chem and CS• Created the Blueprint and Playbook for the company's AI strategy• Built a 3-year Financial Plan to catalyze the creation of a new AI & ML Strategic Business Unit

Najdorf : AI and Machine Learning consulting firm specializing in monetizing clients' existing data sets and delivering actionable insights. Clients: Bio-Rad, Blue Shield of California, Cardinal Health, GSK, Loma Linda University, McKesson Health, Pfizer, Salesforce.com, Stanford University, Sutter HealthMy Role: I managed the daily efforts of a global team of 30+ high-caliber BAs, PMs, software developers, DBAs, and Data Scientists across software development, consulting, and training lines of business.• Built a POC supervised Computer Vision model on whole-slide images of suspected breast cancer specimens to decrease pathologists' time evaluating non-malignant tissue cases• Developed early-warning machine learning model for NICU clinicians caring for premature newborns under duress. Early detection of infant sepsis allows clinicians to rapidly administer antibiotics to save lives. • Developed Treatment Cost Estimator, for payer client, allowing members web portal access to estimate remaining deductible, Out-Of-Pocket, and retail cost of upcoming surgical procedures • Developed Patient Review of Providers, for payer marketing teams, allowing members web portal access to view and rate their doctor in a Physician Scorecard• Developed analytics, for payer executives, identifying California healthcare providers billing for procedures at a per-patient rate greater than national average resulting in lower fraudulent claims• Developed predictive models for a hospital group, identifying patients with high risk of re-admittance. Increased quality of care, decreased costs, and decreased readmit rates• Experienced using AWS Cloud with Apache Spark, EMR, Glue, Kafka, Kinesis, Lambda with S3, Redshift, RDS, MongoDB, and DynamoDB ecosystems.Technologies: C, C++, Java, Python, Scala, MATLAB, Octave, R, Shiny, Tableau, PowerBI, Domo, Alteryx, Cloudera, Netezza, AWS, GCP, Hadoop, Hive, MongoDB, Pig, Spark, pySpark, NumPy, Pandas, TensorFlow, Keras