Benjamin Huang Email & Phone Number

Data scientist focused on enabling scaling of manufacturing operations and product margins. Leveraged in depth on the floor manufacturing experience and data science knowledge to drive operational efficiency projects.Data Science◦ Developed tools and processes to automatically detect failures mid-process and limit non value added processes◦ Leveraged digital twin models to perturb factory inputs and estimate impact to yield, throughput, and CAPEX expenditures.◦ Developed keystone heuristic algorithm to increase manufacturing throughput by 300% and reduced product delivery time by 50%◦ Led project to save 75% in critical raw material consumption costs and increased product outs by 50%◦ Developed novel KPI metrics to keep pulse on manufacturing bottlenecks◦ Leveraged computer vision and clustering algorithms to classify failure modes on microscopy images of E. Coli growth colonies◦ Perform investigations into acute failure events and prescribe potential continuous improvement projects◦ Developed ensemble model to predict product success using retrospective manufacturing quality dataData Engineering◦ Developed and maintained robust ETL pipelines using databricks and snowflake to ingest unstructured data from MES, ERP, and equipment logs into dashboard ready tables◦ Developed self serve plotly dash dashboards to allow manufacturing operators and engineers to monitor business critical KPIs

Understanding operational inefficiencies through data and bringing manufacturing concepts, along with process characterization to a clinical lab testing space.- Pioneered data driven methodology to measure manual process efficiency- Implemented process changes to manual workflow and increased process efficiency by +20%- Developed tools and dashbords to monitor production equipment for critical parameters impacting equipment up-time

Responsible for overall health and capabilities of a high volume manufacturing line. This typically involves keeping a pulse on the health of the manufacturing line and characterizing and understanding new failure modes in order to implement fail safe or corrective procedures. Routinely work cross-functionally with GIS, Supply Chain, Manufacturing, Quality and Analytics team to help drive COGS reduction projects, resolve customer complaints, and increase capacity and yield of manufacturing line.- Lead continuous improvement projects to reduce cost, variability, and improve cycle time in a 24/7 manufacturing environment- Create standard operating procedures (SOP), work instructions, FMEA for various process areas- Data mine manufacturing line health and chart path forward for 5 year plan- Process Health Monitoring and trending to determine root cause failure- Create/Revise processes to reduce rework rate, noncompliance occurrences, and increase in traceability of product- Continuously monitor manufacturing process capabilities through SPC and perform failure/root cause/commonality assessments- Window new critical processes to minimize and characterize process risk- Support COGS reduction efforts through second sourcing of components- Conceived and implemented method for real-time failure reporting and alerting for quick response to manufacturing component deviations- Design and quality manufacturing tools/aids for repeatability & reproducibility- Establish data pipelines to monitor manufacturing key performance metrics to allow quick status updates of manufacturing health

- Integrate, Optimize, Sustain, and categorize failure modes for existing and newly developed assays- Data mine historical data to establish manufacturing specifications for new products- Work cross functionally with IT, Quality, Manufacturing, R&D, and end user to develop new processes for products and continuously improve existing products- Develop and execute edge case test plans to characterize process parameters. Simulate failure modes and recommend fail safe procedures- Create end-to-end assay automation process from sample dilution to automated data analysis. Automation processes were developed with complete flexibility for varying daily needs and built with recovery options in mind to allow for complete run recovery in the event of unforeseen errors.- Maximize accuracy and precision of flow cell based assays- Designed and executed assay guardbanding experiments to establish failure boundary point- Characterize liquid handling equipment difference and minimized %CV between equipment from 30% to 3%.- Establish software requirement specifications and software verification protocols- Create one-off fixtures/prototypes using CAD and 3D printing

9410 Carroll Park Drive San Diego, Ca 92121

-Developed and optimized new FRET, ELISA, Luminex, and proprietary novel assays (CEER) for retrospective disease research. Utilize existing literature research to determine best candidate proteins to measure.-Took developed assays through a validation phase and implement assay acceptance criteria and controls.-Automated multiple Luminex kits (~50 analytes) using an automated liquid handling platform.-Optimized and improved new and existing automated assays to ensure good liquid transfers-Data processing post assay run also automated through the use of R, Python, and VBA scripts to decrease possibility of operator error. Automating the data processing reduced a 4+ hour process to 20 minutes worth script running and eliminated all operator errors.-Utilized Python, R, JMP to do large data set analysis to build longitudinal patient profile from clinical sample data generated through various studies. -Troubleshooted assays using Measurement Systems Analysis and other methods to determine the factor impacting reproducibility and robustness of assays.-Worked with 3rd party vendors to ensure lot to lot variability and robustness of assays

Help research the role of SIRT1 and STAT3 proteins in isoform specific transgenic and knockout mice. Duties involve the preparation of protein lysates from various harvested tissues from mice, determining whole protein concentrations through protein assays and preparing normalized samples for western blots and ChIP-Seq assays. Samples are then analyzed to determine the protein-protein interaction of SIRT1 and STAT3 in the insulin signaling pathway. Additional duties involved mouse husbandry, determining the genotype of mice via PCR, determining level of mRNA expression via qPCR, preparation of data for academic journal presentation, and statistics.