• Volunteer• Mentored and gave strategic advice to UCSF Catalyst Award winners, showcasing abilities in strategic insight and planning.• Provided AI business advice to startups• Guided UCSF startup founders in developing AI-driven business strategies

Aid life science and digital healthcare/fintech businesses in gaining strategic advantage with artificial intelligence. 70% of organization's AI projects are still stuck in the pilot phase. We help these businesses by laying out a detailed roadmap for transformative AI business strategy. The key benefits of our AI business consulting can include increased productivity, innovation, sales, job satisfaction, and decreased costs.As AI business consultants, we focus on:• AI consulting for businesses seeking digital transformation• AI biopharma business consulting• Digital Health/Fintech AI startup advisory services• Small business AI consultant services

Specialized expertise in analyzing and evaluating AI-driven multi-omics technologies and their applications across various industries, helping organizations make smarter decisions about AI implementation and strategy.

• Evaluated novel genomic technologies for potential applications in diagnostics and research• Analyzed scientific literature and market trends to identify emerging opportunities in biotechnology• Communicated complex technological concepts to cross-functional teams

• Evaluated opportunities for capillary electrophoresis in emerging technologies.• Gained knowledge of quality management systems and ISO quality standards, medical device regulations (ISO 13485 and IVDR), and related standards.• Took course, UCSC MEDD.X408 Regulation of in vitro Diagnostics in Europe and in the US.• Helped write documentation for IVDR self-declaration of Applied Biosystems capillary electrophoresis consumables and 3500 Dx instrument.

Consulting for grant writing, scientific design, and NGS assay development.

Our technical aim was to identify pathogens and report their antibiotic sensitivity in less than an hour. Because of this short time to result, doctors would know the microbial ID and results of Antibiotic Sensitivity Testing (AST) before prescribing antibiotics.Our technology, Dynamic Bio-Affinity Patterning, has similarities to whole cell affinity chromatography. When developed, known bacteria are run through micro-channels with sections containing different ligands attached to a 3D scaffold. AI is used to determine the pattern of bacteria binding to the different ligands. Once the patterns are determined for known bacteria, like the ESKAPE pathogens, unknowns are run and then identified via their binding pattern. Phenotypic AST is performed in 30 minutes. The challenge was selling a new platform for microbe ID to investors that wasn’t DNA sequencing or PCR based. We put our efforts into showing feasibility to decrease their risk, but the chemistry on a shoe-string budget took awhile. This allowed our competitors (like isothermal amplification coupled with CRISPR-Cas12) to catch our projected performance for microbe ID, so we decided to stop the venture.• Co-wrote NIH and NSF SBIR grants• Recruited 2 co-founders, 4 advisors, and 1 collaborator.• Pitched to investors• Designed, funded, and managed feasibility studies.• Worked in Lab.

I aided in development of a new NGS barcoding technology for long linked reads, and I designed primers and quantified products using qPCR. I advised the CEO and colleagues on emerging technologies. I trained new hires in silica based and SPRI (Ampure) DNA isolation, and gel electrophoresis, and I supervised a research associate and a technician. The challenge was trying to compete with other companies, like Affymetrix and Illumina.

The challenge was optimizing the Whole Genome Sequencing (WGS) DNA libraries, which were mate-pair with 2 adapters on circular ssDNA. We successfully optimized the libraries for %GC bias, time to result, mapping yield, SNV total calls, genome fraction with sequence coverage greater than 5x, exome fraction with sequence coverage greater than 5x, and chimeras. • Optimizing library preparation required a thorough understanding of DNA polymerases (T4, Q5, PfuCx, Taq, and Klenow), polynucleotide kinase, USER enzyme, and DNA nucleases (MBN, ExoVll, T7, and S1). • Our library had similarities to succeeding MGIEasy Universal Library Conversion Kit (App-A) and circle-sequencing libraries for determining off target cutting by CRISPR:Cas9 (Tsai et al. (2017) Nat Methods 14, 607).