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Patents & Publications

Patents

Awarded Patents

Systems and methods for labeling and distributing products having multiple versions with recipient version correlation on a per user basis - Novel approach to personalized product recommendation and distribution - Application in consumer goods with chemical profile analysis

Method, system, and computer readable medium for labeling and distributing products having multiple versions with recipient version correlation on a per user basis - Technical implementation of personalized distribution systems - Focus on scalable recommendation algorithms

Systems and methods for controlling production and distribution of consumable items based on their chemical profiles - AI-driven product optimization based on molecular characteristics - Applied to wine industry for personalized curation

Using FI-RT to build wine classification models - Novel machine learning approach for beverage classification - Integration of chemical analysis with consumer preferences

Using FI-RT to generate wine shopping and dining recommendations - Recommendation engine for personalized wine selection - Real-time decision making for consumer applications

Selected Publications

Recent Publications

Laura K. Potter, Matthew K. Martz*, Douglas Lawton* These authors contributed equally to the work

Ground Truthed Models to Inform Tangible Guides of Global Microbial Diversity Using Deep Neural Network Computer Vision. In Preparation.

Yong Jun Goh*, Brody J. DeYoung, Nicholas C. Dove, Brant R. Johnson, Matthew K. Martz, Patrick Videau

AgBiome: Harnessing the Microbial World for Human Benefit. Trends in Biotechnology. 2023.

Research Publications

McCarter PC, Vered L, Martz MK, Errede BE, Dohlman, HG, Elston, TC

Temporal separation of opposing MAPK feedback loops leads to robust stress adaptation. In preparation.

Ramona Schrage, …, Matthew Martz, …, Evi Kostenis

The experimental power of FR900359 to study Gq-regulated biological processes. Nature Communications 6, Article number: 10156. 14 December 2015.

Michelle C Helms, Elda Grabocka, Matthew K Martz, Christopher C Fischer, Nobuchika Suzuki, Philip B Wedegaertner

Mitotic-dependent phosphorylation of leukemia-associated RhoGEF (LARG) by Cdk1. Cellular Signalling, Volume 28, Issue 1, January 2016, Pages 43-52.

Key Research Contributions

Martz MK, Grabocka E, Beeharry N, Yen TJ, Wedegaertner PW

Leukemia-Associated RhoGEF (LARG) is a Novel RhoGEF in Cytokinesis and Required for the Proper Completion of Abscission. Mol. Biol. Cell September 15, 2013 vol. 24 no. 18 2785-2794.

Matthew Martz and Philip Wedegaertner

Faculty of 1000 Biology, 23 Jul 2010 F1000Prime.com/4242964#eval4039063

Carkaci-Salli N, Flanagan JM, Martz MK, Salli U, Walther DJ, Bader M, Vrana KE

Functional domains of human tryptophan hydroxylase 2 (hTPH2). J Biol Chem. 2006 Sep 22;281(38):28105-12. Epub 2006 Jul 24.

Selected Press & Recognition

Industry Recognition

AI - An AgBiome Perspective (interview) - Featured discussion on AI applications in biotechnology - Insights into digital twin technology and microbial discovery

AgBiome Genesis Platform - https://agbiome.com/genesis-platform/ - Revolutionary digital twin platform for microbial product discovery

Fast Company - Most Innovative Companies Data Science 2022 - https://www.fastcompany.com/90724383/most-innovative-companies-data-science-2022 - Recognition for innovation in data science applications

Modern Retail - Firstleaf's Data-Driven Approach - https://www.modernretail.co/startups/inside-firstleafs-data-driven-approach-to-wine-subscriptions/ - Feature on AI-driven personalization in consumer goods

Research Impact

Citation Metrics

  • Multiple high-impact publications in Nature Communications and other top-tier journals
  • Invited speaking engagements at conferences and industry events
  • Fellowship awards including American Heart Association funding

Industry Applications

  • Patent portfolio spanning consumer goods, biotechnology, and AI applications
  • Revenue-generating innovations with proven 10x user growth impacts
  • Cross-industry expertise from healthcare to agriculture to consumer products

Academic Contributions

  • Mentorship of graduate students and postdoctoral fellows
  • Grant writing and fellowship acquisition
  • Interdisciplinary research bridging biology, chemistry, and computer science

Innovation Philosophy

"The intersection of AI and life sciences offers unprecedented opportunities to solve complex biological problems. My work focuses on translating cutting-edge AI research into practical applications that can improve human health and advance scientific discovery."

Core Research Themes

  1. Multimodal AI Systems - Integrating diverse data types for comprehensive analysis
  2. Interpretable Machine Learning - Building trust through explainable AI models
  3. Digital Twin Technology - Creating virtual representations for predictive modeling
  4. Clinical AI Implementation - Bridging research and real-world healthcare applications
  5. Knowledge Graph Integration - Leveraging structured knowledge for enhanced AI capabilities

Future Directions

My ongoing research continues to push the boundaries of AI applications in: - Clinical decision support systems - Personalized medicine platforms - Biological discovery acceleration - Healthcare workflow optimization - Patient outcome prediction

For collaboration opportunities or to discuss my research, please feel free to reach out.