Alcantara Data Solutions

About

Lucas Alcantara

ABOUT

I’m a data manager and software developer passionate about building infrastructure that makes research data accessible, reusable, and insightful. With a strong foundation in the life sciences and advanced expertise in computational systems, I’ve dedicated my career to bridging the gap between data producers and decision-makers.

I specialize in developing data architectures and full-stack applications that transform complex datasets into usable tools for researchers, organizations, and institutions. Whether working with real-time sensor data or historical agricultural trials, I create robust and scalable systems for data capture, storage, integration, validation, and visualization.


What I do

  • End-to-End Data Integration: Build custom pipelines and databases to move data from field devices and legacy systems into scalable and queryable formats.
  • Rapid Application Development: Deploy full-stack applications (web-based dashboards, portals, APIs) using R and Python in Dockerized environments.
  • Collaborative Infrastructure Design: Work closely with scientists, technicians, and IT staff to design systems that balance usability, automation, and security.
  • FAIR Data Advocacy: Promote and apply FAIR principles (Findable, Accessible, Interoperable, Reusable) in data infrastructure design.
  • Statistical and Machine Learning Models: Apply analytical approaches to support research questions and optimize data-driven insights.


From Researcher to Researcher

My work is grounded in my experience as a researcher — someone who’s faced the same challenges I now help solve. I earned my Ph.D. in Animal Biosciences from the University of Guelph, where I applied machine learning to improve genetic selection programs in dairy cattle. I’ve published peer-reviewed studies, designed research databases, and developed analysis pipelines from the ground up.

Over the years, I have:

  • Built a decision-tree model to predict insemination outcomes in Holsteins using national datasets.
  • Created a machine learning pipeline to classify text-based breeding protocols using NLP techniques.
  • Estimated genetic parameters for over 60 traits in dairy cattle using Bayesian bivariate models.
  • Developed data infrastructure and interactive dashboards for large-scale projects like the Resilient Dairy Genome Project.
  • Automated the processing of phenotypic and pedigree data from national evaluations to support Canadian feed and methane efficiency research.

Building from ETL systems to dashboards, I understand what researchers need to ask better questions and trust their data.

Current Roles

Manager, Research Centre Data

Office of Research, University of Guelph – Sept 2022 to Present

Design and implement enterprise-level data systems for the Agri-food Research Centres under the Ontario Agri-Food Innovation Alliance.

Key accomplishments:

  • Built a fully automated ETL pipeline and PostgreSQL database from scratch.
  • Developed web dashboards and portals using R Shiny, Docker, and Tailscale VPN.
  • Led transition from fragmented legacy systems to modern IT infrastructure.
  • Delivered training workshops on R, Linux, and GitHub for staff and researchers.
  • Led applied research software projects in feed intake, sensor validation, and data curation.

Sr. Analyst, Systems, Data and Research Technologies (Part-time)

Department of Animal Biosciences, University of Guelph – 2024 to Present

Support departmental IT, research infrastructure, and faculty and students with high-performance computing, database development, and software tools.

Key responsibilities and highlights:

  • Manage and secure complex Linux-based computing environments used for genetic evaluations, research databases, and custom web applications.
  • Design and maintain research pipelines using Perl, R, and SQL for data processing and modeling.
  • Provide technical leadership on IT infrastructure, software deployment, and security best practices.
  • Advise on custom software solutions for data-heavy research challenges.

Solopreneur / Software Developer

Alcantara Data Solutions – Jan 2023 to Present

Lead custom software development and consulting services to research clients needing automated pipelines, remote data collection, and secure data infrastructure.

Notable projects:

  • Deployed data pipeline for methane gas sensors used on dairy farms across two countries. Read more.
  • Engineered IoT-compatible software for remote sites, featuring real-time monitoring and dashboards. Read more.
  • Provided PostgreSQL database design, ETL pipeline development, and front-end management tools. Read more.


Previous Experience

Livestock Data Technician

University of Guelph – Jul 2021 to Aug 2022

  • Managed IT systems at the Elora and Ponsonby Livestock Research Centres, including server configuration, data backups, and hardware maintenance.
  • Provided technical support to researchers, ensuring smooth data access, storage, and analysis in multi-user Linux environments.
  • Built R Shiny applications and Dockerized analytics dashboards to support research operations.
  • Designed and implemented an ETL pipeline that integrated multiple on-farm data sources into a centralized PostgreSQL database.

Graduate Research Assistant

University of Guelph - Sept 2018 – Aug 2022

  • Automated large-scale data ingestion pipelines (Perl, Bash) for downstream processing  large genetic and phenotypic datasets.
  • Built and maintained SQL databases (MariaDB) to serve industry datasets for students under confidentiality agreements.
  • Developed ML models to predict insemination success and classify breeding protocols.
  • Designed interactive dashboards and data visualizations for genetic research projects.

Visiting / Co-op Student

University of Guelph & Semex Alliance – May 2018 to Aug 2018

  • Contributed to genomic research by automating data quality control and analysis pipelines to support genetic evaluations in dairy cattle.
  • Streamlined genome-wide association studies (GWAS) on key conformation traits, improving the efficiency and reproducibility of research workflows.
  • Supported the integration of large-scale genomic datasets into decision-making tools for genetic selection and breeding strategy development.

Student Supervision & Mentorship

I regularly supervise and mentor graduate students working on data-intensive research projects in agriculture and animal science at the University of Guelph. Whether through formal co-supervision or collaborative project leadership, I take a hands-on, researcher-to-researcher approach focused on practical impact, reproducibility, and interdisciplinary communication.

Formal Co-Supervision

  • Diya Pancholi (MSc, Data Science – Fall 2023) - Supervisor: Prof. John Cant

Feed Intake Monitoring Dashboard – Developed an alert-driven dashboard to monitor automated feeding systems at the Ontario Dairy Research Centre. Focus included feed theft detection, animal-specific intake deviations, and bin malfunction reporting.

  • Somaye Ahangarsaryazdi (MSc, Data Science – Fall 2024) - Supervisor: Prof. Adrian Correndo

ODRC Metadata & Usage Explorer – Led development of SQL-driven reports and summary tools to power a public-facing view of metadata and usage statistics from the Ontario Dairy Research Centre Data Portal.

Project-Based Supervision of Graduate Research Assistants

  • Patrick McMillan (PhD, Bioinformatics)

Sensor Data Validation Pipeline – Designed and tested systems for automated detection of faulty data from walk-over weight scales and 3D cameras used in dairy cow monitoring.

  • Busayo Kodaolu (PhD, Environmental Science)

OAC Historical Research Data Explorer App – Built a Shiny-based application for exploring metadata, visualizing raw research data, and generating descriptive statistics from archived trial datasets.

These collaborations are an extension of my commitment to building sustainable, researcher-driven tools and mentoring students to contribute meaningfully to open, applied agricultural science.

Education



Interactive Dashboards (Published)

Dairy Research

Research Software Portals

Workshop & Training

Featured Publications

  • da Silva Pereira, M., Alcantara, L. M., de Freitas, L.M. et al. (2025) Microbial Rumen proteome analysis suggests Firmicutes and Bacteroidetes as key producers of lignocellulolytic enzymes and carbohydrate-binding modules. Braz J Microbiol. https://doi.org/10.1007/s42770-025-01627-8
  • Alcantara L. M., Huitema, C., & Edwards, M. A. (2023). Agri-food Data Canada: A data ecosystem serving agri-food sustainability. In C. Diaz, I. Casasús, F. Estellés, P. Llonch, M. Luque, M. Burke, & C. Mosconi (Eds.), ICAR Technical Series: Breeding for Resilience: Transitioning Diverse Livestock Farming Systems into the Future (Vol. 27, pp. 27). ICAR, Arthur van Schendelstraat 650, 3511 MJ Utrecht, The Netherlands. Retrieved from https://www.icar.org/wp-content/uploads/2024/01/ICAR-Technical-Series-27-Toledo-2023-Proceedings.pdf
  • Martin, A. A. A., Id-Lahoucine, S., Fonseca, P. A. S., Rochus C. M., Alcantara L. M., et al. 2022. Unravelling the genetics of non-random fertilization associated with gametic incompatibility. Scientific Reports 12, 22314. https://doi.org/10.1038/s41598-022-26910-8.
  • Alcantara, L. M., Schenkel F. S., Lynch C., Oliveira Junior, G. A., Baes, C.F. and Tulpan, D. 2022. Machine learning classification of breeding protocol descriptions from Canadian Holsteins. Journal of Dairy Science. https://doi.org/10.3168/jds.2021-21663.
  • Alcantara, L. M., Baes C.F., Oliveira Junior, G.A. and Schenkel, F.S.. 2022. Conformation traits of Holstein cows and their association with a Canadian economic selection index. Canadian Journal of Animal Science.  https://doi.org/10.1139/CJAS-2022-0013.
  • Oliveira Junior, G. A., Schenkel, F. S., Alcantara, L. M., Houlahan, K., Lynch, C. & Baes, C. F. 2021. Estimated genetic parameters for all genetically evaluated traits in Canadian Holsteins. Journal of Dairy Science. 9002-9015. 104(8). doi.org/10.3168/jds.2021-20227.

Featured Abstracts

  • Martin A. A. A., Id-Lahoucine S., Fonseca P. A. S. , Rochus C. M., Alcantara L. M., et. al. (2022). Genotypic interaction between gametes: mate incompatibility in dairy cattle. In: Book of Abstracts of the 73rd Annual Meeting of the European Federation of Animal Science (EAAP), Porto, Portugal.
  • Lopes L., Houlahan K., Alcantara L. M., Oliveira Jr. G. A., Tulpan D., Miglior F., Schenkel F. S., Baes C. F. (2022). Genetic parameters for rumination time and traits related to sustainable dairy production. In: Book of Abstracts of 12th World Congress on Genetics Applied to Livestock Production (WCGALP), Rotterdam, the Netherlands.
  • Alcantara, L. M., Tulpan, D., Baes, C., & Schenkel, F. S. (2021). Machine learning algorithms for prediction of insemination outcome in historical data of Holstein cattle. Poster session (online), 2021 American Dairy Science Association Annual Meeting, Louisville, KY.
  • Alcantara, L. M., Schenkel, F. S. G.A. Oliveira Junior, G. A. & Baes, C. (2020). Conformation traits of Holstein cows and their association with the Pro$ selection index. Oral session (online), 2020 American Dairy Science Association Annual Meeting, West Palm Beach, FL.

Oral Presentations

  • Alcantara, L.M. (November, 2024). Desafios e Aprendizados: Aplicação de Boas Práticas de Cibersegurança em Estações de Pesquisa Agropecuária. Webinar: Segurança Cibernética no Campo: Protegendo a Agropecuária do Futuro. Escola Nacional de Gestão Agropecuária. Brasília, DF, Brazil
  • Alcantara, L.M, Dehghantanha, A. (2024, April). Barn Cybersecurity Simulation hosted at the Ontario Dairy Research Centre. The Future of Cybersecurity in Agriculture, Guelph, Ontario, Canada.
  • Alcantara, L.M. (2023, October). The Ontario Dairy Research Centre Data Platform and it's support to the Resilient Dairy Genome Project. SCC-84 Multistate Meeting, Ithaca, New York, United States.
  • Innes, D. J., Alcantara, L. M., Cant, J. P. (2023, June). From averages to individuals: a data cleaning dashboard for automatically collected feed intake data. In: American Dairy Science Association Annual Meeting (ADSA), Ottawa, Ontario, Canada.
  • Alcantara, L. M., Huitema, C., Edwards, A. M. (2023, May). Agri-food Data Canada: A data ecosystem serving agri-food sustainability. 2023 International Committee for Animal Recording (ICAR) Annual Conference. Toledo, Spain.
  • Alcantara, L. M. Research Centre Data Portals. Agri-Food Data Canada Spring Launch. Guelph, ON.
  • Oliveira Junior G. A., Rochus C. M., Alcantara L., Lynch C., Schenkel F. S., Baes C. F. (2022, June). Genetic architecture of fertility traits in natural and hormonal synchronized dairy cows. In: 2022 ICAR/Interbull Conference, Montreal, Quebec, Canada.
  • Alcantara, L. M., (2022, April). Building a machine learning model to identify text-based descriptions of hormonal synchronization protocols. Seminar presented online at the Centre for Genetic Improvement of Livestock, Guelph, ON.
  • Alcantara, L. M., Tulpan, D., Baes, C., & Schenkel, F. S. (2021, November). Machine learning algorithms for prediction of insemination outcome in historical data of Holstein cattle. Poster session (online), 2021 Dairy Cattle Reproduction Council Meeting. Kansas City, MO.
  • Alcantara, L. M., Schenkel, F. S, Baes, C., Lynch, C., Oliveira Junior, G. A., & Tulpan, D. (2021, October). Classification of breeding code protocol descriptions used with Canadian Holsteins. Report presented online at the Dairy Cattle Breeding and Genetics Committee Meeting, Guelph, ON.
  • Alcantara, L. M., Tulpan, D., Baes, C., & Schenkel, F. S. (2021, June). Machine learning algorithms for prediction of insemination outcome in historical data of Holstein cattle. Poster session (online), 2021 American Dairy Science Association Annual Meeting, Louisville, KY.
  • Alcantara, L. M., Tulpan, D., Baes, C., & Schenkel, F. S (2021, February). Intelligent algorithms for prediction of dairy bull fertility: project overview. Report presented online at the Dairy Cattle Breeding and Genetics Committee Meeting, Guelph, ON.
  • Alcantara, L. M. & Oliveira Junior, G. A. (2021, January). Development of an interactive web-based application to facilitate processing of pedigree data, deregression of EBV, and data visualization of genetic parameters. Seminar presented online at the Centre for Genetic Improvement of Livestock, Guelph, ON.
  • Alcantara, L. M., Oliveira Junior, G. A., Baes, C. & Schenkel, F. S. (2020, September). Development of an interactive web-based application to facilitate data visualization of genetic parameters. Report presented online at the Dairy Cattle Breeding and Genetics Committee Meeting, Guelph, ON.
  • Alcantara, L. M., Oliveira Junior, G. A., Baes, C. & Schenkel, F. S. (2020, September). Conformation traits of Holstein cows and their association with the Pro$ selection index. Report presented online at the Dairy Cattle Breeding and Genetics Committee Meeting, Guelph, ON.
  • Alcantara, L. M., Oliveira Junior, G. A., Baes, C. & Schenkel, F. S. (2020, February). Conformation traits and their correlation with Pro$. Report presented at the Dairy Cattle Breeding and Genetics Committee Meeting, Guelph, ON.
  • Alcantara, L. M., Oliveira Junior, G. A., Baes, C. & Schenkel, F. S. (2019, August). Conformation traits and their correlation with Pro$. Report presented at the Dairy Cattle Breeding and Genetics Committee Meeting, Guelph, ON.
  • Lynch, C., Schenkel, F. S., Houlahan, K., Oliveira Junior, G. A., Alcantara, L. M. & Baes, C. F. (2019, June). Understanding the impact of technologies and novel phenotypes on breeding strategies for genetics progress in dairy cattle. Poster session presented at the 2019 American Dairy Science Association Annual Meeting, Cincinnati, OH.

Awards & Scholarships

  • OAC Outstanding Student Staff Recognition Award (2022)
  • Hamilton Milk Producer's Association Scholarship (2018)
  • International Doctoral Tuition Scholarship (2018-2022)
  • Brazil-Canada Science Without Borders Scholarship (2013)

Meetings Attended

  • 46th ADSA Discover Conference: Milking the Data: Value-Driven Dairy Farming, May 2024, Itasca - IL
  • Future of Cybersecurity in Agriculture: Barn Simulation & Policy Networking, April, 2024, Guelph - ON
  • Cultivating Innovation: Intellectual Property Strategy for Researchers and Entrepreneurs, November 2023, Guelph - ON
  • SCC-84 Multistate Meeting. October 2023, Ithaca - NY
  • 2023 American Dairy Science Association Annual Meeting. June 2023, Ottawa – ON
  • 2023 International Committee for Animal Recording (ICAR) Annual Conference. May 2023, Toledo, Spain
  • Agri-Food Data Canada Spring Launch. May 2023, Guelph - ON
  • 2021 Dairy Cattle Reproduction Council Meeting. Online, November 2021, Kansas City – MO
  • Dairy Cattle Breeding and Genetics Committee Meeting. October 2021, Guelph – ON
  • 2021 American Dairy Science Association Annual Meeting. Online, June 2021, Louisville – KY
  • Open Industry Session. February 2021, Guelph – ON
  • Dairy Cattle Breeding and Genetics Committee Meeting. February 2021, Guelph – ON
  • Open Industry Session. October 2020, Guelph – ON
  • Dairy Cattle Breeding and Genetics Committee Meeting. September 2020, Guelph – ON
  • 2020 American Dairy Science Association Annual Meeting. Online, June 2020, West Palm Beach – FL
  • Open Industry Session. March 2020, Guelph – ON
  • Dairy Cattle Breeding and Genetics Committee Meeting. February 2020, Guelph – ON
  • Dairy Cattle Breeding and Genetics Committee Meeting. September 2019, Guelph – ON
  • Enabling Innovation – Genome Editing and the Canadian Regulatory Environment. March 2019, Toronto – ON
  • Open Industry Session. February 2019, Guelph – ON
  • Dairy Cattle Breeding and Genetics Committee Meeting. January 2019, Guelph – ON

Media

Video Interviews

News Articles


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