Interdisciplinary Research Scientist · Data Scientist · Applied Statistician

Turning complex data
into actionable patterns

Interdisciplinary researcher bridging biomechanics, data science, and human performance. Working with populations from athletes to older adults, I specialize in building Python-based data pipelines, statistical modeling, and finding conditional relationships in complex datasets. Background in mathematics with graduate training in movement science.

ferdinanddelgadophd@gmail.com LinkedIn Google Scholar movemeasure.com
Ferdinand Delgado, PhD

Ferdinand Delgado, PhD

PhD
Exercise & Nutritional Sciences
BS
Mathematics
10+
Years in Sport Science
4
Degrees & Certificates
Selected Work

Projects & Applications

Production tools, analytical pipelines, and research applications built to solve real problems with data.

Data
Pipeline

Automated Force Plate Assessment Reports

Built a complete Python-based report generation system that pulls athlete data from the Hawkin Dynamics API, processes force-time metrics, applies a custom biomechanical framework (Output / Strategy / Driver), and generates professionally formatted PDF reports with force-time curves, asymmetry analysis, and historical comparisons — both for individuals and full teams.

Python REST API Integration PDF Generation Data Visualization Statistical Analysis
View on GitHub →
Deployed in production for Move, Measure, Analyze LLC — generates client-ready reports from raw force plate data in under 60 seconds.
Statistical
Modeling

Gait Deterioration & Fall Risk Classification

Developed an analytical pipeline to classify fallers versus non-fallers using 6-minute walk test data from IMU-based gait analysis (APDM Mobility Lab). The approach segments gait cycles into quarters to examine fatigue-related deterioration patterns, extracting features like gait speed decline, variability changes, and asymmetry shifts across the walk. Statistical analysis includes assumption testing, effect size ranking, FDR correction, and logistic regression with ROC/AUC evaluation.

Python Logistic Regression ROC / AUC IMU Sensor Data Clinical Research
View on GitHub →
Novel quarters-based feature engineering approach to identify gait markers that discriminate fall risk in older adults (n=60).
Data
Engineering

Hawkin API → Excel Data Extraction Pipeline

Built Python scripts to extract full organizational data from the Hawkin Dynamics API — including athletes, teams, groups, and all historical assessment data — and output it into professionally formatted Excel spreadsheets. Handles pagination, rate limiting, data type mapping, and produces clean, analysis-ready workbooks for downstream use.

Python REST API Excel / openpyxl ETL Pipeline Data Cleaning
Transforms raw API data into structured, formatted spreadsheets — automating what previously required manual export and cleanup.
AI /
RAG

Biomechanics Research RAG System

Built a Retrieval-Augmented Generation system for querying biomechanics research literature. Ingests PDF textbooks and papers, chunks and embeds them into a ChromaDB vector database, and generates cited answers using the Claude API. Enables natural language queries against thousands of pages of research with source attribution and page references.

Python ChromaDB Claude API RAG Architecture Vector Embeddings
View on GitHub →
Query 4,500+ document chunks from biomechanics textbooks — bridging research literature with practical questions using AI.
Core Competencies

Expertise

Statistical Analysis

Multivariate analysis, logistic regression, interaction effects, effect sizes, FDR correction, ROC/AUC evaluation, assumption testing, normative modeling, and percentile analysis.

Python & Data Tools

Python for data pipelines, API integrations, automated reporting, and statistical computing. PDF generation, Excel automation, and data visualization.

Biomechanics & Human Performance

Force plate assessment, gait analysis, IMU sensor data processing, motion capture, and athletic performance testing. Deep domain expertise in translating movement data into practical insights.

Research Design

PhD-trained in experimental design, human subjects research (IRB), data collection protocols, literature review, and scientific communication.

Data Communication

Translating complex statistical findings into clear, actionable reports for non-technical audiences. Experience building automated reporting systems.

AI & RAG Systems

Building Retrieval-Augmented Generation pipelines with vector databases (ChromaDB), LLM APIs (Claude), document ingestion, and semantic search for domain-specific knowledge retrieval.

Research Output

Publications

Peer-reviewed research and published conference abstracts with emphasis on statistical analysis. The Δ symbol indicates I performed the statistical analysis for that publication.

Peer-Reviewed Articles

Delgado, F.Δ, Yu, F., Peterson, D.S., Ofori, E., MacKinnon, D.P., Belden, C., Adler, C.H., Beach, T.G., & Der Ananian, C. (2025). Apolipoprotein E, executive function, and falls across cognitive status: A cross-sectional study. Dementia and Geriatric Disorders. doi:10.1159/000548084

Ofori, E., Delgado, F.Δ, James, D.L., Wilken, J., Hancock, L.M., Doniger, G.M., & Gudesblatt, M. (2024). Impact of distinct cognitive domains on gait variability in individuals with mild cognitive impairment and dementia. Experimental Brain Research. doi:10.1007/s00221-024-06832-9

Vento, K.A., Delgado, F.Δ, & Lynch, H. (2022). Lipid profiles of college female student-athletes participating at different competition levels of organized sport. Frontiers in Sports and Active Living. doi:10.3389/fspor.2022.841096

Vento, K.A., Delgado, F.Δ, Skinner, J., & Wardenaar, F. (2021). Funding and college-provided nutritional resources on diet quality among female athletes. Journal of American College Health. doi:10.1080/07448481.2021.1947301

Delgado, F. & Der Ananian, C. (2021). The use of virtual reality via head-mounted display on balance and gait in older adults: A scoping review. Games for Health Journal, 9(6). doi:10.1089/g4h.2019.0159

Published Refereed Abstracts

Delgado, F.Δ & Greenberg, J.J. (2024). Cognitive and practice effects of immersive virtual reality use in older adults: Preliminary results. Innovation in Aging, 8(S1). Gerontological Society of America Annual Meeting. doi:10.1093/geroni/igae098.3939

Delgado, F.Δ, Yu, F., MacKinnon, D.P., Peterson, D.S., Ofori, E., Adler, C., Beach, T.G., & Der Ananian, C. (2023). Severe Alzheimer's dementia alters the relationship between executive function and falls. Innovation in Aging, 7(S1). Gerontological Society of America Annual Meeting. doi:10.1093/geroni/igad104.3588

Delgado, F.Δ, Kaczmarek, O., Trebing, S., Zarif, M., Gudesblatt, M., & Ofori, E. (2021). Exploratory cross-sectional mediation analysis of the dual-task effect of cognition on gait in individuals with memory loss. Alzheimer's & Dementia, 17(S7). Alzheimer's Association International Conference. doi:10.1002/alz.054495

Delgado, F.Δ, Der Ananian, C., & Peterson, D. (2020). Balance and reactive steps in older adults with and without self-reported musculoskeletal conditions. Innovation in Aging, 4(S1). Gerontological Society of America Annual Meeting. doi:10.1093/geroni/igaa057.1683

Delgado, F.Δ, Der Ananian, C., & Merkel, A. (2019). Changes in physical function and body composition among group lifestyle balance program participants with arthritis. Medicine & Science in Sports & Exercise, 51(6S). American College of Sports Medicine Annual Meeting. doi:10.1249/01.mss.0000561144.22005.d2

+ 4 additional published abstracts and 2 manuscripts currently under review

Academic Background

Education

PhD
Arizona State University
Exercise & Nutritional Sciences
Emphasis in Biomechanics
MS
Texas A&M University–Corpus Christi
Kinesiology
Emphasis in Sport Science
Graduate Certificate
University of New Hampshire
Data Science
BS
State University of New York–College at Brockport
Mathematics

Let's work together

Open to data science, applied statistics, and quantitative research roles. Available for full-time positions and consulting engagements.

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