As a dynamic and growth-oriented Data Scientist, I have extensive experience in data analytics, research and development, and engineering, with a particular focus on cognitive science and psychophysiology. Throughout my career, I have consistently demonstrated a goal-directed approach, leveraging advanced statistical techniques, machine learning algorithms, and data visualization tools to extract meaningful insights from complex datasets.
Being a forward-thinking professional, I led and managed end-to-end cognitive science experiments, from participant recruitment to the execution of data acquisition processes, ensuring the integrity and efficiency of research initiatives. My expertise extends to conducting advanced generative modeling and sophisticated graph theoretical analyses, providing unparalleled insights into dynamic fluctuations within large-scale networks. I am known for my ability to streamline data processing workflows through the implementation of automated pipelines in MATLAB and Python, resulting in a significant increase in team productivity. As a compassionate and motivational team member, I coordinate with multidisciplinary teams, including neuroscientists, clinicians, and engineers, to synthesize findings and integrate perspectives. Additionally, I have facilitated multimodal neuroimaging studies by creating efficient experimental protocols for the simultaneous use of electroencephalography and transcranial electrical stimulation, navigating complex regulatory processes while always adhering to ethical practices. Effective communication and collaboration are at the core of my approach, allowing me to work seamlessly with colleagues from diverse backgrounds. My problem-solving abilities have been instrumental in overcoming complex challenges, and my commitment to data ethics and privacy ensures that research initiatives are conducted responsibly and with the utmost integrity. Some of my skills are listed below: Data Visualization \| Statistical Data Analysis \| Experimental Design & Research \| Computational Modeling \| Machine Learning & AI \| Forecasting & Benchmarking

Kyle Curham

Data Scientist | Cognitive Scientist | Engineer | Transforming Complex Data into Profound Insights for Data-Driven Decision-Making

Orange City, Florida, United States of America

Research Expertise

Data Science

Computational Cognitive Neuroscience

About

As a dynamic and growth-oriented Data Scientist, I have extensive experience in data analytics, research and development, and engineering, with a particular focus on cognitive science and psychophysiology. Throughout my career, I have consistently demonstrated a goal-directed approach, leveraging advanced statistical techniques, machine learning algorithms, and data visualization tools to extract meaningful insights from complex datasets. <br> Being a forward-thinking professional, I led and managed end-to-end cognitive science experiments, from participant recruitment to the execution of data acquisition processes, ensuring the integrity and efficiency of research initiatives. My expertise extends to conducting advanced generative modeling and sophisticated graph theoretical analyses, providing unparalleled insights into dynamic fluctuations within large-scale networks. I am known for my ability to streamline data processing workflows through the implementation of automated pipelines in MATLAB and Python, resulting in a significant increase in team productivity. As a compassionate and motivational team member, I coordinate with multidisciplinary teams, including neuroscientists, clinicians, and engineers, to synthesize findings and integrate perspectives. Additionally, I have facilitated multimodal neuroimaging studies by creating efficient experimental protocols for the simultaneous use of electroencephalography and transcranial electrical stimulation, navigating complex regulatory processes while always adhering to ethical practices. Effective communication and collaboration are at the core of my approach, allowing me to work seamlessly with colleagues from diverse backgrounds. My problem-solving abilities have been instrumental in overcoming complex challenges, and my commitment to data ethics and privacy ensures that research initiatives are conducted responsibly and with the utmost integrity. Some of my skills are listed below: Data Visualization \| Statistical Data Analysis \| Experimental Design & Research \| Computational Modeling \| Machine Learning & AI \| Forecasting & Benchmarking

Legacy Map

Full View

Publications

Logic Behind EEG Frequency Analysis

The Oxford Handbook of EEG Frequency

2022

Wrist-mounted smartphone-based navigation device for visually impaired people using ultrasonic sensing

2016 Fifth ICT International Student Project Conference (ICT-ISPC)

2016

Difference in Quality of Life during the Bone Healing Process in Patients with Upper or Lower Extremity Problems

Annual Global Healthcare Conference

2012

Brain activity diagnostics system for exoskeleton control

2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)

2022

Repetitive Transcranial Magnetic Stimulation (rTMS): A Large-Scale Retrospective Clinical Data Analysis Indicating rTMS as Effective Treatment for Generalized Anxiety Disorder (GAD)

Brain Stimulation

2020

Abstract #116: Simulations of temporal interference tCS in a realistic head model

Brain Stimulation

2019

On the Permanence Property in Spherical Spline Interpolation,

Unknown Venue

1982

Brain Waves Meet Real Life: Recent Advances in Mobile EEG

Psychophysiology

2018

Time‐Frequency, Source, and Connectivity Approaches to Study Dynamic Relations Between Monitoring, Control and Anxiety Across Development

Psychophysiology

2017

Multivariate Time-Series Brain Connectivity: A Sum-Up

Methods in Brain Connectivity Inference through Multivariate Time Series Analysis

2016

Midline Frontal ERPS and Theta Phase Alignment

Psychophysiology

2015

The Agony and the Ecstasy: Leveraging Physiological Indices of Reward and Threat Sensitivity to Improve Measurement of Clinical Phenomena

Psychophysiology

2014

Design of a quasi-passive knee exoskeleton to assist running

2008 IEEE/RSJ International Conference on Intelligent Robots and Systems

2008

Education

University of Arizona

Ph.D., Cognitive Neuroscience / January, 2022

Tucson, Arizona, United States of America

University of Arizona

M.A., Psychology / May, 2017

Tucson, Arizona, United States of America

Western Governors University

M.S., Data Analytics / November, 2023

Salt Lake City, Utah, United States of America

University of South Florida

B.S., Mechanical Engineering / May, 2012

Tampa, Florida, United States of America

University of South Florida

B.A., Psychology / May, 2013

Tampa, Florida, United States of America

Experience

University of Arizona

Consulting Data Scientist / November, 2022 — November, 2023

Identify and elucidate effects of transcranial magnetic stimulation on resting-state electrophysiology to maximize understanding of neural responses and open avenues for exploring new applications of neurostimulation techniques in clinical / research settings. Perform advanced statistical analysis on collected resting-state electrophysiological data by employing techniques such as time-frequency analysis and connectivity measures.

Principal Investigator / August, 2019 — May, 2021

Facilitated multimodal neuroimaging studies by creating efficient experimental protocols for simultaneous use of electroencephalography and transcranial electrical stimulation.

Graduate Assistant / August, 2017 — January, 2022

Devised specialized software and hardware solutions to meet stringent regulatory and business requirements, positioning organization at forefront of technological innovation in meeting industry standards.

Teaching Assistant / August, 2014 — January, 2022

Guided students in practical application of quantitative techniques through courses in Measurement and Statistics, Research Methods, and Neuroeconomics. Delivered courses on Drugs, Brain, and Developmental Psychology to render holistic perspectives on complex interactions between brain function, substance use, and human development.

University of South Florida

Research Assistant / August, 2012 — May, 2024

Maximized integrity of the experimental process by strategically overseeing cognitive science experiments, from participant recruitment to acquisition of electrophysiological signals.

Research Assistant / August, 2011 — May, 2012

Conducted in-depth analysis to assess prosthetic dynamics and kinematics across diverse environmental conditions to assure functional adaptation and optimal performance of prosthetic solutions.

Volusia County Schools

Teacher / August, 2023 — Present

Teaching - Probability and Statistics

DataAnnotation.tech

AI Researcher / November, 2023 — Present

Provide High-fidelity training data for AI training and development; critique AI models for A/B testing.

Links & Social Media

Research Web Site

Link

Join Kyle on NotedSource!

Join Now

At NotedSource, we believe that professors, post-docs, scientists and other researchers have deep, untapped knowledge and expertise that can be leveraged to drive innovation within companies. NotedSource is committed to bridging the gap between academia and industry by providing a platform for collaboration with industry and networking with other researchers.

For industry, NotedSource identifies the right academic experts in 24 hours to help organizations build and grow. With a platform of thousands of knowledgeable PhDs, scientists, and industry experts, NotedSource makes connecting and collaborating easy.

For academic researchers such as professors, post-docs, and Ph.D.s, NotedSource provides tools to discover and connect to your colleagues with messaging and news feeds, in addition to the opportunity to be paid for your collaboration with vetted partners.