Resume

John Bradley (JB) Frericks, Ph.D. Candidate

Engineering PhD Candidate | Human-AI Systems, Robotics, and Manufacturing Testbeds

Athens, GA 404-909-4318 [email protected] linkedin.com/in/john-frericks github.com/jbfrericks

Summary of Qualifications

Engineering PhD candidate building human-AI, robotics, VR, and manufacturing research testbeds that connect simulation, physical systems, sensing, and repeatable experimental workflows.
Experienced translating open-ended research questions into working prototypes, data collection procedures, technical documentation, and publication-track results.
Project background spans human-AI interaction, manufacturing automation, autonomous inventory monitoring, RFID-enabled robotics, smart assembly systems, and human-aware manufacturing.

Education

University of Georgia

PhD Candidate, Engineering | Electrical and Computer Systems | Athens, GA

Expected December 2026

Working dissertation title: "From Tools to Teammates: Analyzing the Dynamics of Trust in Human-AI Collaboration"; co-advisors: Dr. Jaime Camelio and Dr. Kyle Johnsen.
Graduate researcher, Manufacturing Living Labs.

University of Georgia

Bachelor of Science, Computer Systems Engineering | Athens, GA

2021

Technical Skills

Robotics & Automation: ROS, Unitree humanoid robots, Unitree quadruped robots, UR cobots, Mobile Industrial Robotics (MiR), Dobot robotics, LiDAR, MoveIt, RViz

Simulation & Virtual Reality: Gazebo, NVIDIA Isaac, Google MuJoCo, Unity, Meta XR

AI, Human-AI Interaction & Multimodal Sensing: LLMs, VLMs, knowledge graphs, RAG, vector databases, STT, TTS, WebGazer.js, EmotiBit, Empatica, Muse EEG, psychophysiological data workflows

Software & Programming: Python, C++, JavaScript, Bash, Git/GitHub, Linux, Windows, macOS, REST APIs, MQTT, SQL, NoSQL, InfluxDB, Grafana, Docker

Additive Manufacturing: CAD, Fusion 360, PrusaSlicer, Bambu Studio, Bambu Suite, Mainsail, FormLabs PreForm

Relevant Project Experience

Autonomous Robotic Entropy-Based Assessment of Factory Floor Organization

January 2026 - Present | Manuscript in preparation | Target: Robotics and Computer-Integrated Manufacturing

Implemented entropy-based factory-floor organization assessment methods on top of an existing Unitree Go2 robotics stack.
Built conversions and entropy calculations for costmaps, zones, point clouds, odometry, velocity/command streams, Jensen-Shannon run comparisons, and normalized AUC over time.
Built the analysis interface and mentored an undergraduate student on the project.
Connected autonomous robot sensing with manufacturing analytics for repeatable assessment of layout organization, disorder, and process friction.

Edge AI Framework for Ambiguous Multi-Robot Manufacturing Tasks

October 2025 - May 2026 | ASME IDETC/CIE 2026 Paper

Contributed to a framework that converts ambiguous worker requests into explainable, executable robot actions for high-mix, low-volume manufacturing.
Paper evaluated 35 ambiguous manufacturing instructions using edge-deployable VLMs, including SmolVLM-500M and Qwen3-VL-2B, against GPT-4o.
Connected task-intention analysis, tool-affordance reasoning, action grounding, robot allocation, and Skill-Code execution across Dobot Magician E6, Unitree G1, and Unitree Go2 platforms.
Supported edge-side deployment goals for manufacturing settings with limited compute budgets, latency constraints, and data compliance concerns.

Psychophysiological Trust Calibration Framework

October 2025 - Present | TETRA-Funded Project | Manuscript in preparation

Developing a real-time trust prediction framework to reduce reliance on post-task surveys.
Built the human-facing interface, backend experimenter controller, physical robot programming, experiment design, and sensor data integration for a Unitree Go2 quadruped robot testbed.
Integrated heart-rate, GSR/EDA, Muse EEG, WebGazer.js eye tracking, video, speech, and survey data using EmotiBit and Empatica devices.
Designed synchronized data collection around human state, robot behavior, task context, and survey measures for real-time trust modeling.

Humanoid Collaboration Framework for Human-Aware Manufacturing

2025 | David Dornfeld Manufacturing Vision Award | Conceptual Framework

Contributed concept development, technical framing, writing, and humanoid behavior concepts.
Framed the system around fatigue, cognitive load, stress, emotion, trust, safety, and workload as human-state inputs for human-aware manufacturing.
Integrated affective computing, sensor fusion, physiological sensing, AI reasoning, robotics, VR, and human-AI collaboration concepts for factory-floor decision support.

VR Human-Robot Search Team Testbed with Embodied Verification

February 2025 - Present | Manuscript in preparation | Target: CHI 2027

Built a Unity VR simulation where participants work with a robot to assign tasks, gather evidence, and identify a target location.
Developed the backend Python WebSocket logging system and AWS bridge so the study can run on internet-connected VR headsets.
Integrated Speech to Text, Text to Speech, eye/gaze tracking, decision logs, timing, robot recommendations, and trust surveys.
Developed embodied verification methods supporting the in-progress manuscript "From Monitoring to Reliance: Embodied Trust Calibration in VR Human-Robot Search Teams."
Designed the study flow around robot recommendations, participant decisions, and reliance behavior in collaborative search tasks.

Autonomous Inventory Management

December 2024 - Present | Undergraduate Capstone Project | Robotics Mentor

Mentored undergraduate capstone students as robotics lead for an autonomous inventory delivery system.
Integrated MiR200 AGV, UR10 arm, LiDAR, dashboard, custom 3D-printed end effector, robot control, and data workflows.
Guided students through robotics architecture decisions, integration tradeoffs, and prototype debugging.

Autonomous RFID-Equipped Robot for Inventory Monitoring

September 2024 - November 2024 | Second Author | Manufacturing Letters

Integrated a SparkFun RFID reader with the Unitree Go2 and created a ROS node for robot-wide RFID sensing.
Owned robot-side movement programming, localization algorithms, sensor integration, and MoveIt/RViz visualizations.
Connected mobile robot sensing, UHF RFID workflows, and flexible inventory mapping for manufacturing operations.

Human-AI Trust Simulation Testbed

August 2022 - October 2024 | DAC-Funded Study | IEEE CogMI 2024 Best Paper

Created the full ROS/Gazebo TurtleBot testbed with PyQt interfaces and repeatable human-robot trust experiments.
Designed participant workflows where users worked with a simulated robot to complete a series of collaborative tasks.
Collected trust, demographic, and human-factors data on how participants monitored, collaborated with, and relied on AI-enabled robots.
Supported the full research pipeline from testbed design and study execution through data analysis, writing, and publication.

Smart Manual Assembly Line Testbed

2021 - Present | Capstone Foundation | Manufacturing Living Labs Testbed

Built the core six-station oscillating multitool assembly line for station-level assembly research.
Added ESP32 devices, cameras, PLCs, load cells, presence sensors, CO2/light sensing, Home Assistant dashboards, and data workflows.
Contributed across hardware, software, data collection, integration, and testbed design toward an open-source manual assembly dataset.
Supported station-level performance, defect, and environmental data collection for line-balancing and Industry 4.0 research.

Relevant Awards & Publications

IEEE CogMI 2024 Best Paper: first author, "Trust and Collaboration Testing in Controlled Human-Robot Environments."
2025 SME David Dornfeld Manufacturing Vision Award: contributor, "Manufacturing Empathy: Sensorial AI for Rewriting Human-AI Collaboration."
Co-authored Manufacturing Letters "SCOUT" paper and ASME IDETC/CIE 2026 "AffordRAG-Factory"; additional manuscripts in preparation on VR embodied verification, entropy-based factory assessment, and psychophysiological trust calibration.