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Apple - AIML

2021–present. Staff Research Scientist.

• Designed and deployed novel machine learning models for large-scale gesture recognition on the Apple Watch (POR) — powering Assistive Touch and Quick Actions—achieving up to 40% latency reduction compared to baseline.
• Played a central role in shaping the gesture vocabulary, informing user study design and guiding feature validation for next-generation interaction paradigms.
• Developed early-stage sensing and ML prototypes that laid the groundwork for new accessibility and health monitoring features, aligning technical innovation with inclusive design principles.
• Led the human red teaming initiative for generative AI safety in Apple Intelligence, ensuring that large-scale language and multimodal systems adhere to principles of trust and safety.

Chatham Labs > Facebook Reality Labs/Meta

2019–2020. Senior Research Scientist.

• Developed dynamic models of hand, head, and gaze behavior to advance predictive and immersive VR interaction paradigms.
• Designed and implemented a learning-based regression algorithm for real-time endpoint prediction, enhancing precision and responsiveness in virtual environments.
• Engineered real-time gap-filling techniques for gaze tracking, ensuring continuity and reliability in eye-based interaction flows.
• Created robust pipelines for artifact detection and noise filtering across controller and headset signals, improving signal integrity for consistent user experience.

Google (Project Soli)

2016–2019. Research Scientist.

• Developed algorithms to extract meaningful signals of interest from high-dimensional spatiotemporal radar data, enabling precise interpretation of complex, real-world input streams.
• Engineered features for machine learning algorithms, enhancing both embedded efficiency and predictive accuracy.
• Designed end-to-end pipelines for filtering, prediction, estimation, and tracking of signals derived from human motion.
• Modeled gesture and interaction dynamics to support adaptive filtering and state estimation, improving real-time system responsiveness and contextual awareness.

Education

Safra International Institute of Neurosciences

2015-2015. Postdoctoral fellowship in Data Analysis & Neuroscience

• Developed an image-based tracking algorithm for rodent behavior analysis, enabling high-resolution, automated observation in behavioral neuroscience research.
• Designed advanced preprocessing pipelines to support the analysis and classification of neural coding patterns, laying the groundwork for more interpretable and scalable neural data analytics.

McGill University & MIT

2010–2014. PhD in Music Technology and Integrated Sensor Systems.

• Developed advanced sensor fusion algorithms for analyzing baseball pitching performance using wearable sensing technologies, enabling objective assessment of skilled motor control.
• Created a novel Kalman filtering framework tailored to human-generated sensor data, optimizing real-time estimation in dynamic and non-linear movement contexts.
• Designed and led user studies with skilled motor performers—including athletes (Boston Red Sox), musicians, and dancers—to investigate the interplay between motion, cognition, and sensor-based signals.
• Broader research scope includes foundational work in sensing systems, motion analysis, and algorithmic design to support human-centered performance technologies.

Santa Catarina Federal University

2006–2008. Master in Mechanical Engineer. Engineered a wireless temperature sensing system for knee prostheses leveraging Surface Acoustic Wave (SAW) technology, pioneering a non-invasive approach to continuous, implantable thermal monitoring and advancing the future of smart orthopedic implants.

2000–2005. Bachelor of Electrical Engineering. Focus on Electronics and Control Engineering.

Federal Technical High School in Pelotas

1994–1998. Technical high/trade school in Electronics.

Selected Publications

• Gunter, T. et al. Apple Intelligence Foundation Language Models. ArXiv. arXiv:2407.21075, 2024.
• Xu, Xuhai, Gong, J., Medeiros, C.B., Liang, L., Suh, B., Gupta, S.K., Agarwal, Y., Lindsey, L., Kang, R., Shahsavari, B., Nguyen, T., Nieto, H., Hudson, S.E., Maalouf, C., Mousavi, J.S., Laput, G.. Enabling Hand Gesture Customization on Wrist-Worn Devices. CHI Conference on Human Factors in Computing Systems, 2021.
• Cheng, T., Park, J.W., Li, J., Ramey, C., Lin, H., Abowd, G.D, Medeiros, C.B., Oh, H., Giordano, M..PITAS: Sensing and Actuating Embedded Robotic Sheet for Physical Information Communication. CHI Conference on Human Factors in Computing Systems, 2021.
• Lapinki, M., Medeiros, C.B., Berkson, E., Kepple, T., Scarborough, D., Paradiso, J. A Wide-Range, Wireless Wearable Inertial Motion Sensing System for Capturing Fast Athletic Biomechanics in Overhead Pitching. Sensors Journal 2019, 19(17), 3637.
• Figueiredo, N., Felix, F., Medeiros, C.B, Queiroz, M. A comparative study on filtering and classification of bird songs. In: Proceedings of the 15th Sound and Music Computing Conference (SMC 2018), pp. 365-372, 2018.
• Medeiros, C.B. and Wanderley, M.W. Comprehensive Review of Sensors and Instrumentation Methods Used in Musical Expression. Sensors. 2014, 14(8), 13556-13591; DOI:10.3390/s140813556
• Medeiros, C.B. and Wanderley, M.W. Multiple-model Linear Kalman Filter Framework for Unpredictable Signals. IEEE Sensors Journal. 2014, 14(4), 979-991, DOI 10.1109/ JSEN.2013.2291683.

Languages

• English, French, Portuguese and Spanish: full professional proficiency
• Programming languages: C, C++, Julia, Matlab, R, Mathematica, Python, obj-C