Led client-focused projects, providing data science consulting and R&D expertise to advance neurotech and healthtech solutions.• Conducted market research and feasibility assessments for a wristband wearable device, delivering strategic recommendations and an R&D roadmap.• Worked with interdisciplinary teams to develop new product prototypes, from concept design to algorithm development and technology validation. • Conducted exploratory data analysis to inform neurotechnology design and extract actionable medical insights.• Effectively managed multiple client projects using Agile methodologies, consistently exceeding expectations.• Drove new client acquisition through relationship building, needs identification, & redefining marketing strategies.• Stayed current with the latest advancements in the rapidly evolving neurotech and digital health landscape.

Led the R&D of multimodal EEG earbuds and an integrated analytics platform to advance the brain healthcare continuum.• Guided business strategy and product requirements using data insights from literature reviews, market research, customer interviews, and competitive analysis.• Directed the development of a research platform including a wearable device, companion app, and web dashboard for rapid biomarker insights from remote data.• Ensured successful execution of sponsored clinical studies by overseeing study design, data management, statistical analysis, report generation, and partner relationships.• Validated EEG earbuds against gold-standard clinical data (PSG, scalp and stereo-EEG) for sleep and epilepsy.• Developed machine learning algorithms for automatic sleep staging and seizure detection using ear-EEG.• Created analytics tools with Python frameworks (e.g., Numpy, Pandas, PyTorch, MNE, Jupyter), ensuring reusable and well-documented code.• Played a key role in regulatory activities, including identifying 510(k) pathways, establishing a QMS, designing V&V tests to demonstrate the safety and effectiveness of EEG earbuds and automatic event detection.• Led the submission and presentation of conference abstracts and scientific papers on sleep and epilepsy.• Contributed to business growth through fundraising, team scaling, and organizational process implementation.

Led research to validate multimodal biosensing earbud technology for Brain-Computer Interface (BCI) and health applications.• Designed and executed studies on various prototypes, including experimental design, data collection, and analysis, using insights to drive iterative hardware design improvements.• Implemented signal processing and machine learning algorithms to extract actionable insights from physiological time-series (e.g., EEG, EMG, EOG).• Developed automated reports for data integrity, signal quality, and biomarkers to ensure robust and accurate insights from wearable EEG earbuds.• Contributed to securing seed funding, spinning out the technology from X, and launching NextSense.

Awarded the inaugural postdoctoral fellowship from the Halıcıoğlu Data Science Institute — aimed at preparing outstanding researchers for leadership careers in data science.• Explored novel brain decoding algorithms (EEG 1/f power spectrum slope and waveform shape) and stimulation strategies to enhance cognitive functions.PI: Brad Voytek

Contributed to a large European consortium focused on developing a Brain-Machine Interface to restore speech• Developed neuronal spike detection algorithms for EU's first patients implanted with Utah microelectrode arrays• Created end-to-end pipeline and reusable tools for analyzing multimodal ECoG LFP and neuronal spiking data• Invited to speak at conferences and panels to address challenges and opportunities in decoding brain signals• Co-authored four peer-reviewed journal articles, incl. in Nature CommunicationPI: Anne-Lise Giraud

Led original research on decoding inner speech from neural data, significantly advancing speech-assistive neurotechnologies.• Managed all phases of human research, incl. study design, protocol implementation, data collection and analysis• Implemented signal processing and machine learning algorithms to decode EEG, ECoG, and DBS time-series• Co-authored 9 journal articles, accumulating 800+ citations, and featured in Science, SciAm, and New Scientist• Received 7 grants & awards, incl. 2nd place in the Brain-Computer Interface Award among 100+ submissions• Teaching Assistant for Data Analysis and Model Classification, Fundamentals of Neuroengineering, and BCI• Completed CTI Innosuisse Startup Training, learning entrepreneurship, lean business, and startup managementPIs: José del R. Millán and Robert T. Knight