I am a clinical research neuroscientist in the Department of Neurology and Neurological Sciences at Stanford Hospital. I completed my training at The University of Kansas Hospital in Kansas City, and graduated from the physician scientist training program at The University of Miami - Miller School of Medicine where I conducted research in imaging surrogate markers of neurovascular disease and public health epidemiology. Miami and Kansas City are also where I developed a passion for global health, and were my home when traveling to formative experiences in disaster response and health management in austere conditions. After completing my doctoral research training I spent time at the NIH/NINDS Intramural Studies program to develop physiologic and neuroimaging markers of psychoactive exposure (e.g. MDMA, THC, JWH018/073), including clinical trials as they related to subject report of the emotional or hallucinatory influence of those drugs. I became interested in epilepsy as a clinical method for defining the interface of human consciousness and behavior, especially as consciousness is modified by pharmacology (e.g. anticonvulsants), structural change (e.g. surgical excision), electrical interference (e.g. brain/machine interface), and emotional control (e.g. stress vs. mindfulness). The core of my intellectual passion is functional interface with the brain, especially sensation and perception, towards multi-modal network regulation to include feedback with bidirectional information transfer among users. My first publication was a novel microelectrode for increasing bio-compatibility in a deep somatosensory implant, and the purpose of my medical training is to identify populations where reimbursable treatment procedures and diagnostic methods can power next generation developments within the scope of clinical practice. The existing tools of Vagal Nerve Stimulation (VNS), Deep Brain Stimulation (DBS) and Responsive NeuroStimulation (NeuroPace) are just a few of those procedures, with advancements from the DARPA human interface initiative becoming closer every day. Breakthroughs in data analytics and machine learning are as necessary as device design to bring neural interface technology to into common use, and to the forum of noninvasive consumer-grade methods with reduced risk compared to those that presently require a surgeon or neurologist to play gatekeeper. The trajectory of these efforts is not only more effective neuromodulatory treatments for epilepsy and other neurocognitive pathology, but also the application potential for neurofeedback in the awake and conscious adult (e.g. gauges of attention, memory, emotion), transmission of information between users, and performance enhancement. In addition to the individual benefit for patients and perhaps an improved general understanding of human consciousness, capture of neurologic markers on a population scale will allow us to identify emergent properties in cognitive networks, especially as they relate to behavior, early diagnosis, and treatment optimization. Co-development with creative technological minds is necessary to share platforms that will deliver meaningful use outside of the research environment. I am a participating investigator in several clinical trials, including mobile application and artificially intelligent machine learning for predicting medication effectiveness, and non-invasive neuromodulation for human cognitive performance enhancement (rTMS). I am always willing to connect the willing with an opportunity to help, feel free to contact me if you have a sense our interests would align - send me a message with your idea, or your ability to support research or technology advancement projects in these areas.