Who I am: Patrick
As a firm, the team at KdT has decided to publish long-form biographies to help the folks we work with learn more about who we are as people. Our hope is that the openness and vulnerability that comes from sharing our stories will help enable dialogues with all our partners, most importantly, current and future KdT founders. Cain, Mack, Phil, Rima, and Ally have previously published their stories. What follows is Patrick’s. Here goes nothing…
My story, like many others, is one of trying to fit in and find my place in the world. Growing up in Akron, Ohio, I was a shy and quiet kid. I was fortunate - I was born into a happy home where my parents provided me with all the tools for a happy childhood. Despite this fortune, I often felt out of place and misunderstood. I had a small group of close friends, but I never felt cool enough to sit wherever I wanted at lunch and I often felt excluded in ways that, at the time, I couldn’t understand. In retrospect, perhaps I shouldn’t have been surprised: I devoted my younger years to swimming and tinkering with computers. While worthwhile endeavors, neither provided me with a sense of belonging or connection with my peers. Everyday after swim practice, I’d come home and spend hours getting lost in whatever computer project I was into at the time, like programming generative art in Python or building/fixing gaming PCs. These pursuits helped shape the person I am today. Whatever drove me to wake up at 5 am to jump into a cold pool still drives my relentless work ethic and my early fascination with computers motivated the rest of my education and career. Most importantly, as someone who often felt isolated from his peers and used these solitary activities as a crutch, I developed an empathy for “outsiders” that I try to remind myself of everyday.
While isolating at times, I was thankfully rewarded for my time in the pool as Emory University recruited me to join the swim team. In the classroom, I gravitated towards neuroscience and computer science. I started reading books on artificial intelligence (such as On Intelligence and Singularity is Near) and was immediately captivated by the question of modeling a human brain on a computer. How could it be that the human brain surpasses the intelligence of a supercomputer, all while running on the power of less than a lightbulb? These unanswered questions guided my studies in neuroscience and computer science, and I soon found my way into a neuroengineering lab. Most scientists can trace their scientific awakening back to one moment in time, one unforgettable experience that inevitably hooks them. For me, it was the awe of my first electrophysiology experiment - the wonder of hearing the “spikes” of neurons under an electrode, and the reward of writing code to discover something new about how the brain works. The iterative process of designing and running experiments in the lab, analyzing the data using computational methods, and then heading back to the lab for follow-up experiments based on what we discovered, was intoxicating. I decided to pursue a career in science, and completed an undergraduate research thesis focused on developing a neurophysiological model for plasticity after spinal cord injury.
My excitement for computational neuroscience pulled me next to Mark Hallet’s Human Motor Control lab at the NIH, an interdisciplinary group of physician-scientists and engineers that used neuro-imaging and computational tools to study neurological disease. I helped develop biomarkers for movement disorders such as Parkinson’s disease using multimodal neuroimaging techniques, and adapted computational methods based on graph theory for functional MRI analysis. Through these technical projects, I understood that the future of healthcare would lie at the intersection of computational disciplines and medicine. However, few understood both of these worlds: Engineers developed computational tools without an understanding of their clinical utility, while the clinicians who used these tools often didn’t understand their inner-workings and limitations. Given my interest in both computers and medicine, I found it frustrating that much of the potential for machine learning in healthcare was being squandered because of the disconnect between these worlds.
To help bridge this gap, I decided to pursue an MD and a computationally-oriented PhD at Georgetown, a short move down the street from NIH. I was excited to stay in DC; striking the right balance between a fast-paced city with lots to do (such as an awesome live music scene), with plenty of outdoor space (like Rock Creek Park) to get away from the noise of daily life, it was the right city for me. These were some of the best years of my life, both personally and intellectually. I met the love of my life (now my wife) and we made DC our long-term home. In graduate school, I pursued my PhD in Max Riesenhuber’s Lab for Computational Cognitive Neuroscience. While it appeared to be an usual choice of a thesis lab for a clinical student, to me it felt like home. Conversations in lab meetings often fell down rabbit holes, like, to what degree deep learning algorithms approximate computation in the human brain, or debates about the neuroscience of free will. These weren’t the most relevant topics for a medical student, but training in Max’s lab was a deliberate part of my plan to acquire the technical skills necessary to become a physician/data-scientist. Throughout my PhD, the curiosity and intellectual energy in the lab was infectious. We worked on mind-bending projects like teaching individuals to understand speech through touch using a sensory-substitution device (a collaboration with Facebook Reality Labs), or disentangling the semantic representation of written words in the brain using machine learning and fMRI. Through these projects, I picked up more of the technical skills required to advance computational tools in healthcare.
After completing my PhD, I returned to my final years of medical school with the plan of pursuing residency. Then, as is often the case in life, serendipity intervened. By chance, I discovered a fellowship opportunity at an upstart venture capital firm called Northpond Ventures. Despite not having a business or finance background, I was intrigued by the opportunity to learn more about early-stage startup investing, and decided to give it a try. The transition was intimidating, no doubt. To spend many years training in one field, and then to pivot to another, mostly foreign field requiring a new set of skills was terrifying. While difficult and overwhelming at first, I quickly realized that venture was the perfect career for me. The ability to translate impactful, computationally-driven science out of the lab and into the real world through the vehicle of entrepreneurship was incredible to me. In academic science, incremental advances are rewarded, and crazy, far-out ideas are often disincentivized. In startups and venture capital, I found the opposite. It is a privilege to partner with visionary scientists and entrepreneurs who are willing to take massive risks to positively impact the world, and help them build their technologies into successful companies. After graduating medical school, I joined Northpond full-time, and helped build an investment focus at the intersection of technology and healthcare.
I met the KdT squad shortly after pivoting to venture, and experienced first-hand their reputation as the kindest, most passionate and intellectually rigorous investors around. I loved the team, strongly identified with their investment thesis at the intersection of compute, biology, and chemistry, and deeply respected the portfolio and founders that are part of the KdT family. When an opportunity arose to join, I couldn’t pass it up.
For a shy and quiet kid from Akron, KdT felt like a place where everyone can be themselves. KdT is a place without judgment or pretension, a place for the misfit scientists and overlooked founders. To me, a place where there are no “outsiders.” The best thing about KdT is that it doesn’t matter who you are. All that matters is being a good human, and sharing a drive for using science and technology to positively impact the world.