Computer Scientist, Software Developer, Data Scientist, Researcher, Entrepreneur
Pivoting from Machine Learning Engineering to Biotechnologist
I'm Morgan, and welcome to my personal website. I am an engineer, scientist, mathematician, teacher, entrepreneur, and bold thinker.
For ten years, I've been a software engineer specialized in machine learning engineering and research (model developmet, algorithm analysis, research engineering, data wrangling). I was motivated by developing innovative technology, researching how brains work and how neural network models mathematically achieve their results, and I enjoyed the work. My research centered on attentional ANN dynamics, and industry work centered stack programming, data management, and integrations.
Due to an alignment of my skills and values, now I apply my computational skills to problems in biotechnology, life sciences, and microbe research. Since Q1 of 2025, I've been in the process of developing industrial and medical cell biology fluency. I am currently retooling and building wetlab skills by pursuing an Associate's degree in Biotechnology. My side projects are bioinformatics projects, and I've started a new consultancy for bioinformatics. As I experiment to figure out my subspecialty, I'm very open to contributing as an entry-level research assistant or intern roles in academia and industry. I am currently looking for opportunities in drylab settings as a bioinformaticist, computational biologist, data engineer, and support software developer.
Microbe engineering is the future. Microbes provide unique and irreplacable solutions to problems in renewable power, drug development and production, food, agriculture, immunology, chemical goods production and materials manufacturing, sustainable resource extraction, remediation, valorization, and profit that outpaces the diversity of networked sectors. To develop microbe-based technology towards competitive advantages in the market, I aim to serve as the computer scientist, machine learning specialist, and data engineer who can solve complex problems in parsing genomic data (especially metagenomics), and to develop the tools needed for industrial optimization. In the future, I aim to contribute to basic biology research and industry startups.
I am a skilled software developer, with specific expertise in front-end development, data science and data analysis, neural network engineering, and scientific research. My main toolbox includes unix, python, js/ts stacks, functional programming, research methodology, mathematical thinking, algorithm analysis and development, and digesting advanced literature. I am often told I have a strong ability to understand complex problems and systems.
I have a consistent entrepreneurial spirit, and I am always open to talk about new business ideas.
I thrive in fast-paced startup work environments where we have to adapt quickly according to business needs. I am scrappy and resourceful. I excel at prioritizing the team's collective goals.
I've done industry work at mid-stage tech startups, angel-stage startups, and fintech and edtech organizations, as both an employee and freelance contractor. My strengths include problem-solving, understanding complex systems deeply, finding unexpectedly useful tools, and goal-directed development with a team.
I do technical work in AI development, data science, front-end engineering, and research.
I have side interests in high-dimensional statistics, applied mathematics, neural network theory, cognitive science, biochemistry, and financial analysis & strategy. I've supported the connectionist hypothesis since 2016. These interests began while I was studying at Stanford and continued through lab membership with the PDP Lab, where I led our attention network focus group starting in 2018.
I have been a mathematical AI model developer & research engineer from 2015 to the heydey of 2023 when the first LLMs reached the general public. I understand in intricate detail what it takes to develop small/medium-scale AI models and both the capabilities, challenges, and shortcomings inherent to transformer-based artificial neural networks. I am adept at using modern AI tools, performing integrations, prompt engineering, and working with AI-integrated software systems.
From as early as 2017, I have had concerns about AI: not about the technology itself but about the manner in which it was being developed and its most likely future applications. Since then, I've observed and become keenly aware of both the benefits and the consequences of excessive AI integration. I acknowledge how it affects a staggering number of aisles, including: new business capabilities and markets, workforce stability, research advancements, environmental responsibility, global considerations, daily joy, technology bubble consequences, responsibility against financial crisis, civil bias, perpetration and detection of fraud, public mystique around advanced technology, liability and explainability, education quality and access, cost-saving automation of routine administrative tasks, and digital mental health of everyday people.
I support the responsible use of AI tools in work environments, especially in assisting to automate rote tasks and in research, and I support the responsible development of new AI technologies. I am wary of overuse of AI, from both a social and economic standpoint. I am more interested in adapting to a changing digital landscape than in heated debates and moral stances. I am not passionately interested in developing new AI technology advancements in my own work, nor in collaborating deeply with those who, according to their material capacity for criticism, are unwilling to acknowledge the real problems that AI is causing, for reasons mostly unrelated to the technology itself.
These stances are approximate and absolutely warrant to change at any time, especially as new information comes to light and the industry/technology's future directions unfold.
Past B.S. Computer Science from Stanford with work in the Stanford Symbolic Systems Program Research Master's under Jay McClelland. In progress: A.S. Biotechnology, Berkeley City College
Nontechnical work includes advocacy & outreach, social work, manual labor, front-of-house, warehousing, meeting facilitator, community space manager, event coordinator, DJ, graphic designer, and teaching and tutoring.
Outside of work, I focus my resources on community engagement, social good, and intersectional justice (especially intersectional LGBT advocacy, racial and socioeconomic justice, and mental health transparency). In my free time, I enjoy art (especially guitar) and doing independent research in theoretical/computational cognitive neuroscience, immunology, bioinformatics, and statistics.
I am genderfluid and it is inappropriate to refer to me using gendered terms. Don't call me he/him/she/her; use they/them instead. Terms such as Mister, actress, dude, bro, Ma'am, chick, etc. are also inappropriate. If I do not correct you, that does not constitute permission or consent to continue using the wrong terms for me. For information about identity terms: transstudent.org/about/definitions/. To learn more and answer questions you might have, I highly recommend browsing YouTube.
To reiterate, I use they/them pronouns.
What's Tao Ke Tao? The Taoist seminal text, the Tao Te Ching by Lao Tzu, begins with the line 道可道非常道 , or in Mandarin pinyin, tào kè tào fēi cháng tào. One translation is, “The Way (Tao) that can be named is not the true Way”; there are also many other reasonable translations. The philosophy of the Tao Te Ching and especially its first chapter highlights my values of mindfulness, critical thinking, and staying adaptible for reaching goals. Plus, somehow 'morganbryant' was a taken username.
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Site current up to May 2026. Material on this domain uses the GNU Affero General Public License.