learn-to-code | episodes

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Learn to Code

Our guests today are Melia Gehan and John Wilmes. But first, our co-host Becky began the show. She discussed her journey from learning HTML and CSS to learning Python and R. She also shared applications of these languages for people in academia.

Becky shared some challenges with the current style of coding classes. She also discussed how students can debug codes with ChatGPT and other LLMs. Wrapping up, she advised beginners on how to get started on their coding journey.

Melia is a member and principal investigator at the Donald Danforth Plant Science Center. She and her team work on improving crop resilience to climate change. She discussed how programming is used in this field. She also shared the Python packages useful for computer vision in crop cultivation. She introduced PlantCV and why it is unique. She shared how LLMs are applied in the field of plant science.

Our second guest, John, is a Machine Learning Researcher at Symbolica AI. John shared his journey to coding. He talked about the Lean programming language and its uniqueness as a language of proof. He also mentioned the challenge with Lean and some state-of-the-art tools, such as LeanDojo, that apply LLMs for theorem proving. Rounding up, he shared advice for people who want to get started with software engineering.

Learn more about our guests


Becky Hansis-O'Neill

Becky is a PhD student in the biology department at University of Missouri - St. Louis (UMSL). She received her BS in Psychology and MS in Biological Sciences from Idaho State University (ISU). She has conducted research on topics such as behavioral pharmacology, developmental neurobiology, pollinator ecology, parasite-host interactions, population ecology, and stable isotope analysis. During her time at ISU, Becky discovered a passion for science communication while teaching undergraduate labs in general biology, ecology, and human anatomy and physiology. After her MS, she worked as the Education Specialist for the Idaho Museum of Natural History (IMNH), managing educational programs and designing and implementing digital interactive components for public exhibits. Because of this, Becky moved on to work at an exhibit design firm, Ideum. She led full exhibit design-build projects that integrated interactive multimedia, custom software development, and both print and digital content creation while managing the Creative Services department. Currently, she is a doctoral candidate at UMSL studying learning and behavior in tarantulas and bumblebees. Becky hopes to continue her career as a researcher when she is finished. In her spare-time she enjoys nature photography, dog training, gardening, and creating digital art.

Malia Gehan

Malia Gehan did her Ph.D. research examining the intersection of cold signaling and the circadian at Michigan State University. She was a NSF Plant Genome Postdoctoral Fellow and is now an Associate Member and Principal Investigator at the Donald Danforth Plant Science Center, whose group focuses understanding mechanisms of crop resilience under temperature stress. To study temperature stress and natural variation, the Gehan lab develops high-throughput and high-resolution image-based phenotyping technologies, including low-cost solutions that use Raspberry Pi computers. The Gehan Lab co-develops and maintain the open-source open- development suite of image analysis tools, PlantCV (https://plantcv.danforthcenter.org/), along with Dr. Noah Fahlgren’s group. In 2021, she received an early career award from the North American Plant Phenotyping Network and she is currently a Taylor Geospatial Fellow, which is awarded to distinguished researchers in geospatial science or adjacent fields.

John Wilmes

I am a machine learning and algorithms researcher with over a decade of experience. My academic work includes first-in-class training guarantees for several neural network architectures and results published in top computer science venues such as Neurips, COLT, FOCS, and STOC. I currently lead the Research Engineering team at Symbolica.

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