CV
Education and research experience.
Contact Information
| Name | Nicholas Ho |
| Professional Title | Computational Biology PhD student |
| nzh@cs.cmu.edu |
Experience
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June 2022 - May 2023 Visiting Research Scholar
Harvard Medical School
• Accepted as a visiting research fellow at Harvard DBMI through a highly competitive application process.
• Currently developing a novel machine learning architecture to deal with missing and imbalanced modalities. -
Feb 2020 - May 2023 Research Associate
Struct. Sys. Bio at Biodesign Institute at ASU
Worked as a Research Associate in the Singharoy Lab. Lead research for my honors thesis to utilize deep ML methods with statistical mechanical methodologies.
• Lead and wrote a project on discovering free energy pathways with reinforcement learning
• Developed a molecular differentiable simulator for Jax based on TorchMD
• Helped develop novel conditional generative models for deriving free energy pathways
• Implemented and tested several physics-informed models.
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June 2021 - August 2021 Visiting Research Scholar
Carnegie Mellon University
Accepted as a visiting research fellow in CMU Statistics through a highly competitive summer research program.
• Created and a novel methodology for using stochastic simulators for soccer game predictions. Our method had comparable results to models trained directly on scores. -
May 2020 - May 2021 Assistant Researcher under Ferran Garcia Pichel at Biodesign Institute
Pichel Lab Biodesign Inst.
Developed a Python Plugin for Qiime2 for the relationship between ribosomal gene copy number and size.
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August 2019 - May 2021 Assistant Researcher
Cao Lab Biodesign Inst.
• Conducted data engineering and analysis on genomes assembled from a metagenome in order to study the strain level variance within microbiome communities.
• Implemented a web system that highlighted which genes present in a pathway for particular cyanobacteria species using PFAM’s Hidden Markov Model package, JavaScript, SQL databases, shell and Python. -
June 2020 - July 2020 Software Engineer, Intern
Western Tool & Supply
• Implemented and trained an LSTM Recurrent Neural Network to predict customer purchase likelihoods. • Integrating and using Bluetooth LE between microcontrollers and Google Chrome into their IOT system.
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May 2020 - August 2020 Virtual Helios Scholar
TGEN
Due to covid, the Helios Scholars Program was moved to a virtual format.
Education
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August 2023 - Present PhD Student
Carnegie Mellon University
- Advised by Prof. Jian Ma and Prof. Eric Xing.
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August 2019 - May 2023 B.Sc. Honors Student
Arizona State University
- Double Major in Mathematics (4.0) and Computer Science (4.0)