Landon Holcomb

(he/him)

PhD Student in Computer Science | Quantum Computing Researcher

Professional Summary

About Me

I’m a PhD student in Computer Science at Clemson University, where I focus on quantum machine learning, variational quantum algorithms, and Quantum Natural Language Processing. My research explores the intersection of quantum computing, machine learning, and algorithm design. I am particularly interested in what QML can reveal about the nature of learning and representation itself, how quantum structure may expose patterns or principles that are hidden to classical models.

Before transitioning to computer science, I completed an MS in Physics at Clemson. I’m passionate about bridging theory and application, and making quantum computing more accessible through teaching and science communication.

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Education

PhD in Computer Science (Ongoing)

Clemson University

MS in Physics

Clemson University

BS in Physics

Texas A&M University

Interests

Quantum Machine Learning (QML) Quantum Natural Language Processing (QNLP) Variational Quantum Circuits & Trainability Quantum Algorithms & Simulation Applications of Quantum Computing

Research Focus

My research sits at the intersection of quantum computing, machine learning, and algorithm design. I work on:

Quantum Machine Learning (QML): Developing and analyzing variational quantum algorithms for machine learning tasks
Quantum Natural Language Processing (QNLP): Exploring novel methods to enhance NLP or improve QNLP
Trainability & Optimization: Understanding and mitigating barren plateaus in variational quantum circuits
Quantum Applications in Physics: Exploring how quantum algorithms can advance computational physics

I’m passionate about bridging theory and application, and I’m always open to collaboration on quantum computing research.

Current Research Publications

Earlier Work

Collaborative research on the Exoplanet Transmission Spectroscopy Imager (ETSI) for characterizing exoplanet atmospheres.

Ryan Oelkers, Luke Schmidt, Erika Cook, Mary Limbach, D. DePoy, J. Marshall, Jimmy Ardoin, Mitchell Barry, Evan Batteas, Alexandra Boone, Brant Conway, Silvana Adrande, John Dixon, Enrique Gonzalez-Vega, Alexandra Guajardo, Landon Holcomb, Christian Lambert, Shravan Menon, Divya Mishra, Kaitlin Webber (2025). Ground-based Reconnaissance Observations of 21 Exoplanet Atmospheres with the Exoplanet Transmission Spectroscopy Imager. The Astronomical Journal.

DOI

Ryan Oelkers, Luke Schmidt, Erika Cook, Mary Limbach, D. DePoy, J. Marshall, Jimmy Ardoin, Mitchell Barry, Evan Batteas, Alexandra Boone, Brant Conway, Silvana Adrande, John Dixon, Enrique Gonzalez-Vega, Alexandra Guajardo, Landon Holcomb, Christian Lambert, Shravan Menon, Divya Mishra, Kaitlin Webber (2025). Ground-Based Reconnaissance Observations of 21 Exoplanet Atmospheres with the Exoplanet Transmission Spectroscopy Imager. arXiv preprint.

DOI

Luke Schmidt, Ryan Oelkers, Erika Cook, Mary Limbach, Darren DePoy, J. Marshall, Landon Holcomb, Willians Pena, Jacob Purcell, Enrique Vega (2025). Rapid characterization of exoplanet atmospheres with the Exoplanet Transmission Spectroscopy Imager (ETSI). arXiv preprint.

DOI

Luke Schmidt, Ryan Oelkers, Erika Cook, Mary Limbach, Darren DePoy, J. Marshall, Landon Holcomb, Willians Pena, Jacob Purcell, Enrique Vega (2024). Rapid characterization of exoplanet atmospheres with the Exoplanet Transmission Spectroscopy Imager. Journal of Astronomical Telescopes, Instruments, and Systems.

DOI

Luke Schmidt, Mary Limbach, Erika Cook, Darren DePoy, Ryan Oelkers, J. Marshall, Landon Holcomb, Willians Pena, Jacob Purcell, Enrique Vega (2022). The Exoplanet Transmission Spectroscopy Imager (ETSI), a new instrument for rapid characterization of exoplanet atmospheres. Ground-based and Airborne Instrumentation for Astronomy IX.

DOI