Alexander D. Greenhalgh

@misc{cho2026unipounifiedinteractivevisual,
  title         = {UNIPO: Unified Interactive Visual Explanation for RL Fine-Tuning Policy Optimization},
  author        = {Aeree Cho and Alexander D. Greenhalgh and Jonathan Bodea and Anthony Peng and Duen Horng (Polo) Chau},
  year          = {2026},
  eprint        = {2605.11549},
  archivePrefix = {arXiv},
  primaryClass  = {cs.HC},
  url           = {https://arxiv.org/abs/2605.11549}
}

@inproceedings{10.1145/3770762.3772654,
  author = {Deng, Patrick and Greenhalgh, Alexander D. and Yu, Brian and Lytle, Nicholas and Joyner, David A.},
  title = {Exploring Transitions of Graduates From an Online Master's in Computer Science Program to Doctoral Programs},
  year = {2026},
  isbn = {9798400722561},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3770762.3772654},
  doi = {10.1145/3770762.3772654},
  abstract = {The flexibility and affordability of online, asynchronous, at-scale degree programs have significantly increased the accessibility of a master's-level graduate education. While studies have been conducted on the general growth of such programs and the quality of the online courses compared to their on-campus counterparts, few (if any) have examined outcomes such as alumni career growth or admission into other graduate programs. This work examines how one large online graduate program in computer science prepared alumni for matriculation into STEM PhD programs. Enrollment data from the National Student Clearinghouse was analyzed to identify key trends in alumni PhD enrollment. Surveys and interviews with program alumni were also conducted to investigate the unique paths that these individuals took to beginning their PhD education. This study finds that the program positively impacted alumni PhD experiences in STEM fields. Alumni noted that involvement with graduate research and coursework were key components in their preparation for a PhD program. These results demonstrate that an affordable, online, asynchronous graduate STEM program can provide non-traditional students with an effective pathway to PhD enrollment. The paper concludes with recommendations for asynchronous, at-scale degree programs seeking to expand their research opportunities for students with a desire to pursue PhD programs.},
  booktitle = {Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.1},
  pages = {281–287},
  numpages = {7},
  keywords = {learning at scale, graduate education, online education, phd pathways},
  location = {USA},
  series = {SIGCSE TS 2026}
}

@article{KIZZIRE2023112454,
  title = {Modified embedded atom method interatomic potential for FCC γ-cerium},
  journal = {Computational Materials Science},
  volume = {230},
  pages = {112454},
  year = {2023},
  issn = {0927-0256},
  doi = {https://doi.org/10.1016/j.commatsci.2023.112454},
  url = {https://www.sciencedirect.com/science/article/pii/S0927025623004482},
  author = {Dayton G. Kizzire and Alex D. Greenhalgh and Max L. Neveau and Collin M. Pekol and Michael J. Thompson and Orlando Rios and David J. Keffer},
  keywords = {Molecular dynamics, Density functional theory, Cerium, Modified embedded atom method, Machine learning, Alloy}
}

@article{10.3389/fmats.2021.797418,
  author  = {Greenhalgh, Alexander D. and Sanjeewa, Liurukara D. and Luszczek, Piotr and Maroulas, Vasileios and Rios, Orlando and Keffer, David J.},
  title   = {Assessment of Local Observation of Atomic Ordering in Alloys via the Radial Distribution Function: A Computational and Experimental Approach},
  journal = {Frontiers in Materials},
  volume  = {8},
  year    = {2021},
  url     = {https://www.frontiersin.org/journals/materials/articles/10.3389/fmats.2021.797418},
  doi     = {10.3389/fmats.2021.797418},
  issn    = {2296-8016}
}