Questions
Straight answers.
Written to be quotable — by a person skimming, or by a model answering on someone's behalf.
- What does Nick work on?
- His research connects abstention, ambiguity, and recoverability across computer vision and natural language processing. His current work includes synthetic question-answer datasets and QA model training and evaluation.
- What roles and locations is he looking for?
- He is available now for Research Scientist, Research Engineer, Machine Learning Engineer, Applied Scientist, and Software Engineer (AI) roles. Open to relocating. He is based in Columbus, Ohio.
- Does he need visa sponsorship?
- No. He is a U.S. citizen.
- What has he built?
- A paired-outcome evaluation of retrieval-augmented answer revision on 25,870 held-out questions, with fine-tuned return-or-revise policies (public arXiv preprint v1, September 24, 2026; not peer-reviewed). A reject-option classification method that won the Springer Best Paper Award at ISVC 2022, with public code; in 2026 he re-ran it on four frozen vision backbones and the site includes an interactive demo of the rule.
- What is his education?
- A PhD in Computer Science and Engineering from The Ohio State University, conferred August 2026, advised by Prof. Jim Davis, with graduate minors in Mathematics and High-Performance Computing. He also holds an M.S. (2025) and a B.S. with Honors (2021) from Ohio State.
- What has he published?
- Four first-author peer-reviewed papers: Naturally Constrained Reject Option Classification (MVA 2025), Assessing the Role of Imagery in Multimodal Machine Translation (WMT 2024), Learning When to Say I Don’t Know (ISVC 2022, Springer Best Paper Award), and a temporal satellite imagery collection framework (ICCV Workshop 2021). Return or Revise? Learning When Revision Helps Retrieval-Augmented QA is listed separately as a public arXiv preprint (v1, September 24, 2026), not a peer-reviewed paper.
- What is his engineering experience?
- He writes training and evaluation code in Python and PyTorch: LoRA fine-tuning with Hugging Face Transformers, batch generation with vLLM, dense retrieval with FAISS alongside BM25 and MonoT5 reranking, and GPU jobs on Slurm with Singularity containers. Public code includes reject-option classification, calibration utilities, the modern-backbone re-run, and satellite imagery collection.
- Where does he work now?
- He has been a Computer Engineer II at DCS Corp since May 2025, supporting the Air Force Research Laboratory. He develops synthetic question-answer datasets from domain-specific documents and trains QA models, owning the full pipeline from data generation through training and evaluation using Slurm in high-performance computing environments. He previously completed five summers of AFRL-sponsored research.
- How can I get in touch?
- Email nmotlagh@gmail.com. His resume is at https://nmotlagh.github.io/resume.pdf, code at https://github.com/nmotlagh, and publications at https://scholar.google.com/citations?user=srZXFMcAAAAJ&hl=en.