Qixu Gong, Ph.D.

Postdoctoral Researcher at New Mexico State University

Specializing in Large Language Models (LLM), Graph Mining, and AI-driven Data Analysis.

Latest News

Upcoming Paper "Deep clustering for large-scale interpretable time series segmentation" accepted by Data Mining and Knowledge Discovery.
July 2024 Paper "Effect of post-weaning development method on spring grazing patterns" published in Livestock Science.
June 2024 Paper "Development of a novel classification approach for cow behavior analysis" published in Sensors.
May 2024 Paper "Backbone Index and GNN Models for Skyline Path Query Evaluation" published in ACM TSAS.
Jan 2024 Joined New Mexico State University as a Postdoctoral Researcher.

About Me

I am a Postdoctoral Researcher at the Department of Computer Science, New Mexico State University (NMSU). Previously, I worked as a Data Scientist at Cisco Systems in San Jose, CA.

My research focuses on Large Language Models (LLM) and graph algorithm optimization. I obtained my Ph.D. in Computer Science from NMSU with a GPA of 3.972. My technical expertise includes fine-tuning leading-edge language models (BERT, T5, Llama, Mistral) and developing efficient query processing techniques for large-scale graphs.

Technical Skills

Experience

Postdoctoral Researcher | New Mexico State University

Present | Las Cruces, NM
  • Conducting advanced research in Computer Science, focusing on graph algorithms and machine learning applications.
  • Collaborating with faculty and students on interdisciplinary projects involving data analysis and algorithm design.

Data Scientist | Cisco Systems

Jan 2022 – 2024 | San Jose, CA
  • Developed in-house LLM systems to facilitate downstream tasks within the Cisco Customer Partner Cloud framework.
  • Developed an end-to-end, AI-guided troubleshooting system with an interactive notebook.
  • Fine-tuned Bi-encoder and Cross-encoder models with network-specific data, improving retrieval accuracy by approximately 50%.
  • Designed a "Tailored Risk Analysis" engine deployed for 4000+ SNTC customers.

Research Assistant | New Mexico State University

Aug 2015 – Dec 2021 | Las Cruces, NM
  • Designed the "Backbone Index" to support approximate skyline queries on large road networks (10M nodes) with 0.5s query time.
  • Developed GRAZETOOLS to analyze animal behaviors using GPS data, widely used by researchers in animal and range sciences.

Selected Publications

Journal Articles
Deep clustering for large-scale interpretable time series segmentation Qixu Gong, et al. Data Mining and Knowledge Discovery, 2024 (Accepted)
Effect of post-weaning development method on spring grazing patterns Qixu Gong, et al. Livestock Science, 2024
Development of a novel classification approach for cow behavior analysis using tracking data and unsupervised machine learning techniques J Liu, DW Bailey, H Cao, TC Son, CT Tobin, Q Gong Sensors 24 (13), 4067, 2024
Backbone Index and GNN Models for Skyline Path Query Evaluation over Multi-cost Road Networks Qixu Gong, Huiying Chen, Huiping Cao, and Jiefei Liu ACM Transactions on Spatial Algorithms and Systems (TSAS), 2024
Weight Gain, Grazing Behavior and Carcass Quality of Desert Grass-fed Raramuri Criollo vs. Crossbred Steers MM McIntosh, AF Cibils, RE Estell, S Nyamuryekung'e, AL González, Q Gong, et al. Livestock Science, 2021
Media-aware quantitative trading based on public Web information Qing Li, Tiejun Wang, Qixu Gong, et al. Decision Support Systems, 2014
Conference Proceedings
GRAZETOOLS: a Set of Tools for Analyzing Livestock Behavior Using GPS data Q Gong, H Cao, A Cibils, S Nyamuryekung'e, M McIntosh, F Continanza AGU Fall Meeting, 2020
CSQ System: A System to Support Constrained Skyline Queries on Transportation Networks Qixu Gong, Jiefei Liu, Huiping Cao IEEE International Conference on Data Engineering (ICDE), 2020
Skyline queries constrained by multi-cost transportation networks Qixu Gong, Huiping Cao, Parth Nagarkar IEEE International Conference on Data Engineering (ICDE), 2019

Projects