Talks, workshops, and current dissemination

• Deep Learning for Science School (DL4Sci), Berkeley Lab 2026
  Five-day summer school on foundation models, reasoning, and agentic AI for scientific discovery.
• Workshop on Network Algorithms, Analysis, and Learning for Science, Berkeley Lab 2025
  Poster: A Framework for Quantifying Variability in LLM-Generated Graphs.
• Summer Institute in Computational Social Science (SICSS-Penn), University of Pennsylvania 2025
  Collaboration on multi-agent LLM frameworks and longitudinal influence modeling.
• SIAM Conference on Mathematics of Data Science (MDS24) 2024
  Co-organized the mini-symposium Graph Learning and Network Analytics: Framework, Information Flow, and Applications; presented Decoding Social Networks: LLM Agents and Information Flow Dynamics.
• First Annual Data Science Conference, University of Nevada, Reno 2024
  Poster presenter.

• A Learning World
• Stochastic Deep Learning
• LLM Agents in Social Network Dynamics: A Study on Information Flow and Propagation
• Exploring Relationships Between Network Properties: A Regression Analysis
• DriveOhio, Autonomous Vehicle Shuttle Service Planning
• Insights into Network Science and Epidemic Modeling in Network Data
• Gold and Bitcoin Portfolio Modeling, 2022 (Meritorious Winner)

• Lamichhane, B., Joseph Palardy, Singh, A.K. The Nuances of Large-Language-Model-Agent Performance in Simple English Auctions. Empirical Economics Letters, 2024.
• Lamichhane, B., Singh, A.K., Devkota, S., Dhakal, U., Singh, S., and Dhakal, C. Understanding the Influence of Genre-Specific Music Using Network Analysis and Machine Learning Algorithms. MDPI Big Data and Cognitive Computing, 2023.
• Singh, A.K., Devkota, S., Lamichhane, B., Dhakal, U., and Dhakal, C. Do Large Language Models Show Human-like Biases? Exploring the Confidence-Competence Gap in AI. MDPI Information, 2024.