https://chrisman.org/Lonnie   
 

Presentations, Videos, Podcast interviews

  • Lonnie Chrisman (10 Sep 2025, upcoming), "Is AI the biggest risk to risk analysis-- or its future?", in person keynote presentation at SiraCON 2025, Boston.
  • Lonnie Chrisman (5 Aug 2025, upcoming), "AI as a collaborative partner in decision modeling: A glimpse into the future", Society of Decision Professionals (SDP) Australasia, free online presentation, sign up page.
  • Lonnie Chrisman (March 2025), "Advancing model-driven decision making through AI assistance", Society of Decision Professionals (SDP 2025) conference presentation, Vancouver, BC.
  • Lonnie Chrisman (26 Feb 2025), "Demo on Assista, the new AI assistant in Analytica", Lumina webinar.
  • Lonnie Chrisman (21 Oct 2024), "An agentic and collaborative AI assistant for building decision models", in-person presentation to the Bay aRea AI Network (BrAIN) meetup at POSHMARK. (Not recorded)
  • Lonnie Chrisman (10 Oct 2024), "An AI assistant collaboration to develop risk management models", Risk Awareness Week 2024 conference presentation.
  • Mark Kuczmarski and Shashank Bharadwaj (Sept 14, 2024), "Interview with Lonnie Chrisman" on "The Generative AI Meetup Podcast", episode titled "The most outstanding electrical engineering student in the USA".
  • Lonnie Chrisman (Oct. 2023), “Artificial Intelligence in plain English: Why everyone’s so fascinated”, presentation given at Saratoga Retirement Community.
  • Lonnie Chrisman (May 2023), “A.I. and Machine Learning: Crossing Frontiers with Lonnie Chrisman, Ph.D.”, Lumina webinar,

    • Selected articles

  • Lonnie Chrisman (Nov. 2023), "Does GPT-4 pass the Turing test?, Lumina blog.
  • Sammy Martin, Lonnie Chrisman, Aryeh Englander (Aug. 2023), “A model-based approach to A.I. existential risk”, A.I. Alignment Forum and Less Wrong
  • Lonnie Chrisman and Ryan Chin (Aug. 2023), “Computer Programming in English (part 1 & part 2): Lumina blog,
  • Aryeh Englander, Lonnie Chrisman, Yaakov Trachtman (Jan. 2023), “Is the Fermi Paradox due to the Flaw of Averages?”, A.I. Alignment Forum and LessWrong.
  • Lonnie Chrisman (2022), “Decision making without historical precedent”, Lumina webinar.
  • Lonnie Chrisman (Aug 2021), “The deadly pillow fallacy”, Lumina blog.
  • Lonnie Chrisman (May 2020), “Voluntary vs. mandatory testing for naval crew selection”, Lumina blog.
  • Lonnie Chrisman (Apr 2020), “Early COVID-19 decay rates for countries that have peaked”, Lumina blog
  • Lonnie Chrisman (Apr 2020), “Adjusting the Santa Clara County COVID-19 Antibody testing study results for self-selection bias”, Lumina blog
  • Lonnie Chrisman (Apr 2020), “The Suppression Triangle for COVID-19: How soon can we end the lockdown?”, Lumina blog
  • Lonnie Chrisman (Apr 2020), “A critique of the HealthData.org COVID-19 model, and how it works”, Lumina blog
  • Lonnie Chrisman (Mar 2020), “Suppression strategy and updated forecast for US deaths from COVID-19 Coronavirus in 2020”, Lumina blog
  • Lonnie Chrisman (Mar 2020), “How social isolation impacts COVID-19 spread in the US: A Markov model approach”, Lumina blog
  • Lonnie Chrisman (Mar 2020), “Estimating US Deaths from COVID-19 Coronavirus in 2020”, Lumina blog
  • Lonnie Chrisman (2 Feb 2020), “The mortality rate of the Wuhan coronavirus”, Lumina blog

    • Selected publications

  • Manel Baucells, Lonnie Chrisman, Thomas W. Keelin and Stephen Xu (2025), "On the properties of the Metalog distribution", submitted for publication.
  • Keelin, Thomas W., Lonnie Chrisman, and Sam L Savage. “The Metalog Distributions and Extremely Accurate Sums of Lognormals in Closed Form.” In 2019 Winter Simulation Conference (WSC), 3074–85. National Harbor, MD, USA: IEEE, 2019. doi.org/10.1109/WSC40007.2019.9004930. [pdf]
  • S.D. Bay, L. Chrisman, A. Pohorille, and J. Shrager, “Temporal Aggregation Bias and Inference of Causal Regulatory Networks”, Journal of Computational Biology 11(5), 2004. [abstract] [pdf]
  • Lonnie Chrisman, Pat Langley, Stephen Bay and Andrew Pohorille, "Incorporating Biological Knowledge into Evaluation of Causal Regulatory Hypotheses", Pacific Symposium on Biocomputing (PSB), Kawaii, Hawaii, January 2003. [abstract] [pdf]
  • Lonnie Chrisman, "Incremental conditioning of lower and upper probabilities." International Journal of Approximate Reasoning 13(1):1-25, 1995. [pdf]
  • Lonnie Chrisman, "Propagation of 2-Monotone Lower Probabilities on an Undirected Graph", Proceedings of Uncertainty in Artificial Intelligence (UAI), Portland, Oregon, August 1996. [pdf]
  • Lonnie Chrisman, "Independence with Lower and Upper Probabilities", Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), Portland, Oregon, August 1996. [pdf]
  • Reid Simmons, Lars Henriksen, Lonnie Chrisman, and Greg Whelan, "Obstacle Avoidance and Safeguarding for a Lunar Rover", Panel on Planetary Robotics, American Institute of Aeronautics and Astronautics (AIAA) Annual Robotic Technology Forum on Advanced Developments in Space Robotics, University of Wisconsin, Madison, July 1996. [pdf]
  • Reid Simmons, Eric Krotkov, Lonnie Chrisman, Fabio Cozman, Richard Goodwin, Martial Hebert, Guillermo Heredia, Sven Koenig, Pat Muir, Yoshikazu Shinoda, and William Whittaker, "Mixed-mode control of navigation for a lunar rover." Proceedings of the S.S.I./Princeton Space Manufacturing Conference, Princeton, N.J., 1995. [abstract] [pdf] [download]
  • Reid Simmons, Eric Krotkov, Lonnie Chrisman, Fabio Cozman, Richard Goodwin, Martial Hebert, Latitesh Katragadda, Sven Koenig, Gita Krishnaswamy, Yoshikazu Shinoda, William Whittaker, and Paul Klarer, "Experience with rover navigation for lunar-like terrains." Proceedings of the International Conference on Robot Systems (IROS), Pittsburgh, PA 1995. [pdf]
  • Lonnie Chrisman, "Reasoning about probabilistic actions at multiple levels of granularity." AAAI Spring Symposium Series: Decision-Theoretic Planning, Stanford University, March 1994.
  • Lonnie Chrisman, "Reinforcement learning with perceptual aliasing: The perceptual distinctions approach." Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI), Morgan Kaufmann, 1992. [pdf]
  • Lonnie Chrisman, "Abstract probabilistic modeling of action." Proceedings of the First International Conference on Artificial Intelligence Planning Systems (AIPS.), J. Hendler (ed.), Morgan Kaufmann, 1992. [pdf]
  • Lonnie Chrisman, "Planning for closed-loop execution using partially observed Markovian decision processes." AAAI Spring Symposium Series: Control of Selective Perception, Stanford University, March 1992. [pdf]
  • Lonnie Chrisman, "Decision theory or the holy grail?: Response to Tom Dean's Position", AAAI Spring Symposium Series: Control of Selective Attention, position statement included with proceedings to symposium participants, Stanford University, March 1992.
  • Lonnie Chrisman, Rich Caruana, and Wayne Carriker, "Intelligent agent design issues: Internal agent state and incomplete perception." AAAI Fall Symposium Series: Sensory Aspects of Robotic Intelligence, Avi Kak (ed.). Nov. 1991. [pdf]
  • Lonnie Chrisman and Reid Simmons, "Sensible planning: Focusing perceptual attention." Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI), 1991. [pdf]
  • Lonnie Chrisman, "Learning recursive distributed representations for holistic computation." Connection Science 3(4):345-366, 1991. [download] [pdf]
  • Lonnie Chrisman, "Evaluating bias during Pac-learning." Proceedings of the Sixth International Workshop on Machine Learning, Morgan Kaufmann, 1989. [abstract]
  • Joann Stevenson, Lonnie Chrisman, and Douglas Silkwood, "Data management for tissue samples in an ultrastructure laboratory." Eleventh Western Regional Meeting of Electron Microscopists, Asilomar, Pacific Grove, Ca., May 1983.

    • Technical Reports

  • Fabio Cozman and Lonnie Chrisman, "Learning Convex Sets of Probability from Data", Robotics Institute, Carnegie Mellon University, CMU-RI-TR-97-24, June 1997. [abstract] [pdf]
  • Lonnie Chrisman, "Approximation of Graphical Probabilistic Models by Iterative Dynamic Discretization and Application to Time-Series Segmentation", Ph.D. Thesis, CMU-CS-96-166, Sept. 1996. [pdf]
  • Lonnie Chrisman, "Learning recursive distributed representations for holistic computation", Carnegie Mellon University, CMU-CS-91-154, 1991. [pdf]
  • Lonnie Chrisman, "Extending the Valiant framework to detect incorrect bias", Carnegie Mellon University, CMU-CS-89-137, May 1989. [pdf]

    • Patents

  • Max Henrion, Lonnie Chrisman and Zac Robinson, "Automated decision advisor, US Patent #7080071, filed 2001, granted 2006.

    • Other

  • Lonnie Chrisman, "A Roadmap to Bayesian Network Research", unpublished, last updated 1996.
  • Lonnie Chrisman and Michael Littman, "Hidden State and Short-Term Memory: A bibliography", unpublished, from ML93 reinforcement learning workshop presentation, 1993. [pdf]