TID Grand Round Talks

Using Artificial Intelligence to Accelerate Systems Thinking for Conflict Resolution and Change Management.

Christophe Lambert
Christophe Lambert, PhD
Interim Chief, Division of
Translational Informatics
CTSC Informatics Core
Lead, Professor


  • Creativity emerges from conflict: learn how to frame and resolve a personal or organizational conflict with the “evaporating cloud” conflict resolution diagram.

  • Understand the “resistance to change” allegory for evaluating the pros and cons of organizational change versus keeping the status quo from the perspective of multiple stakeholders.

  • Learn how to use chatGPT templates to alleviate the congnitive effort of the above two processes to accelerate our capacity to consider win-win option for personal and organizational transformation.
Thursday, Sept.7th | 12:30-1:30 pm

Using Structured Knowledge for Casual Feature Selection.

Scott Malec, PhD
Assistant Professor,
Division of Translational Informatics


  • To define and understand confounding and selection bias and why addressing these is important.

  • To answer why addressing confounding and selection bias is difficult (and what the limitations are of conventional approaches).

  • To grasp the importance of computional tools (from processing the biomedical literature with natural language processing and biomedical ontologies) for identifying cofounders and to gain an awareness of the limitations and concepts for mitigating these limitations.

Watch Full Talks

Thursday, Sept.14th | 12:30-1:30 pm

Navigating Cellular Complexity in Disease through Advanced Computational Models.

Avi Sahu, PhD
Assistant Professor, UNM
Comprehensive Cancer
Center, Division of
Translational Informatics


  • Learn how to detect cellular changes from single-cell data. Understand the limitations of current algorithms, specifically how they can produce false positives due to variations among individuals and cohorts.

  • Learn a new computional framework designed to account for individual and cohort variations in single-cell data, thereby improving the accuracy of analysis.

  • Learn how the transcriptome-translator, similar to a Google Translator for genomics, can tackle major challenges in cancer treatment, such as tumor heterogeneity and health care disparities.

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Thursday, Sept.21st | 12:30-1:30 pm