MCB 529

Spring 2026 All Classes

All Classes

Special Topics in Cell and Developmental Biology

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Credit: 1 TO 4 hours.

Discussion of current topics of interest in higher eukaryotic cellular and molecular biology, development, neurobiology; seminar or lecture format. Topics vary.

Approved for Letter and S/U grading. May be repeated if topics vary, to a maximum of 8 hours. Prerequisite: Consent of instructor.

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MCB 529 class schedule data for spring 2026
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
78465	Lecture-Discussion	BA1	4:30PM -5:30PM	M	Location Pending	Gillette, R Gribkova, E Zhai, C	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 1 hours Section Title: Biologically Plausible AI Section Info: Topic: From Biological to Artificial Intelligence Recent breakthroughs in Artificial Intelligence (AI) technologies, notably deep neural networks and reinforcement learning, were largely inspired by our understanding of biological intelligence and how human brain works. At the same time, effective AI models such as large language models may also provide insights useful for understanding biological intelligence. This course will explore a broad range of topics in AI, as well as biological principles of intelligence and their implementation in AI. We will review current state-of-the-art AI models, with particular focus on biological plausibility. Course topics may include but are not limited to: biological and artificial memory systems, generative AI models, reinforcement learning algorithms, and evolution of nervous systems and behavioral complexity. There will be weekly discussions and student presentations of recent papers, aiming to explore the potential advantages, complexities, and short-comings of the AI models presented, and how they relate back to biological, psychological, and evolutionary principles.
78493	Lecture-Discussion	BA2	4:30PM -5:30PM	M	Location Pending	Gillette, R Gribkova, E Zhai, C	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 2 hours Section Info: Topic: From Biological to Artificial Intelligence Recent breakthroughs in Artificial Intelligence (AI) technologies, notably deep neural networks and reinforcement learning, were largely inspired by our understanding of biological intelligence and how human brain works. At the same time, effective AI models such as large language models may also provide insights useful for understanding biological intelligence. This course will explore a broad range of topics in AI, as well as biological principles of intelligence and their implementation in AI. We will review current state-of-the-art AI models, with particular focus on biological plausibility. Course topics may include but are not limited to: biological and artificial memory systems, generative AI models, reinforcement learning algorithms, and evolution of nervous systems and behavioral complexity. There will be weekly discussions and student presentations of recent papers, aiming to explore the potential advantages, complexities, and short-comings of the AI models presented, and how they relate back to biological, psychological, and evolutionary principles.
51948	Conference	GSD	3:30PM -4:50PM	M	7 Burrill Hall	Sokac, A	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 1 hours Section Title: Graduate Skill Development Section Info: Graduate students will build skills to: (1) work in interdisciplinary and diverse teams; (2) orally communicate research findings; and (3) proactively advance their professional development towards a chosen career path. Emphasis will be placed on conducting original research with rigor and attention to societal impact, while also building transferrable professional skills. This holistic research training will prepare students to address pressing challenges of our time as they take their place in the modern STEM workforce. Restriction(s): Restricted to Graduate - Urbana-Champaign.