Orit Peleg's research is aimed at understanding how biological communication signals are generated and interpreted. While the channel may change - whether chemical, sound, or light - the living creatures of our world all encode high-dimensional biological features into low-dimensional communication patterns. Peleg uses insect swarms as a model system for identifying how organisms harness the dynamics of communication signals, perform spatiotemporal integration of these signals, and propagate those signals to neighboring organisms. Examples include fireflies who communicate over long distances using light signals, and bees who serve as signal amplifiers to propagate pheromone-based information about the queen’s location.
keywords
Collective Behavior, Local Sensing, Distributed Systems, Physics of Living Systems
CSCI 4314 - Dynamic Models in Biology
Primary Instructor
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Spring 2019 / Spring 2020 / Spring 2021 / Spring 2022 / Spring 2023
Surveys computational and mathematical modeling to illuminate biological processes. Students work together to learn to build and analyze models using a variety of numerical tools, tackle meaningful biological problems, and communicate effectively across disciplines. Specific topics: Langevin dynamics of protein folding, agent-based models, finite difference models of organismal growth, stochastic and deterministic cellular automata game of life, models of behavior. Recommended prerequisite: Linear Algebra (CSCI 2820 or CSCI2897 or MATH 2130 or MATH 2135 or APPM 2360 or APPM 3310), and intended for students in their third or fourth years of Computing or other majors. Same as CSCI 5314.
CSCI 4831 - Special Topics in Algorithms
Primary Instructor
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Spring 2018
Covers topics of interest in computer science at the upper-division undergraduate level. Content varies from semester to semester. Only 9 credit hours from CSCI 4830 and/or CSCI 4831 can count toward Computer Science BS or BA.
CSCI 5314 - Dynamic Models in Biology
Primary Instructor
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Spring 2019 / Spring 2020 / Spring 2021 / Spring 2022 / Spring 2023
Surveys computational and mathematical modeling to illuminate biological processes. Students work together to learn to build and analyze models using a variety of numerical tools, tackle meaningful biological problems, and communicate effectively across disciplines. Specific topics: Langevin dynamics of protein folding, agent-based models, finite difference models of organismal growth, stochastic and deterministic cellular automata game of life, models of behavior. Recommended prerequisite: comfort with mathematics and/or programming experience, and more advanced understanding (upper undergraduate level) of any relevant discipline. Same as CSCI 4314.
CSCI 5423 - Biologically-inspired Multi-Agent Systems
Primary Instructor
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Spring 2019 / Spring 2020 / Spring 2021 / Spring 2022 / Spring 2023
Explores the principles and emergent properties of collective dynamics through computational modeling and theory. Focuses on multi-agent systems using insights from biology, like the self-assemblage of cells and insect colony behavior. Topics include designing swarm intelligence, networked agents, cellular computing and self-assembly, optimization, synchronization, and evolutionary computation. Uses cross-discipline research developments to practice applied techniques. Biology background is not required. Recommended prerequisite: CSCI 2270 and basic knowledge of programming.
CSCI 7000 - Current Topics in Computer Science
Primary Instructor
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Spring 2018
Covers research topics of current interest in computer science that do not fall into a standard subarea. May be repeated up to 18 total credit hours.
