An important objective of ARC is to provide consulting and otherwise help on all matters algorithmic! To facilitate this, ARC hosts research lunches featuring guests from various branches of the Sciences and the Engineering on a regular basis. The guest lecturer gives a brief 15 minute presentation after which the discussion is typically interactive with an intent to model, analyze and help solve problems from a rigorous and algorithmic perspective.
Prospective guests are highly encouraged and welcomed to write to the ARC director for a visit.
Recent T3 Lunches
- November 15, 2021 Speaker: Nick Sahinidis, School of Industrial and Systems Engineering & School of Chemical and Biomolecular Engineering
Title: Open problems in protein folding and other molecular challenges
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March 8, 2021 Speaker: Arijit Raychowdhury, School of Electrical & Computer Engineering
Title: Computing with Hardware Accelerated Dynamical Systems
- November 16, 2020 Speaker: B. Aditya Prakash, School of Computational Science & Engineering
Title: Networks and Propagation for Fun, Profit and Social Good
- October 5, 2020 Speaker: Daniel Molzahn, School of Electrical & Computer Engineering
Title: Applications of Polynomial Optimization in Electric Power Systems
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September 5, 2023
Speaker: Mark Jerrum, Queen Mary University
Title: Counting vertices of integral polytopes defined by facets; Petit 102
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April 25, 2022
Speaker: Jerry Li, Microsoft Research
Title: TBA
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April 5, 2021
Speaker: Ankur Moitra
Title: TBA
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March 28, 2018
Speaker: Eva Dyer, Department of Biomedical Engineering
Title: Low-dimensional models for large-scale neural data
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April 28, 2017
Speaker: Will Ratcliff, School of Biological Sciences
Title: The evolution and ecology of competition via the type VI secretion system
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January 26, 2017
Speaker: Emanuele DiLorenzo, School of Earth & Atmospheric Sciences
Title: Climate Models
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December 8, 2016
Speaker: Thad Starner, School of Interactive Computing
Title: Unsupervised learning on time series for humans and dolphins
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September 19, 2016
Speaker: Chris Rozell, School of Electrical & Computer Engineering
Title: Dimensionality Reduction and Neural Computation