The annual IAM retreat will be held on Friday, April 11th 2024, from 9am to 4:30pm, at the Green College Coach House, located at 6201 Cecil Green Park Road. The IAM retreat is a day-long event where graduate students and post-doctoral fellows have the opportunity to share their research with the community in the format of brief (five-minute) presentations. The retreat is an excellent opportunity to learn about the wide range of research interests in the IAM, eat delicious catered food (coffee, lunch, and snacks), and enjoy great company.
Everyone associated with the IAM is invited to attend, and we encourage all interested graduate students, post-doctoral fellows, and faculty to register, whether they are official IAM members or not. IAM students and post-docs are also encouraged to sign up to give a five-minute talk on their research. In the case that the number of those wishing to give talks is greater than the number of “talk-spots” available, talks will be admitted on a first-come basis.
Vital information:
- Registration is now closed. If you signed up to deliver a talk, the talk slides are due on April 8.
- Retreat location: Green College Coach House, located at 6201 Cecil Green Park Road.
- Retreat Timing: 9am to 4:30pm.
- Catered snacks, coffee/tea, and lunch will be served.
SCHEDULE
9:00 – 9:30 | Check-in; coffee, tea, and bagels | |||
9:30 – 9:40 | A word from the IAM director | |||
9:40 | Session 1 | Liam Yih | Mathematics | Small Scale Binders Under Forces |
9:48 | Jonah Hall | Microbiology/Immunology | Optimization of Pertussis Immunization Using Mathematical Modeling | |
9:56 | Katie Faulkner | Mathematics | Lipid regulation and type 2 diabetes | |
10:04 | Tim Tian | Mathematics | Modelling Plant Cortical Microtubules | |
10:12 | Victor Ogesa Juma | Mathematics | Diffusion-induced transitions and far-from-equilibrium dynamics in a bistable reaction-diffusion system | |
10:20 | Gulsemay Yigit | Mathematics | The role of the geometry for pattern formation in reaction-diffusion systems | |
10:28 | Jupiter Algorta | Mathematics | Minimal Models for Migrating Cells | |
10:40 – 11:00 | Break | |||
11:00 | Session 2 | Fatemeh Saghafifar | Mathematics | Unraveling Cell Paths: Inferring Trajectories Through Random Walk Models |
11:08 | Yuqi Xiao | Mathematics | Modeling mechanosensitive cell response to implant after reconstructive breast cancer surgery | |
11:16 | Sharvaj Kubal | Mathematics | Optimal sequencing depth for single-cell RNA-sequencing in Wasserstein space | |
11:24 | Vincent Guan | Mathematics | Langevin SDEs have unique transient dynamics | |
11:32 | Maricela Best Mckay | Mathematics | Sketchy Natural Gradient Descent for Physics Informed Neural Networks | |
11:40 | Maksym Zubkov | Mathematics | Understanding Neural Networks via Tensors | |
11:48 | Matthew Scott | Mathematics | Denoising Optimized Compressive Sampling | |
12:00 – 2:00 | Lunch | |||
2:00 | Session 3 | Yabing Qi | Computer Science | Using Online Learning to Detect Misinformation |
2:08 | Nicholas Richardson | Mathematics | Discretizing Constraints at Multiple Scales | |
2:16 | Yao Kuang | Computer Science | BlockProx: A Communication-Efficient Proximal Method for Decentralized Multi-task Learning | |
2:24 | Ana Mucalica | Mathematics | Elastic Capsules in Inertial Shear Flow: A Snapshot of Suspension Rheology | |
2:32 | Biswajeet Rath | Mechanical Engineering | Elastic Contact of Deformable Bodies in Fluid Flow | |
2:40 | Yuxiu Zhang | Mathematics | Hartree Equation and its Semiclassical Limit | |
2:48 | Marnie Smith | Mathematics | Quantum Landau damping | |
3:00 – 3:20 | Break | |||
3:20 | Session 4 | Clement Soubrier | Mathematics | Modelling meiotic spindle using spatial birth-death process |
3:28 | Shikun Nie | Mathematics | Inference of Rate Parameters in Superresolution Imaging via Hidden Markov Models | |
3:36 | Pavel Buklemishev | Mathematics | Cell Shape Analysis | |
3:44 | Musanna Galib | Mechanical Engineering | Dendrite Inhibition Strategy Using Hetero-Epitaxy In Thin Film Deposition Mechanics | |
3:52 | Roger Bader | Mathematics | Improved Training Method for Energy-Based Models | |
4:00 | Francesco Tosello | Mathematics | How Data Structure Affects Learning in Restricted Boltzmann Machines | |
4:10 – 4:30 | Wrap-up |
All the best,
Ali, Anny, Clément and Sharvaj
Student Committee of the IAM