Events

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FDS events are launchpads for partnerships, spaces where disciplines cross and innovations spark. Join us to discover the exciting work—and infinite possibilities—of data science.

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Past Events

2024
09.09

S&DS Seminar: Brice Huang (MIT): "Capacity threshold for the Ising perceptron"

09.04

Computational Biology & Biomedical Informatics (CBB) and Biomedical Informatics & Data Science (BIDS) Project Match

09.04

FDS Colloquium: Quanquan C. Liu, “Massive Graph Algorithms from Theory to Practice and Back”

08.27

FDS Data Science Project Match

06.26

FDS HNL Colloquium: Boris Power (OpenAI)

06.18

FDS Member Luncheon

06.05

FDS Member Luncheon

05.22

FDS Member Luncheon

05.06

Undergraduate Data Science Poster Session

04.29

S&DS Seminar: Reza Gheissari (Northwestern)

04.28

Workshop Honoring Andrew Barron: Forty Years at the Interplay of Information Theory, Probability and Statistical Learning (Day 3)

04.27

Workshop Honoring Andrew Barron: Forty Years at the Interplay of Information Theory, Probability and Statistical Learning (Day 2)

04.26

Workshop Honoring Andrew Barron: Forty Years at the Interplay of Information Theory, Probability and Statistical Learning

04.25

Yale Theory Student Seminar: Jonas Katona, "Connections between Symplectic Integration and Algorithmic Game Theory: A Symplectic Analysis of Alternating Mirror Descent"

04.24

FDS Colloquium: David Matteson (Cornell), “Drift vs Shift: Decoupling Trends and Changepoint Analysis”

04.22

S&DS Seminar: Bingxin Zhao (UPenn), "Analyzing genetic summary data: statistical models and platforms"

04.17

FDS Member Colloquium: Van Vu (Department of Mathematics), “New perturbation bounds for matrices with rapidly decaying spectrum”

04.15

S&DS Seminar: Yiling Chen (Harvard), "Strategic Design to Improve Information Integrity"

04.10

FDS Colloquium: Earl Bellinger (Department of Astronomy), “Probing far-ranging astrophysics with big data and machine learning”

04.09

Yale Theory Student Seminar: Anay Mehrotra

04.08

S&DS Seminar: Santosh Vempala (Georgia Tech), "Robust Statistics in High Dimension"

04.04

Yale Theory Student Seminar: Heejune Sheen, "Implicit Regularization of Gradient Flow for One-layer Softmax Attention"

04.03

FDS Colloquium: Lior Pachter (Caltech), "Some open and solved problems in dimensionality reduction (for single-cell genomics data)"

04.01

S&DS Seminar: Mingyuan Zhou (UTexas at Austin), "Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation"

03.28

FDS x Math Colloquium: Phillip Atiba Solomon (f.k.a. Goff), "The After Math of Injustice"

03.27

FDS Colloquium: Aaditya Ramdas (CMU), "The numeraire e-variable and reverse information projection"

03.26

Yale Theory Student Seminar: Jane Shi (MIT)

03.25

S&DS Seminar: Johan Ugander (Stanford), "Harvesting randomness to understand computational social systems"

03.14

Yale Theory Student Seminar: Siyu Chen, "Training Dynamics of Multi–Head Softmax Attention for In–Context Learning: Emergence, Convergence, and Optimality"

03.06

FDS Colloquium: Ankur Moitra (MIT) "Learning from Dynamics"

03.05

Yale Theory Student Seminar: Geelon So (UCSD), "Optimization on Pareto sets: Geometry of Multi–objective Optimization"

02.29

Yale Theory Student Seminar: Max Ovsiankin (TTIC), "Approximation Algorithms for lp–Shortest Path and lp–Network Design problemsk"

02.21

FDS Colloquium: Dr. Yuejie Chi (CMU), "Learning from Data with Low–rank Priors and Beyond"

02.15

FDS Valentine's Day Party

02.12

S&DS Seminar: Alex Wein (UC Davis) "Fine–Grained Extensions of the Low–Degree Testing Framework"

02.08

Yale Theory Student Seminar: Curtis McDonald, "Using Log Concavity and Differential Expressions to Compute Score Diffusions"

02.05

S&DS Seminar: Manolis Zampetakis

02.01

Yale Theory Student Seminar: Marco Pirazzini, "An Approach to Computing the log–Sobolev Constant of Graphs"

01.29

S&DS Seminar: Max Simchowitz (MIT), "Mathematical Foundations for Physical Agents"

01.25

Yale Theory Student Seminar: Felix Zhou, "Applications of Uniform Sampling for Densest Subgraph"

01.22

S&DS Seminar: Mikhail Belkin (UCSD)

01.15

FDS Talk: Sifan Wang (UPenn),"Physics–informed machine learning: Theory, Algorithms, and Applications"

01.12

FDS Talk: Yuning You (TAMU), "Generalizable Graph AI for Biomedicine"

01.11

FDS Talk: Serena Wang (UC Berkeley), "Bridging gaps between metrics and goals in modern machine learning ecosystems"

01.11

FDS Talk: Tudor Manole (CMU), "Statistical Inference for Multivariate Optimal Transport"

01.04

FDS Talk: Abhishek Shetty (UC Berkeley), "Optimal PAC Bounds without Uniform Convergence"

2023
12.13

FDS Colloquium: Cristopher Moore (Santa Fe Institute), "Tensor Networks, phase transitions, and algorithms"

12.06

FDS x Astronomy Colloquium: Viviana Acquaviva, "Machine Learning for Science: A Journey from Astrophysics to Climate"

12.06

FDS Special Seminar: Kasper Green Larsen, "Bagging is an Optimal PAC Learner"

12.04

S&DS Seminar: Andrea Montanari (Stanford)

11.30

Data Science Project Match

11.29

Yale Theory Student Seminar: Tianhao Wang, "Algorithm Dynamics in Modern Statistical Learning: Universality and Implicit Bias"

11.27

S&DS Seminar: Daniel J. Hsu (Columbia University)

11.22

Yale Theory Student Seminar: Siddharth Mitra, "On System Identification in Linear Dynamical System"

11.15

FDS x Astronomy Colloquium: Shirley Ho, "Foundation Models for Science"

11.15

Yale Theory Student Seminar: Alkis Kalavasis, "Optimizing Solution–Samplers for Combinatorial Problems: The Landscape of Policy–Gradient Methods"

11.13

S&DS Seminar: Yuejie Chi (Carnegie Mellon University)

11.08

Yale Theory Student Seminar: Peiyuan Zhang, "The Minimax Theorem and Algorithms in Geodesic Metric Space"

11.06

S&DS Seminar: Devavrat Shah (MIT)

11.01

FDS Colloquium: Luciano Floridi, "The Ethics of Artificial Intelligence: Challenges and Opportunities"

11.01

Yale Theory Student Seminar: Zihan Tan (DIMACS), "On (1 + eps)– Approximate Flow Sparsifiers

10.30

S&DS Seminar: Tim G.J. Rudner (NYU)

10.25

FDS Workshop: "Theory and Practice of Foundation Models"

10.23

S&DS Seminar: Cynthia Rush (Columbia University)

10.18

Yale Theory Student Seminar: Binghui Peng (Columbia), "Memory–Query Tradeoffs for Randomized Convex Optimization"

10.16

S&DS Seminar: Cheng Mao, "Learning One–Dimensional Geometry in Random Graphs"

10.11

FDS Colloquium: Tong Wang, "ProtoX: Explaining a Reinforcement Learning Agent via Prototyping"

10.11

Yale Theory Student Seminar: Felix Zhou, "Replicable Clustering"

10.09

S&DS Seminar: Jinyoung Park, "Thresholds"

10.04

FDS x Astronomy Colloquium: Priyamvada Natarajan

10.04

Yale Theory Student Seminar: Grigoris Velegkas, "Statistical Indistinguishability of Learning Algorithms"

10.02

S&DS Seminar: Cyril Zhang (Microsoft Research NYC)

09.27

FDS Colloquium: Yunbum Kook, "Gaussian Cooling and the Dikin Walk: The Interior–Point Method for Logconcave Sampling"

09.27

Yale Theory Student Seminar: Anay Mehrotra, "Selection with Implicit Bias: Evaluating the Efficacy of Interventions"

09.25

S&DS Seminar: Subhro Ghosh (National University of Singapore)

09.22

The Unveiling of Yale's Institute for Foundations of Data Science (FDS)

09.21

Getting the Most Out of Your Representations

09.18

S&DS Seminar: Qiang Liu, Learning flows for generating and transferring data: An embarrassingly simple approach

09.13

Special Seminar: Meet the FDS Postdocs

09.13

Yale Theory Student Seminar: Xifan Yu, "From an Interview Probability Question to Expansion Properties of Some 0/1 Polytopes"

09.11

S&DS Seminar: Chris Harshaw, "Clip–OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments"

09.06

Yale Theory Student Seminar: Alkis Kalavasis, "Some Open Problems in TCS"

08.30

Yale Theory Student Seminar: Gaurav Mahajan, "Some Open Problems in TCS"

08.29

Data Science Project Match

08.23

Yale Theory Student Seminar: Aditi Laddha, "Determinant Maximization via Local Search"

08.16

Yale Theory Student Seminar: John Lazarsfeld, "Decentralized Learning Dynamics in the Gossip Model"

07.26

Yale Theory Student Seminar: Khashayar Gatmiry (MIT), "Sampling with Barriers: Faster Mixing via Lewis Weights"

07.19

Yale Theory Student Seminar: Marco Pirazzini, "On the Small Set Expansion Hypothesis"

07.12

Yale Theory Student Seminar: Asaf Etgar, "On Graphs and Geometry"

07.05

Yale Theory Student Seminar: Siddharth Mitra, "On Single–cell Trajectory Inference"

06.14

Yale Theory Student Seminar: Jinzhao Wu, "On the Optimal Fixed–Price Mechanism in Bilateral Trade"

06.07

Yale Theory Student Seminar Series: Jane Lee, "Statistics Without iid Samples: Learning From Truncated Data"

05.31

Yale Theory Student Seminar: Asaf Etgar, "On the Connectivity and Diameter of Geodetic Graphs"

05.24

Yale Theory Student Seminar: Xifan Yu, "Algorithmic Lower Bounds for Expansion Profile of Regular Graphs"

05.03

FDS Seminar: Wei Ji Ma, "Process models of complex mental computation"

05.01

Workshop: Healthcare Data Science

04.27

FDS Seminar: Abhinav Bhardwaj (Yale Math), "Entry–wise dissipation for singular vector perturbation bounds"

04.24

FDS Colloquium: Robert Schapire (Microsoft Research) "Convex Analysis at Infinity: An Introduction to Astral Space"

04.20

FDS Colloquium: Philippe Rigollet (MIT) "Statistical applications of Wasserstein gradient flows"

04.17

FDS Colloquium: Dan Yamins "A Fruitful Reciprocity: The Neuroscience–AI Connection

04.05

FDS & Econometrics Talk: Markus Pelger (Stanford) "Stripping the Discount Curve – a Robust Machine Learning Approach"

04.04

Critical Visualizations: Rethinking representations of data

04.03

S&DS Seminar: Sebastian Pokutta (TU Berlin), "Conditional Gradients in Machine Learning"

04.03

Gerstein Lab: Diego Garrido (Univ of Barcelona) “A multivariate approach to study the genetic determinants of phenotypic traits”

03.31

FDS Faculty Showcase

03.31

FDS Colloquium: Tara Javidi (UCSD) "A (Con)Sequential View of Information for Statistical Learning and Optimization"

03.29

FDS Colloquium: Nathan Srebro (TTIC) “Interpolation Learning and Overfitting with Linear Predictors and Short Programs”

03.27

S&DS Colloquium: Nadav Cohen (Tel Aviv University) "What Makes Data Suitable for Deep Learning?"

03.08

S&DS Seminar: Masatoshi Uehara (Cornell)

03.06

S&DS Seminar: Theodor Misiakiewicz (Stanford)

03.01

S&DS Seminar: Oscar Leong (Caltech)

02.27

S&DS Seminar: Lu Lu (University of Pennsylvania)

02.23

S&DS Seminar: Ilias Zadik (MIT)

02.22

S&DS Seminar: Talin Wu (Stanford)

02.20

S&DS Seminar: Zhimei Ren (University of Chicago)

02.15

S&DS Seminar: Sinho Chewi (MIT)

02.08

S&DS Seminar: Omar Montasser (TTI–Chicago)

02.08

Data Science Lit Search Nightmares (and how to avoid them)

02.06

S&DS Seminar: Raaz Dwivedi (Harvard & MIT)

02.01

S&DS Seminar: Frederic Koehler (Stanford)

01.31

Special Seminar: Dr. Maria Rodriguez Martinez (IBM Research) "Interpretable deep learning for cancer personalized medicine"

01.30

S&DS Seminar: Ruishun Liu (Stanford)

01.19

S&DS Seminar: Edward De Brouwer (KU Leuven)

01.13

FDS Seminar: Ming Yin (UCSB)

01.13

FDS Seminar: Gaurav Mahajan (UCSD)

01.12

FDS Seminar: Arnab Auddy (Columbia)

2022
12.19

FDS Seminar: Alkis Kalavasis (National Technical University of Athens)

12.16

FDS Seminar: Aditi Laddha (GA Tech)

12.16

FDS Seminar: Yuchen Wu (Stanford University)

11.22

FDS Seminar: Michael Lopez Sr. (NFL) "Analyzing the National Football League is challenging, but player tracking data is here to help"

11.09

FDS Seminar: Priya Panda (Department of Electrical Engineering)"Exploring Robustness and Energy–Efficiency in Neural Systems with Spike–based Machine Intelligence"

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