We keep a short list of special events on campus or nearby relevant to machine learning here.
For the latest information about these events, click the links below or see the primary source: Tufts CS Events Webpage
Events happening over zoom: . Access details are available on the colloquium website. Please message csadmin(AT)cs.tufts.edu to get the password.
Reading group: Interested research students are also invited to our machine learning reading group (we meet once a week). For details, please contact a faculty member.
Events: Fall 2020
SEP
24
Colloquium: Addressing Problems in Global Health with Non-traditional Data and Machine Learning
- 09/24
- 3:00PM
- Zoom
Speaker: Elaine O. Nsoesie, Boston University
OCT
01
Colloquium: Machine Learning for Drug Discovery
- 10/01
- 3:00PM
- Zoom
Speaker: Alix Lacoste, Benevolent AI
OCT
15
Colloquium: Equitable machine learning to advance healthcare
- 10/15
- 3:00PM
- Zoom
Speaker: Irene Chen, MIT
NOV
05
Colloquium: Physics Guided Machine Learning: A New Framework for Accelerating Scientific Discovery
- 11/05
- 3:00PM
- Zoom
Speaker: Vipin Kumar, University of Minnesota
DEC
10
Colloquium: Knowledge-based Biomedical Data Science
- 12/10
- 3:00PM
- Zoom
Speaker: Larry Hunter, University of Colorado
Events: Spring 2020
MAR
19
JAN
31
Event: Launch of the NSF-funded TRIPODS institute at Tufts
- 01/31
- 9:00AM
- TBD
Speaker: Several internal and external speakers
Events: Fall 2019
NOV
19
Doctoral Thesis Defense: Characterizing Pathway-Specific Anomalies in Temporal Patterns of Gene Expression
- 11/19
- 3:00PM
- Halligan 102
Speaker: Michael Pietras
NOV
7
Colloquium: What is your data worth? Quantifying the value of data in machine learning
- 11/07
- 3:00PM
- Halligan 102
Speaker: James Zou, Stanford
SEP
12
Colloquium: Towards More Automated Machine Learning: High-Dimensional Bayesian Optimization and Probabilistic Neural Architecture Search
- 09/12
- 3:00PM
- Halligan 102
Speaker: Nicola Fusi, Microsoft Research
Events: Spring 2019
MAR
04
Colloquium: Data Enrichment for Data Science
- 03/04
- 3:00PM
- Halligan 102
Speaker: Fatemeh Nargesian, U. Toronto
FEB
07
Colloquium: Natural Language Understanding for Events and Participants in Text
- 02/07
- 3:00PM
- Halligan 102
Speaker: Rachel Rudinger, Johns Hopkins
FEB
04
Colloquium: Structured Approaches to Natural Language Understanding
- 02/04
- 3:00PM
- Halligan 102
Speaker: Snighda Chaturvedi, UCSC
JAN
31
Colloquium: Algorithmic Human-Robot Interaction for All People
- 01/31
- 3:00PM
- Halligan 102
Speaker: Elaine Short, UT-Austin
JAN
28
Colloquium: Learning from Natural Language Supervision
- 01/28
- 3:00PM
- Halligan 102
Speaker: Shashank Srivastava, CMU
Events: Fall 2018
DEC
13
DEC
06
Colloquium: Aurum: A Data Discovery System
- 12/06
- 3:00PM
- Halligan 102
Speaker: Raul Castro Fernandez (MIT)
NOV
29
Colloquium: Reliable Decision-Support using Counterfactual models
- 11/29
- 3:00PM
- Halligan 102
Speaker: Peter Schulam (Johns Hopkins)
NOV
06
Colloquium: Data Science Humanely
- 11/06
- 3:00PM
- Halligan 102
Speaker: Carlos Scheidegger (University of Arizona)
OCT
26
PhD Thesis Defense: Incremental and Memory-Limited Probabilistic Generative Models of Early Word Learning
- 10/26
- 10:00AM
- Halligan 209
Speaker: Sepideh Sadeghi
OCT
12
PhD Thesis Defense: Algorithms and Theory for Variational Inference in Two-level Non-conjugate Models
- 10/12
- 10:00AM
- Halligan 102
Speaker: Rishit Sheth
OCT
11
Guest Lecture: Horseshoe Priors for Bayesian Neural Networks
- 10/11
- 3:00PM
- Halligan 111A
Speaker: Soumya Ghosh (IBM Research)
OCT
04
Colloquium: Online Algorithms for Extreme Clustering and Automated Integration of Crowdsourced Feedback
- 10/04
- 3:00PM
- Halligan 102
Speaker: Ari Kobren (University of Massachusetts, Amherst)
SEP
27
Colloquium: Bayesian Nonparametric Machine Learning for Discrete Random Structures
- 09/27
- 3:00PM
- Halligan 102
Speaker: Diana Cai (Princeton)
SEP
06
Colloquium: Human-in-the-Loop AI for Autonomous Problem Solving (or why humans ruin the best things)
- 09/06
- 3:00PM
- Halligan 102
Speaker: Kartik Talamadupula, IBM