Merge pull request #1066 from jayfo/schedules

Post Student Meeting Schedule

_compile-calendar-sequences.yml

@@ -1281,14 +1281,14 @@ sequences:
     hash: fa4f3e45c97efc62c72e8908c80ce7d8
     sequence: 1
   _seminars/2024-04-03.md:
-    hash: d777350b1bb3fc9ef9110af16be82639
-    sequence: 4
-  _seminars/2024-04-17.md:
-    hash: db08d1da669bf80310b81284f184ccd3
+    hash: c668cec0bb4afe0e20c047f64986bdb5
     sequence: 5
+  _seminars/2024-04-17.md:
+    hash: dbde0c688a5d93d290c33516bb9927ff
+    sequence: 6
   _seminars/2024-05-01.md:
-    hash: 40fc29174e0f2b5fef205527c77f02eb
-    sequence: 3
+    hash: 9e37f80569ba464fba35132b37df4b24
+    sequence: 4
   _seminars/2024-05-08.md:
     hash: 43e59e2c5972e34d9bf3c5aafcfc7a71
     sequence: 2

_seminars/2024-04-03.md

@@ -13,7 +13,7 @@ version: 1
 # - This is used to keep the iCal up to date.
 # - Increment the sequence each time the seminar file is updated.
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-sequence: 4
+sequence: 5
 
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 # Date and time of the seminar.
@@ -151,6 +151,14 @@ location:   "CSE2/Gates 401 - Hybrid via Zoom"
 abstract: |
   Compositionality is a fundamental characteristic of both human vision as well as natural language. It allows us to recognize new scenes and understand new sentences as a composition of previously seen atoms (e.g. objects in images or words in a sentence). Although scholars have spent decades injecting compositional priors into machine learning models, these priors have fallen away with the recent rise of large-scale models trained on internet scale data. In this talk, I will first formalize the notion of compositionality for vision and language by drawing on cognitive science literature. WIth this formalization, we evaluate whether today's best models (including GPT-4V and Gemini) are compositional, uncovering that they perform close to random chance. Next, we will draw on additional priors from neuroscience and cognitive science experiments on human subjects to suggest architectural changes and training algorithms that encourage the emergence of compositionality. Next, we will utilize the same formalism to evaluate generative models, embodied AI, and tool-usage, showcasing that they too are not compositional and demonstrate mechanisms to improve them. Finally, we will end by showing that compositionality can also be used to identify cultural and linguistic biases in datasets and model behaviors, and provide suggestions for how cultural diversity might be one way to improve models.
 
+  #### Schedule 
+  
+  11:45am - 12:15pm: Food and community socializing.
+
+  12:15pm - 1:15: Presentation with Q&A.  Available hybrid via Zoom.
+
+  1:15pm - 2:00pm: Student meeting and discussion with speaker, held in CSE2/Gates 371.
+
 bio: |
   Ranjay Krishna is an Assistant Professor at the Paul G. Allen School of Computer Science & Engineering. His research lies at the intersection of computer vision and human computer interaction. This research has received best paper, outstanding paper, and orals at CVPR, ACL, CSCW, NeurIPS, UIST, and ECCV, and has been reported by Science, Forbes, the Wall Street Journal, and PBS NOVA. His research has been supported by Google, Amazon, Toyota Motor, Sony, Cisco, Toyota Research Institute, NSF, ONR, and Yahoo. He holds a bachelor's degree in Electrical & Computer Engineering and in Computer Science from Cornell University, a master's degree in Computer Science from Stanford University and a Ph.D. in Computer Science from Stanford University.
 

_seminars/2024-04-17.md

@@ -13,7 +13,7 @@ version: 1
 # - This is used to keep the iCal up to date.
 # - Increment the sequence each time the seminar file is updated.
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-sequence: 5
+sequence: 6
 
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 # Date and time of the seminar.
@@ -152,6 +152,14 @@ location:   "Kane 225 - Hybrid via Zoom"
 abstract: |
   Computing holds the promise of alleviating the negative impact of chronic disease and mental health disorders by scaling human effort over time and space. Four in ten adults in the US have two or more chronic illnesses, and one in five adults experiences a mental illness. The urgent need to improve chronic care calls for robust and reliable technology that is readily available to integrate into care-ecologies. In this talk, I will demonstrate how human-centered computing can leverage the generalizability of theoretical frameworks to build systems for asthma, PTSD, and diabetes. I will discuss the unique challenges in their context of care: for patients with asthma and diabetes including poor patient engagement and lack of continuity of care, while PTSD therapy is limited by over-reliance on patient self-reports and clinician intuition. I will present theory-driven technology interventions that address these issues and describe how AI could transform patient care and expedite clinician training. I will also discuss how ecological computing systems can lead to improved health and wellness in diverse populations. 
 
+  #### Schedule 
+  
+  11:45am - 12:15pm: Food and community socializing.
+
+  12:15pm - 1:15: Presentation with Q&A.  Available hybrid via Zoom.
+
+  1:15pm - 2:00pm: Student meeting and discussion with speaker, held in CSE2/Gates 371.
+
 bio: |
   Dr. Arriaga is a Human Computer Interaction (HCI) researcher in the School of Interactive Computing. Her current research is in mental health and chronic care management. She designs technology to increase patient engagement, support continuity of care, enhance clinical decision making and mediate patient-provider communication.  She has received NSF awards to develop computational systems to improve PTSD treatment and recovery (NSF Smart & Connected Health), and to incorporate AI into the clinical work-force (NSF Future of Work). She is also funded by the American Diabetes Association to create a diabetic foot ulcer care system.
  

_seminars/2024-05-01.md

@@ -13,7 +13,7 @@ version: 1
 # - This is used to keep the iCal up to date.
 # - Increment the sequence each time the seminar file is updated.
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-sequence: 3
+sequence: 4
 
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 # Date and time of the seminar.
@@ -153,6 +153,14 @@ abstract: |
 
   This seminar is co-organized with [UW CREATE](https://create.uw.edu/).
 
+  #### Schedule 
+  
+  11:45am - 12:15pm: Food and community socializing.
+
+  12:15pm - 1:15: Presentation with Q&A.  Available hybrid via Zoom.
+
+  1:15pm - 2:00pm: Student meeting and discussion with speaker, held in CSE2/Gates 371.
+
 bio: |
   Dr. Meryl Alper is an Associate Professor in the Department of Communication Studies and Affiliate Associate Professor in the Department of Communication Sciences and Disorders at Northeastern University. She researches the social, cultural, and health implications of communication technologies, with a focus on disability, digital media, and children and families’ technology use. Dr. Alper is the author of three books on the topic: Digital Youth with Disabilities (MIT Press, 2014), Giving Voice: Mobile Communication, Disability, and Inequality (MIT Press, 2017), and Kids Across the Spectrums: Growing Up Autistic in the Digital Age (MIT Press, 2023). In her research and teaching, Dr. Alper also draws on 20 years of professional experience in the children’s media industry as a researcher, strategist, and consultant with organizations such as Sesame Workshop, PBS KIDS, Nickelodeon, and Disney. Prior to joining the faculty at Northeastern, Dr. Alper earned a Ph.D. and M.A. from the Annenberg School for Communication and Journalism at the University of Southern California. She also holds a B.S. in Communication Studies and History from Northwestern University, as well as a certificate in Early Childhood Education from UCLA.