Dear Research Community,

Leslie Shor (Associate Dean, Engineering) and Gerry Altmann (Director, Institute for the Brain and Cognitive Sciences) have organized a Meet & Speak that will bring together researchers from CLAS and Engineering with an interest in computational modeling / machine learning / and AI. The aim is for the different communities across the colleges to better understand the research that we are each engaged in. The meeting will offer an opportunity to foster greater cross-college discourse and collaboration, and may serve as a foundation for greater university investment in computational modeling. The Meet & Speak is scheduled for May 6th, 12pm-3pm on Zoom. You will be able to join the meeting by visiting this webpage.

Attendees will be able to submit questions during each talk using the Q&A feature. Our hosts will select questions during/after the talk. If your question is selected, the host will temporarily turn on your microphone and call on you to ask your question directly.

There will be 12 speakers, each taking up a 12-minute slot including questions (speakers have been asked to limit their talks to 8-9 minutes). These speakers are a sample of faculty with interests in computational modeling. We could not include all the faculty with such interests and our apologies if we did not include you - one purpose of this meeting is to use this as a starting point for identifying researchers at UConn who share these computational interests.

Speakers (and relevant research interests):

1. Gerry Altmann (Director, IBACS; Psychological Sciences): Language and event comprehension in Recurrent Neural Networks.

2. Jim Magnuson (Psychological Sciences): Bridging the gaps between automatic speech recognition and human speech recognition.

3. Whit Tabor (Psychological Sciences): Language processing within a Dynamical Systems approach to Cognition.

4. Jay Rueckl (Psychological Sciences): Connectionist modeling of literacy development.

5. Ed Large (Psychological Sciences): Oscillator models of rhythm and music perception.

6. Ian Stevenson (Psychology): Modeling neural dynamics and information encoding within the human brain.

7. Monty Escabi (Biomedical Engineering): Algorithms for modeling how neurons process complex sounds.

8. Sabato Santaniello (Biomedical Engineering): Biophysically-principled modeling for brain disorders and neuromodulation

9. Derek Aguiar (Computer Science & Engineering): Probabilistic machine learning models to better understand genomics and genetics data applied to complex disease.

10. Jinbo Bi (Associate Head, Computer Science & Engineering): Machine learning and Data mining for Bioinformatics, Medical informatics, and Drug discovery

11. Ranjan Srivastava (Head of Chemical & Biomolecular Engineering): Mathematical models of biological systems.

12. Caiwen Ding (Computer Science & Engineering): Machine Learning & Deep Neural Networks

Further details (including schedule of talks, with titles and abstrac