Research Focus
Our group focuses on the overlap between Network Science (the study of complex systems using network modeling
and graph mining methods), Neuroscience, and Machine Learning.
In a first research thrust, we study the brain using computational models and network analysis
methods, leveraging the rich datasets that are becoming available about the brain's connectome and activity.
In a second research thrust, we design novel machine learning architectures that are
neuro-inspired and that can learn in an unsupervised, adaptive and robust manner.
We believe that the solution to the problem of Artificial General Intelligence will be neuro-inspired.
International Conference on Neural Information Processing Systems (NeurIPS) 2023:
Neural Sculpting: Uncovering hierarchically modular task structure in neural networks through pruning and network analysis
with Shreyas Malakarjun Patil and Loizos Michael. NeurIPS, December 2023.
International Conference on Machine Learning (ICML) 2022:
NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks
with Mustafa Burak Gurbuz. In ICML 2022, July 2022. Code repo: Github link.
International Conference on Machine Learning (ICML) 2021:
PHEW: Constructing Sparse Networks that Learn Fast and Generalize Well without Training Data
with Shreyas Malakarjun Patil. In ICML 2021, July 2021. Code repo: Github link.
International Joint Conference on Artificial Intelligence (IJCAI) 2021:
Unsupervised Progressive Learning and the STAM Architecture
with James Smith, Cameron Taylor, and Seth Baer. In IJCAI 2021, August 2021. Code repo: Github link.
PhD students and PostDocs:
Former PhD and PostDoc advisees:
- Kamal Shadi (graduated in Dec'19, now at Decooda)
- Kaeser Md. Sabrin (graduated in Dec'18, now at LinkedIn)
- Payam Siyari (graduated in Dec'18, now at Uber)
- Ilias Foudalis (graduated in May'16, now at Relational AI)
- Saamer Akhshabi (Deceased in March 2014.
Farewell to Saamer)
- Aemen Lodhi (graduated in Dec'14, now at Facebook)
- Demetris Antoniades (PostDoc 2012-2014, now at the University of Cyprus)
- Partha Kanuparthy (graduated in Dec'12, now at Amazon)
- Amogh Dhamdhere (graduated in May'09, now at the CAIDA research center)
- Ravi Prasad (graduated in December'07, now at Cisco Systems)
- Ruomei Gao (co-advised with Ellen Zegura, graduated in August'07, now at Akamai)
- Manish Jain (graduated in December'06, now at Akamai)
- Yong Zhu (co-advised with Mostafa Ammar, graduated in August'06, now at Google)
- Qi He (co-advised with Mostafa Ammar, graduated in August'05, now at Apple)
-
EAGER:Using Network Analysis And Representational Geometry To Learn Structure-Function Relationship In Neural Networks,
Award Number:2039741. Principal Investigators: Eva Dyer and Constantine Dovrolis. Organization: Georgia Tech. NSF Organization:IIS. Start Date:01/01/2021. Award Amount:$199,999.00.
- National Science Foundation,
"CRCNS: Modeling and Manipulating Dynamic Network Activity in the Brain",
September 2018 to August 2021.
In
collaboration with Prof. Shella Keilholz from Emory University.
- DARPA,
Lifelong Learning Machines (L2M),
January 2018 to December 2019.
In collaboration with Dr. Zsolt Kira (Georgia Tech), Prof. Astrid Prinz (Emory) and Prof. Sarah Pallas (Georgia State Univ).
- National Science Foundation,
"NeTS: Protocol Stacks Design and Evolution: The Role of Layering and Modularity",
October 2013 to September 2016.
In
collaboration with Prof. Roch Guerin from Washington University, Saint Louis.
- DARPA,
Social Media in Strategic Communication,
February 2012 to February 2015.
In collaboration with Prof. Eric Gilbert and others at Georgia Tech.
- US Department of Energy (Office of Science),
Validation and quantification of uncertainty in coupled climate models using network analysis,
September 2011 to August 2014.
In collaboration with Prof. Annalisa Bracco from Georgia Tech (Atmospheric and Climate Sciences).
Some representative papers and projects:
Education
Teaching (recently)
Advisees
Funding and sponsors (recently)
Open-Source Code (recently)