February 2-3, 2021
Collocated with the Thirty-Fifth Conference on Artificial Intelligence (AAAI-21)
External site: https://aaaidc.github.io/dc2021/
The Twenty-Sixth AAAI/SIGAI Doctoral Consortium (DC) provides an opportunity for a group of Ph.D. students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. The eighteen students accepted to participate in this program will also participate in the AAAI-21 Poster Sessions on Thursday, February 4 (see accepted list below). All interested AAAI-21 student registrants are invited to observe the presentations.
The full Doctoral Consortium schedule is available at https://aaaidc.github.io/dc2021/schedule/.
AAAI and SIGAI gratefully acknowledge the generous grant from the National Science Foundation, which makes this program possible.
AAAI-21 Doctoral Consortium Accepted Papers
DC-79: AI for Social Good: Between My Research and the Real World
Zheyuan Ryan Shi
DC-118: Effective Clustering of scRNA-seq Data to Identify Biomarkers without User Input
Hussain A. Chowdhury
DC-127: Verification and Repair of Neural Networks
Dario Guidotti
DC-169: Towards Fair, Equitable, and Efficient Peer Review
Ivan Stelmakh
DC-200: Creating Interpretable Data-Driven Approaches for Remote Health Monitoring
Alireza Ghods
DC-246: Distributed Situation Awareness for Multi-Agent Mission in Dynamic En-vironments: A Case Study of Multi-UAVs Wildfires Searching
Sagir Muhammad Yusuf, Chris Baber
DC-260: On Learning Deep Models with Imbalanced Data Distribution
Puspita Majumdar, Richa Singh, Mayank Vatsa
DC-276: A Computational Approach to Sign Language Understanding
Tejaswini Ananthanarayana
DC-281: Artificial Intelligence and Machine Learning for Autonomous Agents that Learn to Plan and Operate in Unpredictable Dynamic Environments
Leonardo Lamanna
DC-304: How Human Centered AI Will Contribute Towards Intelligent Gaming Systems
Yilei Zeng
DC-311: Perception beyond Sensors under Uncertainty
Masha Itkina
DC-314: Robots that Help Humans Build Better Mental Models of Robots
Preeti Ramaraj
DC-317: Constraint-Driven Learning of Logic Programs
Rolf Morel
DC-318: Screening for Depressed Individuals by Using Multimodal Social Media Data
Paulo Mann, Aline Paes, Elton H. Matsushima
DC-340: Multi-Agent Reinforcement Learning for Decentralized Coalition Formation Games
Kshitija Taywade
DC-415: Transfer Learning of Engagement Recognition within Robot-Assisted Therapy for Children with Autism
Nazerke Rakhymbayeva, Anara Sandygulova
DC-423: Relational Learning to Capture the Dynamics and Sparsity of Knowledge Graphs
Mehrnoosh Mirtaheri
DC-429: Safety Assurance for Systems with Machine Learning Components
Chelsea Sidrane