About
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An active researcher in the domain of Artificial Intelligence (AI) with focus on resolving the problems of link dynamics (such as Breakup Prediction, Link Prediction, Link Influence, etc.), and related problems in Social Network Analysis (SNA) such as Node Classification, Community Detection, Event-based Analysis, Information Diffusion, etc. Primarily, my approach involves the study and discovery of effective as well as efficient techniques targetted at resolving the aforementioned open problems in Artificial Intelligence. In this regard, my approach to research-problem resolution employs Deep Learning (DL) architecture(s) and/or technique(s) with respect to Deep Belief Networks (DBNs), Recurrent Neural Networks (RNNs), Recursive Neural Networks (RvNNs), and Convolutional Neural Networks (CNNs). Moreover, my approach encompasses nonlinear Machine Learning (ML) techniques such as K-Nearest Neighbor, K-Means, etc.; and tree-based ML techniques like Decision Tree, Random Forest, and XGBoost models.
Profile
Furthermore, I am a seasoned solutions and web/mobile developer with over 8 years of industry experience. A flexible, collaborative, and good multi-tasker who is self-motivated, committed, and target-driven.
- Fullname: Bonaventure Chidube Molokwu
- Birth Date: June 30
- Job: Assistant Professor, Sessional Instructor, and Researcher
- Website: bhevencious.github.io
- Email: bonaventure.molokwu[at]concordia.ca bcmolokwu[at]gmail.com
Skills
I can adapt swiftly to newer skills, and can manage time and other resources wisely without constant supervision.
