Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
Yaqoob Ansari
Affiliation
Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Ar-Rayyan, Qatar
Topic
Wireless Networks,3D Planning,Access Points,Advanced Machine Learning,Artificial Neural Network,Auction,CPLEX Solver,Communication Constraints,Communication Range,Convolutional Neural Network,Convolutional Neural Network Model,Data Augmentation,Deep Convolutional Neural Network,Deep Learning,Distribution Of Tasks,Diverse Capabilities,Enhancing Communication,Euclidean Space,General Properties,Graph Neural Networks,Ground Plane,Incremental Update,Indoor Wireless,Learning Rate,Limited Communication,Local Point,Machine Learning,Makespan,Market-based Approach,Mean Absolute Error,Mission Planning,Model Architecture,Multi-agent Systems,Multi-robot Task Allocation,Nature Of The Task,Neural Network,Number Of Agents,Numerical Data,Radio Propagation,Ray-tracing Simulations,Received Signal Strength,Regression Problem,Rescue Missions,Robotic Tasks,Scheduling Algorithm,Search Area,Shared Representation,Signal Strength,Spatial Allocation,Task Allocation,
Biography
Yaqoob Ansari is currently pursuing the bachelor’s degree in electrical and computer engineering with Texas A&M University in Qatar. Prior to his studies with Texas A&M, he was enrolled with the Computer Science Program, Carnegie Mellon University in Qatar, for two years. His academic pursuits are characterized by a strong emphasis on machine learning, deep learning, and computer vision. His research primarily explores innovative applications of these technologies within the field of engineering. The unique combination of his studies in both computer science and engineering provides a robust foundation for his research endeavors, positioning him well to contribute to advancements in interdisciplinary technology solutions.