Research Areas in Computer Engineering

Trending Research Areas in Computer Engineering are listed below, we solve all your research issues by providing best answers. In computer engineering, there are several areas that are progressing in the contemporary years. But some of the regions are considered as popular. Below are few of the famous study regions in the domain of computer engineering:

  1. Embedded Systems: Concentrating on incorporation, microcontrollers, practical computing, and communication among software and hardware, it is approachable to model and create the embedded frameworks.
  2. Computer Architecture and Hardware: Involving GPUs, multicore processors, quantum computing, and particularized processors such as TPUs for AI, investigate novel computer infrastructures.
  3. VLSI Design (Very Large Scale Integration): Integrated circuits must be created in such a way by integrating thousands or millions of transistors in one chip, concentrating on regions such as FPGA advancement, nanotechnology, and ASIC structure.
  4. Networks and Communications: Aim to investigate procedures, network structures, 5G/6G technologies, network safety, Internet of Things (IoT), and wireless and mobile networks.
  5. Cybersecurity and Information Security: It is beneficial to examine the cybersecurity in IoT, safety in cloud computing, cryptography, safer computing models, and network safety.
  6. Signal Processing: Encompassing applications in audio processing, image and video processing, and telecommunications, aim to deal with analog or digital signal processing.
  7. Robotics and Automation: It is appreciable to model and progress robotic frameworks, encompassing sensors and actuators, control models, and incorporation of machine learning and AI.
  8. Machine Learning and AI Hardware: In this area, construct hardware such as neural network accelerators and energy-effective AI chips that helps in improvement for AI applications.
  9. Quantum Computing and Information: In this region, aim to explore quantum cryptography, quantum error correction, hardware-software interface in quantum computers and quantum techniques.
  10. Power-Efficient and Green Computing: Involving low-power electronics, renewable energy resources in computing, and sustainable data centers, it is better to model frameworks for energy effectiveness.
  11. Biomedical Engineering and Bioinformatics: Aim to implement policies of computer engineering to the biomedical domains, encompassing bioinformatics, medical imaging, and advancement of medicinal devices.
  12. Nanotechnology and Nanoelectronics: In computer engineering, examine the molecular electronics, nano-scale electronic elements, and applications of nanotechnology.
  13. Software Engineering: Even though there are more advancements with computer science, the progression of software models that have the ability to handle hardware devices is concentrated on the software engineering area within the computer engineering domain.
  14. Human-Computer Interaction (HCI): Mainly for different computing devices, it is better to create virtual reality (VR), user interfaces, augmented reality (AR), and user-experience (UX) optimization.
  15. Edge Computing: For applications such as automatic vehicles, smart cities, and IoT, research the decentralized processing of data at the edge of the network, close to the resource of data.
  16. Autonomous Vehicles and Intelligent Transportation: Involving decision-making techniques, sensor incorporation, and vehicle-to-vehicle interaction, it is approachable to investigate in systems that assist automated driving.

What are the emerging areas in research in computer science?

Numerous areas are rising in the field of computer science. From that, we list out various evolving research regions that are considered as significant as well as interesting:

  1. Quantum Computing: Realistic applications and techniques for quantum computing such as quantum machine learning and quantum cryptography are obtaining concentration over conceptual research.
  2. Explainable AI (XAI): Specifically, in vital applications such as finance and healthcare, to be clearer and more understandable there is an advancing requirement for AI frameworks, when AI becomes more predominant.
  3. Edge AI and Computing: In order to decrease delay and enhance performance, mainly in IoT applications, it is beneficial to approach processing AI workloads at the network edge.
  4. Blockchain Beyond Cryptocurrency: In regions such as digital identity authentication, supply chain management, and voting models, intend to investigate applications of blockchain technology.
  5. Augmented Reality (AR) and Virtual Reality (VR): For different applications, encompassing training, entertainment, academics, and healthcare, offer developments in AR/VR.
  6. Ethical AI and Algorithmic Fairness: The unfairness in AI techniques must be solved and it is appreciable to assure that they are ethical, objectivity, and unbiased.
  7. Cyber-Physical Systems (CPS): Aim to incorporate computational methods along with physical procedures, involving applications in Industry 4.0, smart cities, and automated vehicles.
  8. Human-AI Collaboration: In what way AI frameworks and humans can effectively cooperate should be investigated, improving human decision-making instead of substituting it.
  9. Neuromorphic Computing: Providing possible developments in performance and AI processing, it is advisable to model computer chips in such a way that imitate the design and processing capability of the human brain.
  10. Advanced Cybersecurity Techniques: The requirement for more complicated cybersecurity criterions such as AI-based safety approaches are increasing due to the development of cyber-attacks.
  11. Federated Learning: Among decentralized devices a machine learning method in which the procedures are skilled, helps in securing confidentiality and decreasing data centralization.
  12. Green Computing and Sustainability in IT: Concentrating on decreasing the ecological influence of computing innovations, it is beneficial to create energy-effective computing frameworks, data centers, and methods.
  13. Bioinformatics and Computational Biology: Specifically, for genomics, biotechnology, and genetics, concentrate on data analysis by combining computer science with biology.
  14. Autonomous Systems and Robotics: Encompassing swarm robotics, human-robot communication, and automatic model ethics, it is better to progress study in robotics.
  15. 5G and Beyond: It is appreciable to examine developed networking technologies, involving the advancement of 6G and its applications.
  16. AI for Social Good: Aim to implement AI in order to resolve significant social limitations such as academics, ecological security, humanitarian endeavour, and healthcare.
  17. Digital Twins: Mainly for simulation, exploration, and control, it is approachable to develop digital imitations of real-time frameworks.

Research Topics in Computer Engineering

How Can Data Privacy Be Addressed in Computer Science Research?

We assure that all your data are kept confidential. Generally, research means confidential we are in this field for past 18+ years all scholars details are secure with us. Some of the best thesis ideas in field of computer science are listed below.

  1. Dynamic circular cellular networks for adaptive smoothing of multi-dimensional signals
  2. D2D Communications Meet Mobile Edge Computing for Enhanced Computation Capacity in Cellular Networks
  3. Resource Allocation for Energy-Efficient Transmission in D2D Underlaid Cellular Networks
  4. CPICH power settings in irregular WCDMA macro cellular networks
  5. A Collaborative Hotspot Caching Design for 5G Cellular Network
  6. Radio resource allocation for cellular networks based on OFDMA with QoS guarantees
  7. A Framework for Automated Cellular Network Tuning With Reinforcement Learning
  8. On the optimal small cell deployment for energy-efficient heterogeneous cellular networks
  9. Cache- and Energy Harvesting-Enabled D2D Cellular Network: Modeling, Analysis and Optimization
  10. Influence-based channel reservation scheme for mobile cellular networks
  11. Optimal Base Station Sleeping Control in Energy Harvesting Heterogeneous Cellular Networks
  12. A low complexity resource scheduler for cooperative cellular networks
  13. Load Balancing for Cellular Networks Using Device-to-Device Communications
  14. A Token-Based Group Mutual Exclusion Algorithm for Cellular Wireless Networks
  15. D2D Communications-Assisted Traffic Offloading in Integrated Cellular-WiFi Networks
  16. Determination of optimal handover boundaries in a cellular network based on traffic distribution analysis of mobile measurement reports
  17. Performance Analysis and Optimization of Uplink Cellular Networks with Flexible Frame Structure
  18. Location management strategies for mobile cellular networks of 3rd generation
  19. Spiral wave patterns in two-dimensional computational verb cellular networks
  20. A Dynamic Reservation and Call Admission Control Policy with HMM for Multimedia Cellular Networks