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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
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The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Chen, F., Cao, L., Wu, D., Zhang, E., Wang, T., Jiang, X., Chen, J., Wu, H., Lin, S., Hou, Q., Zhu, J., Yang, J., Sawan, M., & Zhang, Y. (2025). Acoustic inspired brain-to-sentence decoder for logosyllabic language. Cyborg and Bionic Systems, 0257 (35 pages). External link
Chen, J., Wu, H., Tian, F., Hou, Q., Lin, S., Yang, J., & Sawan, M. (2024, May). A Low-Power Level-Crossing Analog-to-Spike Converter Intended for Neuromorphic Biomedical Applications [Paper]. IEEE International Symposium on Circuits and Systems (ISCAS 2024), Singapore, Singapore. External link
Chen, J., Wu, H., Eskandari, R., Liu, X., Lin, S., Hou, Q., Tian, F., Zou, W., Yang, J., & Sawan, M. (2024, April). A Neuron-Inspired 0.0032mm2−1.38μW/Ch Wireless Implantable Neural Interface with Direct Multiplexing Front-End and Event-Driven Spike Detection and Transmission [Paper]. IEEE Custom Integrated Circuits Conference (CICC 2024), Denver, CO, USA. External link
Chen, J., Liu, X., Wu, H., Tian, F., Zou, W., Katebi, M., Eskandari, R., Yang, J., & Sawan, M. (2023, October). A Clockless Robust Bionic Spike Detector for Implantable Brain-Computer Interfaces [Paper]. Biomedical Circuits and Systems Conference (BioCAS 2023), Toronto, ON, Canada (5 pages). External link
Chen, J., Wu, H., Liu, X., Eskandari, R., Tian, F., Zou, W., Fang, C., Yang, J., & Sawan, M. (2023, June). NeuroBMI: A New Neuromorphic Implantable Wireless Brain Machine Interface with A 0.48 µW Event-Driven Noise-Tolerant Spike Detector [Paper]. 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS 2023), Hangzhou, China (5 pages). External link
Chen, J., Wu, H., Yang, J., & Sawan, M. (2022, November). A 97 fJ/Conversion Neuron-ADC with Reconfigurable Sampling and Static Power Reduction [Paper]. Asia Pacific Conference on Circuits and Systems (APCCAS 2022), Shenzhen, China. External link
Eskandari, R., Katebi, M., Wu, H., Tan, Z., Mao, Y., Faezipour, M., Abdollah Mirbozorgi, S., & Sawan, M. (2025, May). Implantable Closed-loop Neuromodulation Platform Dedicated to Diabetes Diagnosis and Treatment [Paper]. IEEE International Symposium on Circuits and Systems (ISCAS 2025), London, United Kingdom. External link
Liu, X., Chen, J., Wu, H., Zou, W., Yang, J., & Sawan, M. (2025). An On-Chip Reconfigurable Front-end for Ultra-Low-Power RF Energy Harvesting. IEEE Transactions on Circuits & Systems II Express Briefs, 5 pages. External link
Liu, X., Zou, W., Wu, H., Chen, J., Yang, J., & Sawan, M. (2024, October). A Reconfigurable RF Energy Harvesting Front-end Interface for Biomedical Applications [Paper]. Biomedical Circuits and Systems Conference (BioCAS 2024), Xi'an, China (4 pages). External link
Mao, Y., Chen, J., Wu, H., Yang, J., Kuang, X., & Sawan, M. (2025, May). A 2.53 fJ/Conversion Low-Power Hybrid ADC with Level-Crossing Assisted Sparisty Adaptivity for Implantable Neural Interface [Paper]. International Symposium on Circuits and Systems (ISCAS 2025), London, United Kingdom (4 pages). External link
Shao, K., Tian, F., Wang, X., Zheng, J., Chen, J., He, J., Wu, H., Chen, J., Guan, X., Deng, Y., Tu, F., Yang, J., Sawan, M., Cheng, T. K.-T., & Tsui, C.-Y. (2025, March). SynDCIM: A Performance-Aware Digital Computing-in-Memory Compiler with Multi-Spec-Oriented Subcircuit Synthesis [Paper]. Design, Automation & Test in Europe Conference (DATE 2025), Lyon, France. External link
Tian, F., Chen, J., Shao, K., Liu, Z., Zheng, J., Wu, H., Fang, C., Wang, X., Shen, Z., Dong, P., Yao, Y., Wang, X., Yang, J., Sawan, M., Tsui, C.-Y., & Cheng, K.-T. (2025, April). E-NPU: A 34~126nJ/Class Event-Driven Adaptive Neural SoC with Signal-Dynamics-Aware Feature Clustering and Multi-Model In-Memory Inference/Training for Personalized Medical Wearables [Paper]. IEEE Custom Integrated Circuits Conference (CICC 2025), Boston, MA, USA. External link
Tarkhan, M., Wu, H., Ullah, F., & Sawan, M. (2025). A Flexible High-Accuracy Memristor Model Using Varactors. IEEE Access, 13, 217423 (14 pages). External link
Tian, F., Chen, J., Zheng, J., Wu, H., He, J., Wang, X., Fang, C., Yuan, Y., Yang, J., Sawan, M., Tsui, C.-Y., & Cheng, K.-T. (2024). BioPI: An Energy Efficient and Low-Latency Neuromorphic Pipelined System with Joint Design Optimizations of Sensor-Algorithm-Processor for Wearable Healthcare. IEEE transactions on circuits and systems for artificial intelligence., 1-17. External link
Tian, F., Wang, X., Chen, J., Zheng, J., Wu, H., Liu, X., Tu, F., Yang, J., Sawan, M., Tsui, C.-Y., & Cheng, K.-T. T. (2023, September). BIOS: A 40nm Bionic Sensor-defined 0.47pJ/SOP, 268.7TSOPs/W Configurable Spiking Neuron-in-Memory Processor for Wearable Healthcare [Paper]. 49th European Solid State Circuits Conference (ESSCIRC 2023), Lisbon, Portugal. External link
Wu, H., Tan, Z., Liu, X., Chen, J., Zou, W., Hou, Q., Lin, S., Mao, Y., Kuang, X., Yang, J., & Sawan, M. (2025, May). Efficient Self-Adaptive Pseudo-Resistor with Rapid Settling and High Linearity for Neurorecording Front-End Circuits [Paper]. IEEE International Symposium on Circuits and Systems (ISCAS 2025), London, United Kingdom. External link
Wu, H., Tan, Z., Liu, X., Chen, J., Zou, W., Hou, Q., Liu, S., Mao, Y., Kuang, X., Yang, J., & Sawan, M. (2025). Self-Adaptive Pseudo-Resistors Enabling Millisecond-Level Artifact Recovery and High-Linearity for Neural Recording Front-Ends. IEEE Transactions on Biomedical Circuits and Systems, PP, 12 pages. External link
Wu, H., Chen, J., Liu, X., Zou, W., Yang, J., & Sawan, M. (2023). An Energy-Efficient Small-Area Configurable Analog Front-End Interface for Diverse Biosignals Recording. IEEE Transactions on Biomedical Circuits and Systems, 17(4), 818-830. External link
Zou, W., Eskandari, R., Liu, X., Chen, J., Ye, Y., Wu, H., Yang, J., & Sawan, M. (2024, October). A 34 μW and 3.4 pJ/b IR-UWB Transmitter Featuring Spectrum Tunability for Brain-Machine Interfaces [Paper]. IEEE Biomedical Circuits and Systems Conference (BioCAS 2024), Xi"an, China. External link
