Presentations

Oral Presentations

1. S. Biswas, C. O. Ayna, S. Z. Gurbuz and A. C. Gurbuz, "Complex SincNet for More Interpretable Radar Based Activity Recognition," 2023 IEEE Radar Conference (RadarConf23), San Antonio, TX, USA, 2023, pp. 1-6, doi: 10.1109/RadarConf2351548.2023.10149682.

2. S. Biswas, B. Bartlett, J. E. Ball and A. C. Gurbuz, "Classification of Traffic Signaling Motion in Automotive Applications Using FMCW Radar," 2023 IEEE Radar Conference (RadarConf23), San Antonio, TX, USA, 2023, pp. 1-6, doi: 10.1109/RadarConf2351548.2023.10149728.

3. S. Biswas and A. C. Gurbuz, "Deep Learning Based High-Resolution Frequency Estimation for Sparse Radar Range Profiles," 2024 IEEE Radar Conference (RadarConf24), Denver, CO, USA, 2024, pp. 1-6, doi: 10.1109/RadarConf2458775.2024.10548421.

4. A. Dahal, S. Biswas, S. Z. Gurbuz and A. C. Gurbuz, "Comparison Between Wi-Fi-CSI and Radar-Based HAR," 2024 IEEE Radar Conference (RadarConf24), Denver, CO, USA, 2024, pp. 1-6, doi: 10.1109/RadarConf2458775.2024.10548515.

5. S. Biswas, “Angular Subspace Projection for Radar-based Multi-target Classification”, ECE Graduate Research Symposium Fall 2022.

6. S. Biswas, “Boosting Multi-Target Recognition Performance with MIMO Radar-based Angular Subspace Projection and Multi-View DNN”, Mississippi State Graduate Research Symposium Fall 2022.

7. S. Biswas, “CV-SincNet: Learning Complex Sinc Filters from Raw Radar Data for Computationally Efficient Human Motion Recognition”, Mississippi State Graduate Research Symposium Fall 2023.

8. S. Biswas, “HRSpecNET: Deep Learning-Based High-Resolution Time Frequency Analysis”, Mississippi State Graduate Research Symposium Fall 2024.

9. S. Biswas, "Optimization of Electric Vehicle Charging to Shave Peak Load for Integration in Smart Grid", 2020 IEEE Region 10 Symposium (TENSYMP).