Jamming Energy Allocation in Training-Based Multiple Access Systems. - Hamed Pezeshki; Xiangyun Zhou 001; Behrouz Maham (IEEE Commun. Lett., 2013)

Anywhere decoding: Low-overhead basestation cooperation for interference- and fading-limited wireless environments. - Hamed Pezeshki; J. Nicholas Laneman (Allerton, 2015)

Extraction of spiculated parts of mammogram tumors to improve accuracy of classification. - Hamed Pezeshki; Maryam Rastgarpour; Arash Sharifi; Samaneh Yazdani (Multim. Tools Appl., 2019)

Anywhere Decoding: Low-Overhead Uplink Interference Management for Wireless Networks. - Hamed Pezeshki; Masoumeh Sadeghi; Martin Haenggi; J. Nicholas Laneman (IEEE Trans. Wirel. Commun., 2020)

Mass classification of mammograms using fractal dimensions and statistical features. - Hamed Pezeshki; Maryam Rastgarpour; Arash Sharifi; Samaneh Yazdani (Multidimens. Syst. Signal Process., 2021)

Long Short-Term Memory Based Millimeter Wave Beam Change Prediction via Real-World Data. - Qiaoyu Li; Arumugam Kannan; Himanshu Joshi; Taesang Yoo; Philip Sisk; Mahmoud Taherzadeh Boroujeni; Hamed Pezeshki; Tao Luo 009 (GLOBECOM (Workshops), 2022)

Beyond Codebook-Based Analog Beamforming at mmWave: Compressed Sensing and Machine Learning Methods. - Hamed Pezeshki; Fabio Valerio Massoli; Arash Behboodi; Taesang Yoo; Arumugam Kannan; Mahmoud Taherzadeh Boroujeni; Qiaoyu Li; Tao Luo 009; Joseph B. Soriaga (GLOBECOM, 2022)

Breast tumor segmentation in digital mammograms using spiculated regions. - Hamed Pezeshki (Biomed. Signal Process. Control., 2022)

Position Aided Beam Prediction in the Real World: How Useful GPS Locations Actually Are? - João Morais; Arash Behboodi; Hamed Pezeshki; Ahmed Alkhateeb (CoRR, 2022)

Multi-Modal Beam Prediction Challenge 2022: Towards Generalization. - Gouranga Charan; Umut Demirhan; João Morais; Arash Behboodi; Hamed Pezeshki; Ahmed Alkhateeb (CoRR, 2022)

Position-Aided Beam Prediction in the Real World: How Useful GPS Locations Actually are? - João Morais; Arash Bchboodi; Hamed Pezeshki; Ahmed Alkhateeb (ICC, 2023)

Machine Learning Based Time Domain Millimeter-Wave Beam Prediction for 5G-Advanced and Beyond: Design, Analysis, and Over-The-Air Experiments. - Qiaoyu Li; Philip Sisk; Arumugam Kannan; Taesang Yoo; Tao Luo 009; Gaurav Shah; Badri Manjunath; Chanaka Samarathungage; Mahmoud Taherzadeh Boroujeni; Hamed Pezeshki; Himanshu Joshi (IEEE J. Sel. Areas Commun., 2023)

Artificial Intelligence and Machine Learning Based Beam Prediction in 5G-Advanced and 6G Communications. - Qiaoyu Li; Philip Sisk; Arumugam Kannan; Tao Luo 009; Taesang Yoo; Hamed Pezeshki; Mahmoud Taherzadeh Boroujeni (IEEECONF, 2024)