| 2025 | WCNC | Performance Evaluation of MU-MIMO Systems with Multi-Antenna Users for Different Precoding Strategies. | Joo Paulo P. G. Marques, Kiril Danilchenko, Catherine Rosenberg |
| 2023 | FedCSIS | Online Learning Framework for Radio Link Failure Prediction in FANETs. | Kiril Danilchenko, Nir Lazmi, Michael Segal |
| 2023 | WiMob | Reinforcement Learning Based Routing For Deadline-Driven Wireless Communication. | Kiril Danilchenko, Gil Kedar, Michael Segal |
| 2022 | ICWSM | Opinion Spam Detection: A New Approach Using Machine Learning and Network-Based Algorithms. | Kiril Danilchenko, Michael Segal, Dan Vilenchik |
| 2022 | IWCMC | TDMA Frame Length Minimization by Deep Learning for Swarm Communication. | Kiril Danilchenko, Michael Segal |
| 2021 | FedCSIS | An Efficient Connected Swarm Deployment via Deep Learning. | Kiril Danilchenko, Michael Segal |
| 2021 | IWCMC | Transmission Power Control using Deep Neural Networks in TDMA-based Ad-hoc Network Clusters. | Rina Azoulay, Kiril Danilchenko, Yoram Haddad, Shulamit Reches |
| 2020 | Algosensors | Covering Users by a Connected Swarm Efficiently. | Kiril Danilchenko, Michael Segal, Zeev Nutov |
| 2020 | Mobisys | Connected Ad-Hoc swarm of drones. | Kiril Danilchenko, Michael Segal |