Dr. Paresh Saxena is an Associate Professor in the Dpt. of Computer Science & Information Systems, BITS-Pilani, Hyderabad, India. He is currently leading a project MUT-DROCO (Multipath Networking Testbed for Drone Communications) funded by DST-SERB, Govt. of India and a project NANCY (Neural Adaptive Network Coding for video transmission over wireless networks) funded by TCS, India. Previously, he has been involved as a work package leader in two European Space Agency (ESA) funded projects: SatNetCode and HENCSAT, along with a work package member in European H2020 funded project Geo-Vision. He was a member of European COST action IC1104 from 2013-2016 and worked on the project funded by MITACS, Canada in 2008. He has been a visiting researcher in SFU, Vancouver, Canada in 2008 and Telecom ParisTech, Paris in 2010. During his PhD from UAB, Barcelona, Spain, he was awarded UAB Doctoral Fellowship Grant (P.I.F) from 2011-2015. Post-PhD, he was fortunate to spend a few years at AnsuR Tech., Oslo, Norway as a Senior researcher from 2015-2018. Prior to his graduation, he was awarded with a National Talent Search Examination (NTSE) scholarship, India where he scored overall 11th rank in the country. His primary research focus is on the design and implementation of reliable and robust data transfer protocols for Non-terrestrial networks.

Email: psaxena@hyderabad.bits-pilani.ac.in   

Ph.D. Students

Mandan Naresh
Mandan Naresh received the B. Tech and M. Tech degrees in Computer Science and Engineering in 2012 and 2014, respectively. He has been working as a Lecturer in Computer Science department before starting his PhD studies. His research interests are in the field of machine learning techniques for video distribution.

Pattiwar Shravan Kumar
Shravan Pattiwar received the B.Tech and M.Tech degrees in Computer Science and Engineering from Jawaharlal Nehru University, Hyderabad, in 2011 and 2017, respectively. He has been working in software industry for several years before starting his PhD studies. His research interests are in multipath networking technologies.

Chavali Lalitha
Chavali Lalitha received the B. Tech degree in Information Technology from Jawaharlal Nehru University, Hyderabad in 2017 and the M. Tech degree in Computer Science from Osmania University in 2019. Her research interests are primarliy in the field machine learning techniques for non-terrestrial networking and communications.

Nida Fatima
Nida Fatima received the B. Tech and M. Tech degrees in Computer Science and Engineering from Jawaharlal Nehru University, Hyderabad, in 2012 and 2015, respectively. She has been a Lecturer in Computer Science Dept., since 2015. Her research interests are primarily in the field of integrated satellite-terrestrial networking, software defined networking and Internet of Things.

Chillara Anil Kuma
Chillara Anil Kumar received the B. E degree in Instrumentation and Electronics from Bangalore University in 2005 and the M. Tech degree in Information Technology from VTU, 2009. He has several years of work experience as an IT consultant before joining his PhD program in 2020. His research interests are primarily in the field of ML integrated data security algorithms for I/O devices.

S Shashank
S Shashank received a B. Tech degree in Electronics and Communication Engineering from Jawaharlal Nehru Technological University, Hyderabad, in 2018 and an M. E degree in Electronics and Communication Engineering from Osmania University in 2021. His research interests are primarily in the field of RF Communications and Signal Processing.

Krishna Maitreya Jaldu
Krishna Maitreya Jaldu earned his B.Tech degree in Electronics and Communication Engineering from Vel Tech University in 2024. His research interests encompass IoT and computer vision for detection applications.

Undergraduate Researchers

• Thesis Student: Shivaank Agarwal, Thesis Topic: Computer vision and image processing for plastic waste classification, Co-Supervisor: Prof. Ravindra Gudi, IIT Mumbai.
  
• Thesis Student: Krut Patel, Thesis Topic: Enabling Analytics Queries on Petabyte Scale Data, Co-Supervisor: Dr. Bhargav Gulavani, Microsoft Research Lab India, Bangalore.
  
• Project Students: Vaibhav Yadav, Gokul Kumar, Ujjwal Raizada, Pranjal Gupta (Multipath Networking Protocols), Simran sandhu and Vamsi Nallapareddy (Reinforcement Learning for Video) and Gotam Dahiya (Drones Hardware).
  

• [J16] Krishna, N. V., Chintalapati, R., Saxena, P., Soumya, J. Enhancing Functional Coverage Closure in Network-On-Chip Systems with Reinforcement Learning. IEEE Embedded Systems Letters, 2026.
• [J15] Pattiwar, S. K., Saxena, P., Alay, Ö. PRISM: Proximal Policy Optimization with Deep Reinforcement Learning for Intelligent Scheduling in Multipath QUIC under Heterogeneous and Hybrid 5G/B5G–Satellite Networks. Computer Communications, Elsevier, 2026.
• [J14] Maganti, P., Saxena, P., Maiti, R. R. Discovering Attack Signature and Its Travel Path using Graphical Model in CPS: A Case Study. ACM Transactions on Cyber-Physical Systems, 2025.
• [J13] Kumar, P. S., Saxena, P., Alay, Ö. Next-generation DRL empowered actor-critic schedulers for multipath QUIC in 5G vehicular IoT. Internet of Things, Elsevier, 2025.
• [J12] Mandan, N., Saxena, P., Gupta, M. DRL Empowered On-policy and Off-policy ABR for 5G Mobile Ultra-HD Video Delivery. Mobile Networks and Applications, Springer, 2025.
• [J11] Chillara, A. K., Saxena, P., Maiti, R. R. USB-GATE: USB-based GAN-augmented transformer reinforced defense framework for adversarial keystroke injection attacks. International Journal of Information Security, Springer, 2025.
• [J10] Fatima, N., Saxena, P., Giambene, G. Deep reinforcement learning based computation offloading for xURLLC services in UAV-assisted MEC systems. Wireless Networks, Springer, 2024.
• [J9] Chillara, A. K., Saxena, P., Maiti, R. R. Deceiving supervised machine learning models via adversarial data poisoning attacks. International Journal of Information Security, 2024.
• [J8] Marisetty, H. V., Fatima, N., Gupta, M., Saxena, P. Resource scheduling and distributed learning in IoT edge computing. Internet of Things, Elsevier, 2024.
• [J7] Chavali, L., Krishnan, A., Saxena, P., et al. Off-policy actor-critic deep reinforcement learning methods for alert prioritization in intrusion detection systems. Computers & Security, Elsevier, 2024.
• [J6] Fatima, N., Saxena, P., Giambene, G. Integration of MEC with UAVs: Current techniques and research directions. Physical Communication, Elsevier, 2022.
• [J5] Agarwal, S., Gudi, R., Saxena, P. Image classification approaches for segregation of plastic waste. Transactions of the Indian National Academy of Engineering, 2022.
• [J4] Naresh, M., Das, V., Saxena, P., Gupta, M. Deep reinforcement learning-based QoE-aware actor-learner architectures for video streaming in IoT environments. Computing, Springer, 2022.
• [J3] Saxena, P., Vázquez-Castro, M. Á. Dare: DOF-aided random encoding for network coding over lossy line networks. IEEE Communications Letters, 2015.
• [J2] Saxena, P., Vázquez-Castro, M. Á. Link-layer systematic random network coding for DVB-S2X/RCS. IEEE Communications Letters, 2015.
• [J1] Pimentel-Niño, M. A., Saxena, P., Vázquez-Castro, M. Á. Reliable adaptive video streaming driven by perceptual semantics. The Scientific World Journal, 2015.

• [C20] Shashank, S., Narayane, V. B., Saxena, P., Baheti, A. Design of Multiband Frequency-Modulated GPS Jamming Waveform. 22nd European Radar Conference (EuRAD), 2025, IEEE.
• [C19] Pattiwar, S. K., Saxena, P., Alay, Ö., et al. Performance Analysis of Multipath QUIC Schedulers for Video Streaming. IFIP International Conference on Network and Parallel Computing (NPC), 2025, IFIP.
• [C18] Chavali, L., Saxena, P. Multi-critic Deep Reinforcement Learning for Alert Prioritization. International Conference on Advanced Information Networking and Applications (AINA), 38th Edition, 2025, Springer.
• [C17] Shashank, S., Narayane, V. B., Saxena, P., Baheti, A. Direction Estimation of a Jamming Signal Using an Optimized Direction-Finding Algorithm. IEEE Microwave, Antennas, and Propagation Conference (MAPCON), 2025, IEEE.
• [C16] Pattiwar, S. K., Saxena, P., Alay, Ö., Griwodz, C., et al. Impact of Latency on User Experience in Immersive Teleoperation. IEEE Smart World Congress (SWC), 2025, IEEE.
• [C15] Fatima, N., Saxena, P., Giambene, G. Computation Offloading in NTN-empowered MEC using Multi-agent Distributed Deep Reinforcement Learning. IEEE Global Communications Conference (GLOBECOM), 2024, IEEE.
• [C14] Kumar, S. P., Saxena, P., Alay, Ö. DEAR: DRL empowered actor-critic scheduler for multipath QUIC under 5G/B5G hybrid networks. International Conference on Advanced Information Networking and Applications (AINA), 38th Edition, 2024, Springer.
• [C13] Naresh, M., Saxena, P., Gupta, M. GRAAB: Gradient Sharing A3C for Adaptive Bitrate Streaming. International Conference on Information Networking (ICOIN), 2024, IEEE.
• [C12] Chavali, L., Saxena, P., Mitra, B. Knowledge-empowered DRL for alert prioritization in IDS. International Conference on Advanced Information Networking and Applications (AINA), 38th Edition, Springer.
• [C11] Naresh, M., Saxena, P., Gupta, M. PPO-ABR: Proximal Policy Optimization based DRL for Adaptive Bitrate Streaming. International Wireless Communications and Mobile Computing Conference (IWCMC), 2023, IEEE.
• [C10] Naresh, M., Saxena, P., Gupta, M. Deep Reinforcement Learning with Importance Weighted A3C for QoE Enhancement in Video Delivery Services. IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2023, IEEE.
• [C9] Kota, S. et al. INGR Roadmap Satellite Chapter. IEEE Future Networks World Forum (FNWF), 2023, IEEE.
• [C8] Kumar, S. P., Saxena, P., Fatima, N. Performance Analysis of Multipath Transport Layer Schedulers under 5G/B5G Hybrid Networks. 14th International Conference on COMmunication Systems & NETworkS (COMSNETS), 2022, IEEE.
• [C7] Naresh, M., Saxena, P., Gupta, M. SAC-ABR: Soft Actor-Critic based Deep Reinforcement Learning for Adaptive Bitrate Streaming. 14th International Conference on COMmunication Systems & NETworkS (COMSNETS), 2022, IEEE.
• [C6] Chavali, L., Gupta, T., Saxena, P. SAC-AP: Soft Actor-Critic based DRL for Alert Prioritization. IEEE Congress on Evolutionary Computation (CEC), 2022, IEEE.
• [C5] Vázquez-Castro, M. Á., Saxena, P. Network Coding over Satellite: From Theory to Design and Performance. International Conference on Wireless and Satellite Systems (WSS), 2015, Springer.
• [C4] Saxena, P., Vázquez-Castro, M. Á. Network Coded Multicast and Multi-unicast over Satellite. International Conference on Advances in Satellite and Space Communication (SPACOMM), 2015, Springer.
• [C3] Saxena, P., Vázquez-Castro, M. Á. Network Coding Advantage over MDS Codes for Multimedia Transmission. International Conference on Personal Satellite Services (PSATS), 2013, Springer.
• [C2] Pimentel-Niño, M. A., Saxena, P., Vázquez-Castro, M. Á. QoE-driven Adaptive Video with Network Coding. 31st AIAA International Communications Satellite Systems Conference (ICSSC), 2013, AIAA.
• [C1] Saxena, P., Vázquez-Castro, M. Á. Interference-free Regions with Han-Kobayashi Scheme. 8th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2012, IEEE.

• [T1] Adamson, B. et al. RFC 8406: Taxonomy of Coding Techniques for Efficient Network Communications, IETF, 2018.
• [T2] Adamson, B. et al. Taxonomy of Coding Techniques for Efficient Network Communications (Internet Draft), 2018.
• [T3] Adamson, B. et al. Network Coding Taxonomy (Internet Draft), IRTF NWCRG, 2017.
• [T4] Bilbao, J. et al. NWCRG Internet-Draft (Informational), INRIA, 2018.
• [T5] Adamson, B. et al. Taxonomy of coding techniques for efficient network communications (tech report), 2018.