Sajjad Baghaee

Dr. Sajjad Baghaee (Alper Alioğlu) is a senior researcher at METU, PI at JeoIT and CTO at FreshData. His work is on adaptive, resource-efficient communication for wireless and constrained networks — systems that have to stay timely and reliable inside an energy budget — across the Internet of Things, networking and learning-based control.

He combines analytical modelling with implementation, favouring experimentally validated results over simulation alone — packet-level simulation in ns-3, emulation through Mininet-WiFi, and embedded IoT platforms deployed in operational environments.

Within the ERC-funded GO-SPACE project at METU, under the supervision of Prof. Dr. Elif Uysal, he works on goal-oriented communication, reinforcement-learning-based flow control and adaptive scheduling for disruption-prone networks. A central theme is putting intelligence inside the protocol, so it can balance freshness, congestion, energy and reliability as conditions change: given limited energy, bandwidth and time, which piece of information actually changes what the receiver will do next?

Current work in that project applies constrained reinforcement learning to relay-side bundle management and flow control for deep-space links, in Goal-Oriented Bundle Management and Flow Control for Deep-Space Communications via Reinforcement Learning, accepted for the 77th International Astronautical Congress (IAC 2026).

That thread runs wider than one project: Age of Information, LoRa/LoRaWAN systems, edge intelligence, and future 6G and non-terrestrial networks. What holds in constrained space environments — cross-layer optimisation, adaptive reliability — carries back to resilient terrestrial systems.

Alongside networking, a substantial strand of the work is learning and control: reinforcement and meta-reinforcement learning for building climate control, surrogate simulators that shorten training, and device-free wireless sensing from Wi-Fi channel state information.

The five research areas

Since 2018 he has worked at JeoIT as a Senior IoT Engineer and later as Principal Investigator, leading projects involving adaptive communication protocols, embedded firmware, hardware integration and wireless sensing. As CTO at FreshData Technologies he led the development of an AoI-aware smart-grid monitoring device for electricity distribution: hardware design, embedded software, adaptive communication and pilot deployment in transformer substations, eventually becoming a commercial product.

A major strand of recent work is LoRa-based wireless sensing for smart environments and digital twins. As PI of Work Package P9 in the TÜBİTAK 1004 SUIT Platform project he led SensorBox, a low-power environmental sensing platform integrating heterogeneous sensors, LoRa, edge processing and MQTT pipelines, deployed at the Architectural Engineering and Technology Department of Delft University of Technology for occupancy-aware analytics and digital-twin-driven monitoring.

His contributions also include LoRaFRESH®, a duty-cycle-aware and freshness-driven communication framework for LoRa/LoRaWAN under strict energy and regulatory constraints, examining how sensing frequency, packet scheduling and lightweight reliability affect freshness, congestion and energy in real deployments.

Projects and deployments

He received his Ph.D. in Electrical and Electronics Engineering from METU in 2023 with a dissertation titled Age of Information Based Flow Control in Communication Networks, on AoI-aware protocols and adaptive reliability mechanisms that treat freshness as a system-level optimisation objective. His M.Sc., also from METU, was on Identification and Localization on a Wireless Magnetic Sensor Network.

Education record Full experience

He is the author and co-author of peer-reviewed publications in networking, communication systems, IoT, control and sensing; contributed the chapter Age of Information in Practice to the Cambridge University Press volume Age of Information: Foundations and Applications; and is a named inventor on the A³L-FEC patent application.