Project Forum 2025 – Summary Report
Written by Song Jianan, MSc student of the Faculty
The forum can be rewatched here: https://www.inf.elte.hu/visszanezheto-projekt-forum-20
The Project Forum 2025, organized by the Faculty of Informatics at ELTE, provided an overview of the research directions, semester-long projects, and collaboration opportunities available to students for Spring 2025. Although diverse in scope, all projects shared a common purpose: integrating students into real research environments and preparing them for work in data-driven, AI-centric, or system engineering fields. Below is a structured summary of the projects, key themes, and my personal reflections.
1.General Impressions of the Event
The forum was presented as an open, interactive session where project supervisors briefly introduced their topics. The atmosphere was practical and research-oriented: every presenter focused on the expected student workload, recommended background knowledge, and possible long-term outcomes such as thesis work, publications, or industrial collaboration.
Across all presentations, I observed three strong clusters of research:
- Computational Neuroscience & Cognitive-inspired AI
- Robotics, Autonomous Systems & Human–Robot Interaction
- AI, NLP, and Data-centric Applied Research
This segmentation made it easier for students to identify which fields best matched their interests or skill levels.
2. Project Category Summaries
- Computational Neuroscience & Cognitive-inspired AI
My key takeaway: This research line is ideal for students who want to bridge neuroscience and computer science. It requires mathematical maturity and an interest in biological processes but provides exposure to rapidly growing research areas like neuromorphic computing.
- Robotics, Human–Robot Interaction & Autonomous Systems
This was the most practically oriented section of the forum. My impression:
These robotics topics are ideal for students wanting hands-on experience. They combine machine learning, computer vision, and system engineering.
- AI, NLP & Data-Driven Applied Research
This category included multiple projects applying data science methods to real problems. Overall impression: These projects are suited for students aiming at a career in data science, software engineering, or applied machine learning. They require less hardware expertise than robotics projects but encourage more experimentation with datasets and modeling techniques.
3. Personal Observations and Reflections
Strengths of the Forum
Clear, compact presentations helped students quickly understand project expectations. Breadth of topics ensured that students from theoretical, applied, or interdisciplinary backgrounds could find relevant work. Openness of supervisors allowed students to ask realistic questions about workload, tools, and difficulty.
What I Found Most Interesting
The projects on Spiking Neural Networks and Autonomous Driving Perception (ELTECar) stood out to me. SNNs represent one of the most future-oriented directions in AI, especially for low power or event-based computing. ELTECar provides a real platform with sensors, ROS2 pipelines, and computer vision challenges — a rare opportunity for students to work on autonomous vehicle perception at the university level.
4. Conclusion
The Project Forum 2025 effectively showcased the research and project opportunities available for the upcoming semester. It highlighted ELTE’s strengths in computational neuroscience, robotics, and applied AI. For students, the event was both informative and motivating — offering a clear picture of how academic study connects to research problems and emerging technologies.