Helsinki ICT Research Day
When
Where
Schedule
Come join us on Helsinki ICT Research Day! Join your fellow researchers from the Aalto University Department of Computer Science, Department of Information and Communications Engineering, and the University of Helsinki Department of Computer Science.
Our early career researchers will provide a 5-minute-pitch about their research. Below is the order in which they will appear:
| Order | Name |
| 1 | Christian Guckelsberger |
| 2 | Juhi Kulshrestha |
| 3 | Suhas Thejaswi |
| 4 | Sebastian Szyller |
| 5 | Qi Chen |
| 6 | Mohammad Vali |
| 7 | Haoye Tian |
| 8 | Niklas Halonen |
| 9 | Aakash Ravindra Shinde |
| 10 | Raphael Weidhaas |
| 11 | Verena Distler |
| Research Software Engineering@UH | Practical Computing Support for Modern Research | |
| Aalto Scientific Computing | Aalto Scientific Computing: tools and support for your research. | |
| 1 | Satyam Singh | Computational Geometry |
| 2 | Chandra Mohapatra | Optimal Union Probability Interval Is NP-Hard |
| 3 | Nana Reinikainen | Evaluating REST API Test Generation Strategies Using Log Coverage |
| 4 | Linzh Zhao | On Optimal Hyperparameters for Differentially Private Deep Transfer Learning |
| 5 | Gauri Pradhan | Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy |
| 6 | Gizem Akman | Privacy-Preserving Determination of Fair Meeting Point |
| 7 | Sanish Gurung | PQC Multi-Party Key Exchange (MP-KEX) |
| 8 | Haoye Tian | Trustworthy LLM-based Software Maintenance |
| 9 | Ana Paula Gonzalez Torres | AI the Brussels way: Simulating the regulatory simplification agenda |
| 10 | Niki Pennanen | Human Perception of AI Creativity |
| 11 | Kate Hahn-Madole | Human–LLM Interaction at Scale: Evidence from Cross-Platform Conversational Data |
| 12 | Henrik Lassila | Aalto Good Life Lab Research |
| 13 | Anh Duong Nguyen | Community Detection and Analysis of Empirical Networks: The case of Human-Computer Interaction Researchers. |
| 14 | Nam Hee Kim | A VR Bot That Plays Like Us |
| 15 | Yunhao Yuan | Mental Health Impacts of AI Companions: Triangulating Social Media Quasi-Experiments, User Perspectives, and Relational Lens |
| 16 | Yajing Wang | Lonely individuals show distinct patterns of social media engagement |
| 17 | Giulio Jacucci | Designing for Meaningful Agency in AI-Driven XR |
| 18 | Ying Song | Multimodal anomaly detection in microservice systems |
| 19 | Mohammad Belal | Breadth vs. depth in online engagement: Evidence from large-scale session-level web traces data |
| 20 | Carine Fabritius | Intangible Forest Heritage in the Interactive User-Centered Digital Art Experience |
| 21 | Shreyas Giridhar | In-the-Loop Training for Machine Learning Sub-Grid-Scale Models |
| 22 | Jinbin Zhang | DynaSpec: Context-aware Dynamic Speculative Sampling for Large-Vocabulary Language Models |
| 23 | Yang Yang | PriorGuide: Test-Time Prior Adaptation for Simulation-Based Inference |
| 24 | Nasrulloh Satrio (Loka) | Efficient Autoregressive Inference for Transformer Probabilistic Models |
| 25 | Jenni Hukkanen | On Feed-Forward Models for Scene Reconstruction and Representation |
| 26 | Ekkehard Schnoor | Concept Activation Vectors: A Unifying View and Adversarial Attacks |
| 27 | Abdur Rahman | Fixed-Mode inverse-Gamma Fitting of Aerosol Particle Number Size Distributions |
| 28 | Anchen Li | Chemical Reaction-Based Molecular Representation Modeling |
| 29 | Ke Ping | MULTI-MODALITY DATASET FOR AD & RCA IN MICROSERVICE SYSTEM |
| 30 | Sahar Golipoor | RFID-based motion recognition |
| 31 | Xu Yang | |
| 32 | Jiaheng Lu | Multi-model data management |
| 33 | Tetiana Malykhina | High-performance distributed computing and data processing for fundamental and applied scientific research |
| 34 | Plasma Physics Meets AI | |
| 35 | Salma Rachidi | Interpretable Multiple Myeloma Prognosis with Observational Medical Outcomes Partnership Data |
Title: What Should We Trust AI to Do? Agency, Delegation, and Digital Ethics from Software Agents to Agentic AI
Abstract:
Thirty years ago, my master's thesis explored agent-based systems, i.e. pieces of software designed to act autonomously on a user's behalf. What was then a research curiosity has become everyday infrastructure: AI agents now make consequential decisions in our work, institutions, and private lives. This talk traces that arc and asks the questions it forces on us. What do we actually want to delegate to machines, and what should we keep for ourselves? How and why do we come to trust AI systems? What is it, exactly, that we are trusting, and when is that trust misplaced?
Drawing on recent years of teaching Digital Ethics at Aalto University, I will argue that agency and trust are not technical properties to be engineered into a system, but contested ethical terrain. Design choices are never value-neutral, and the principles of trustworthy AI run into real tensions in practice: transparency against privacy, autonomy against beneficence, fairness against accuracy. Frameworks for trustworthy AI don't resolve these tensions; they name them. The choices about what we delegate, and what we trust machines to do, are made in the systems we design. The ethical question is not whether those choices are being made, but who is making them, and on whose behalf.