Jennifer Tersteegen is a Doctoral Researcher affiliated with Aalto University's Department of Bioproducts and Biosystems. She works within the Biomolecular Materials research group, focusing on biomaterials and sustainable material development. Research Interests: Her work spans biomaterials engineering, protein-based adhesives, sustainable chemistry, and open-source hardware. She investigates condensate dynamics in biomolecular materials, develops bio-inspired polymers, and contributes to low-cost measurement technologies. Scientific Awards: Poster prize (Aug 2023) Working grant for 2024 (Oct 2023) Encouragement grant (May 2023) Working grant for 2023 (Jan 2022) Collaborations: Active across multidisciplinary projects in bioproducts, physics, and open-source engineering.
Nassim Sehad is a Doctoral Researcher at Aalto University's Department of Information and Communications Engineering, focusing on immersive communication technologies and UAV applications. Their work intersects with 6G network development, digital twinning, and virtual reality systems. Honors include a Nokia Foundation personal grant for thesis work . Recent publications analyze generative AI for Internet-of-Senses, UAV control mechanisms, and real-time aerial video streaming challenges, reflecting interdisciplinary research in telecommunications and autonomous systems.
Christian Guckelsberger is an Assistant Professor in Creative Technologies at Aalto University, leading the Autotelic Interaction Research (AIR) group. He also serves as a visiting scholar at the School of Electronic Engineering and Computer Science, Queen Mary University of London, and is a principal investigator (PI) at the Finnish Center for Artificial Intelligence (FCAI) and a member of the European Laboratory for Learning and Intelligent Systems (ELLIS). His research focuses on engineering creative artificial systems that interact meaningfully with humans, leveraging intrinsic motivation as a core driver of creativity. He bridges disciplines such as artificial intelligence (AI), human-computer interaction (HCI), psychology, philosophy, and creative practice, with applications in videogames, fine art, and design. Recent research trends include modeling intrinsic motivation for AI creativity, developing formal theories of competence, applying reinforcement learning to game design, and exploring human perception of AI-generated content. His work emphasizes sustainable adoption of creative AI in society and the workplace. Scientific awards include: Honorable Mention (CHI PLAY 2023) Finalist in “AI Game Dev” Competition (2021) Best Paper Award (International Conference on Computational Creativity, 2020) Best Paper Award (IEEE Conference on Computational Intelligence and Games, 2018) Finalist in EPSRC’s “Creative Computing” Competition (2018) Best Paper Honourable Mention (CHI Play, 2017) Christian is actively involved in mentoring, offering opportunities for research visits, postdocs, PhD, and Master’s thesis projects. His work intersects AI, game design, and interdisciplinary creativity research.
Stefan Werner is an Adjunct Professor in the Department of Information and Communications Engineering at Aalto University, specializing in statistical signal processing, adaptation and learning, distributed processing, wireless communications, and smart grids. He is an active member of the Risto Wichman Research Group. Werner's research centers on advancing distributed machine learning frameworks and signal processing techniques. His work in federated learning addresses critical challenges including model-poisoning resilience, communication efficiency, and personalized learning with privacy guarantees. In wireless communications , he contributes to massive MIMO channel modeling and consensus algorithms for networked systems. His recent innovations extend to lightweight deep learning for hyperspectral anomaly detection and non-convex optimization methods for quantile regression, with applications spanning smart grids and next-generation wireless networks. Analysis of his 2023-2025 publications reveals a dominant focus on distributed intelligence, with 60% of papers dedicated to federated learning advancements. Key trends include asynchronous online learning protocols, graph-based meta-learning frameworks, and robust optimization techniques. These works consistently bridge theoretical signal processing with practical implementations in wireless communications and remote sensing, demonstrating strong interdisciplinary impact across IEEE's top signal processing and IoT journals. Werner collaborates within the Risto Wichman Research Group at Aalto University, which pioneers signal processing solutions for 6G communications, IoT networks, and energy-efficient wireless systems.
Samuel Olukayode Akinwamide is a Research Fellow at the Department of Energy and Mechanical Engineering , Aalto University, Espoo, Finland. His research focuses on advanced materials for energy storage, corrosion behavior, and sustainable manufacturing processes. Position: Research Fellow Institution: Aalto University Department: Energy and Mechanical Engineering Key research areas include energy storage materials , electrochemical processes , additive manufacturing , and tribological properties of ceramics and composites. Recent publications highlight work on optimizing materials like Ti-6Al-4V composites, AlSi10Mg alloys, and graphene oxide derived from industrial waste for energy applications. His collaborative research spans journals such as Materials Science and Engineering: A , Smart Nanomaterials for Environmental Applications , and Journal of Energy Storage . Topics range from corrosion analysis to hybrid modeling for wear prediction. No awards or student advisories are explicitly listed.
Mahdi Bayanifar serves as a Postdoctoral Researcher in the Department of Information and Communications Engineering at Aalto University, Finland, operating within the Communications Theory research group. His work bridges theoretical and applied communications engineering with emerging quantum information systems. His research focuses on Wireless Communications, Information Theory, and Quantum Communications, with significant contributions to non-coherent signal processing using binary chirps, quantum error correction for repeaters, and RIS-enhanced mmWave networks. Recent work integrates classical random access protocols with quantum communication frameworks to address scalability challenges in next-generation networks. Analysis of his 2022-2025 publications reveals a strategic pivot toward quantum-classical hybrid systems, particularly in quantum repeater architectures and error correction, while maintaining strong contributions to 5G/6G wireless protocols through unsourced random access and chirp-based non-coherent communications. Scientific Awards: No awards, fellowships, or medals are documented in the provided materials. Advising and Grants: No information regarding student supervision, grant funding, or collaborative projects is available in the source text. Labs and Teams: He actively participates in Aalto University's Communications Theory research group, which specializes in mathematical modeling of communication systems, quantum information theory, and advanced wireless protocol design.
César Iván Olvera Espinosa is a Doctoral Researcher at Aalto University's Department of Information and Communications Engineering, specializing in Cloud and Network Computing . His research focuses on advanced computational systems and network infrastructure. Position: Doctoral Researcher Department: Information and Communications Engineering Research Groups: Cloud and Network Computing Contact: cesar.olveraespinosa@aalto.fi
Dr. Ashvin Srinivasan is a Doctoral Researcher at Aalto University , affiliated with the Department of Information and Communications Engineering . His research focuses on the intersection of wireless communications, network optimization, and machine learning. Academic Rank: Researcher Email: ashvin.1.srinivasan@aalto.fi His work explores reinforcement learning applications in next-generation cellular networks and dynamic resource allocation. Key research areas include: Multi-Agent Reinforcement Learning Cache Policy Optimization Asynchronous Scheduling A review of his publications reveals a focus on artificial intelligence-driven network optimization , particularly in cellular infrastructure and subnetwork scheduling. Recent studies emphasize deep reinforcement learning for adaptive systems. Affiliated with the Communications Theory research group, Dr. Srinivasan collaborates on advancing wireless communication frameworks.
Jari Collin is an Adjunct Professor of Enterprise Information Systems and Service Networks at Aalto University, Finland. With a dual background in academia and industry, he bridges theoretical research with practical implementation in digital transformation and industrial internet. Education: M.Sc. in Industrial Management (Tampere University of Technology, 1996), D.Sc. in Industrial Management (Helsinki University of Technology, 2003) Dr. Collin's research focuses on industrial internet , 5G applications , and data-driven business models for manufacturing companies. His work explores how digitalization disrupts traditional industries and creates new opportunities. His recent publications highlight trends in smart grid technologies , industrial IoT , and platform economy . Articles like 'Mobile base station site as a virtual power plant' (2025) demonstrate his emphasis on cross-disciplinary innovation. Scientific Awards Plan for Supply Chain Agility - Lessons from Mobile Infrastructure Industry (2005, ICAM International Conference on Agility) Leadership Grants: Directed ACIO research program (2013-15) on ICT utilization in Finnish organizations and contributes to Aalto University's Digital Disruption of Industry research program.
Stephane Deny is an Assistant Professor at Aalto University's Department of Neuroscience and Biomedical Engineering , affiliated with the Computer Science Professors research group. His work bridges computational neuroscience and artificial intelligence. Research interests focus on: Machine learning algorithms for object recognition Neuroscience-inspired AI architectures Self-supervised learning at scale Biomedical engineering applications of neural networks Recent publications examine the comparative performance of humans and AI in visual perception tasks, with emphasis on deep learning limitations and blockwise training approaches. Collaborators include researchers from computer science and cognitive neuroscience backgrounds. Key scientific contributions include: Advancing self-supervised learning methodologies Investigating pose-invariant object recognition Developing scalable neural network frameworks
Benjin Jin is a Doctoral Researcher at Aalto University , affiliated with the Chemistry and Materials research group. Their work focuses on advanced electrocatalysis and materials engineering for sustainable energy applications. Research Interests : Electrochemistry Catalysis Nanomaterials for Energy Conversion CO2 Reduction Water Splitting Graphene-Based Composites Publication Trends : Recent works (2024–2025) analyze novel catalysts for oxygen evolution reaction (OER), CO2-to-formate conversion, and graphene-supported bimetallic systems. Techniques include quantum dot engineering, hydrophilic-hydrophobic domain design, and computational modeling with machine-learned potentials. Collaborations : Active in multidisciplinary teams with researchers like Tanja Kallio, Hua Jiang, and Junjie Shi. Contact : benjin.jin@aalto.fi
Alexandru Paler serves as an Associate Professor in the Department of Computer Science at Aalto University, Finland, where he leads research in quantum software development. His work focuses on designing compilers and optimization frameworks for quantum circuits, with emphasis on quantum error correction implementation and fault-tolerant quantum computing systems. Based in Espoo at Konemiehentie 2, he maintains active research collaborations through the university's quantum computing initiatives. Dr. Paler's research spans quantum circuit compilation, quantum error correction (particularly surface codes and QLDPC codes), and quantum software optimization. His team develops high-performance quantum compilers for neutral atom architectures and modular superconducting systems, addressing critical challenges in resource estimation and fault tolerance. The Quantum Operating Systems (QUANTUM) research group he contributes to explores scalable quantum software frameworks that bridge theoretical algorithms with practical hardware constraints, with significant work on graph-state compilation and reinforcement learning for circuit optimization. Analysis of his 15 most recent publications (2023-2025) reveals concentrated efforts in quantum compiler design, error correction scalability, and hardware-aware quantum software. Key trends include machine learning applications for decoder optimization, novel approaches to measurement-free error correction, and queuing theory models for fault-tolerant circuit analysis. His work consistently addresses the practical barriers to large-scale quantum computing through compiler innovations and resource-efficient circuit design. Dr. Paler actively participates in the Quantum Operating Systems (QUANTUM) research group within Aalto's Department of Computer Science, focusing on Algorithms and Theoretical Computer Science. This team develops quantum software infrastructure for next-generation quantum hardware, with current projects including Pandora (ultra-large-scale circuit compilation), quantum circuit caching mechanisms, and standardized cell approaches for neutral atom systems. Their research directly supports the transition from theoretical quantum algorithms to executable, error-resilient quantum programs.
Cristian A. Galvis Florez is a doctoral researcher at Aalto University's School of Electrical Engineering, supervised by Professor Simo Särkkä. As part of the QuantLearn project funded by the Research Council of Finland, he explores quantum machine learning algorithms with applications in computational science. His academic journey spans Colombia, Oxford, and Finland, bridging quantum mechanics and machine learning. Education: Master’s in quantum computing, PhD ongoing at Aalto University Research Focus: Quantum state tomography, Gaussian process algorithms, and NISQ device optimization His work integrates quantum computing with machine learning , emphasizing probabilistic modeling and quantum hardware implementation . Recent publications highlight advancements in quantum-assisted regression and state estimation techniques . The QuantLearn project underpins his research, developing algorithms with potential to revolutionize computational domains. His publications demonstrate cross-disciplinary expertise in quantum theory and statistical modeling , leveraging low-rank Gaussian processes for quantum applications.
Muhammad Iqbal is a Research Fellow at Aalto University, affiliated with the Department of Electrical Engineering and Automation. His work focuses on resilient control systems, cybersecurity for cyber-physical systems, and advanced signal processing techniques. Research Interests: Resilient control of connected automated vehicles Robust Kalman filtering under cyber-attacks Multi-agent systems and distributed optimization Signal denoising and sparse signal processing Microgrid fault diagnostics and control Hydropower system regulation Research Groups: Sensor Informatics and Medical Technology.
Ying Liu is a Doctoral Researcher in the Department of Information and Communications Engineering at Aalto University . Ying is affiliated with the Ambient Intelligence research group, focusing on advanced wireless network optimization and edge computing systems. Position: Doctoral Researcher Institution: Aalto University Email: ying.2.liu@aalto.fi Research Interests span wireless network optimization, unmanned aerial vehicle (UAV) systems, edge computing, and deep reinforcement learning applications. Ying’s work addresses dynamic resource allocation challenges in multi-UAV environments and task offloading strategies for IoT systems. Publications highlight contributions to UAV deployment and latency reduction in edge computing. Key journals include the IEEE Internet of Things Journal .
