About

The Aalto Systems and Services Engineering Analytics (AaltoSEA) Group concentrates and consolidates research activities, resources, results, and collaborations on foundational principles, concepts and techniques for service engineering analytics of distributed software systems and services, big data applications, machine learning systems and IoT. We are a member of The Department of Computer Science, Aalto University. We also contribute to the newly established Aalto Center for Autonomous Systems. Recently, we have also started to study what does it mean software and services analytics in the age of quantum computing through the collaboration in The Finnish Quantum Institute. At Aalto we teach students to study topics in Big Data Platforms and Systems for Big Data/Machine Learning and supervise research theses in, for example, cloud computing, big data, IoT, edge computing, and ML.

Engineering Analytics

Engineering analytics is concerned with the techniques and tools for designing, monitoring, analyzing, explaining and optimizing functions, performance, data quality, elasticity, and uncertainties associated with systems, software, data and services. In our work, we focus on engineering analytics for: Systems and their interplay(IoT, Cloud and Edge Systems), Software (Machine Learning, Middleware, Protocols, and Tools), Data (Models and Analytics), Services (Data Marketplace, Service Models, APIs, and Configuration). We apply our engineering analytics techniques to various applications. See some high-level ideas in this presentation.

Systems

we focus on emerging complex distributed systems covering cloud systems, IoT, edge systems, cyber-physical systems and social-cyber-physical systems. Some of our novel concepts are elastic systems, IoT Cloud systems and the ensembles of IoT, Cloud and Networks

Software

We focus on system software, middleware, tools and applications in IoT, cloud, edge, enterprise, cyber-physical systems, and machine learning systems. Application domains are smart agriculture, smart city, e-science, and industrial internet. Some recent tools are IoT management, Uncertainty Testing for CPS, and IoT Cloud uncertainties

Data

We focus on IoT/big data data models and analytics, including various types of data in complex distributed systems that are gathered, processed and provisioned under different services. Some our novel concepts are elastic data analytics, Quality of Analytics, and incidents in big data

Services

We focus on novel technical service models (data-as-a-service, IoT services, e-science services, and several application-specific services), service API and execution management, and dynamic business models (e.g. pay-per-use) for consumers. Some of our novel conconcepts are Data-as-a-Service, data contracts for data marketplaces, human sensing data marketplace, and machine learning services

Research Directions

AI/Machine Learning/LLMs Observability and Optimization

End-to-end ML serving, LLMs Coordination, Quality of Analytics for ML

Quality-aware Data Intensive Systems

Data Concerns, Data Quality Evaluation and Data Contracts for Data Services, Data Marketplaces, Quality-aware Data Science, Big Data Systems

Uncertainties, Performance and Reliability Evaluation

Uncertainties analytics, performance monitoring and evaluation, IoT-Edge-Cloud Observability

Elasticity Engineering and Analytics

Multi-dimensional Elasticity, R3E Concepts, Multi-continuum engineering and analytics

Programming and Service Models for Hybrid Quantum Computing

Novel models and techniques for characterizing and optimizing non-functional parameters, including performance and interaction couplings, for emerging complex applications in hybrid quantum computing environments

Hybrid Intelligence Software (HIS) in Edge-Cloud Environment

HIS Characterization, Testing and Quality of Analytics (QoA) methods for HIS, Composability and Design Patterns with AI/LLMs

Team

Want to join the team for doing the research? Contact us!

Photo: Aalto University/Jaakko Kahilaniemi

Hong-Linh Truong

Anh-Dung Nguyen

Debayan Bhattacharya

Korawit Rupanya

Master Thesis Students

  • Timo Nappa
  • Lac Truong
  • Niko Vänttilä

Past members

Postdocs: Dr. Thanh-Phuong Pham, Dr. Bunjamin Memishi, Dr. Luca Berardinelli, Dr. Georgiana Copil, Dr. Daniel Moldovan,
Research assistants/Master Students: Thao-Nguyen Vuong, My-Linh Nguyen, Rohit Raj, Minh-Duc Ta, Strasdosky Otewa, Oscar Henriksson, Kreics Krists, Filip Rydzi, Michael Hammerer, Lingfan Gao, Juraj Cik, Florin Balint, Manfred Halper, Matthias Karan, Peter Klein

Past visitors

Jingyu Liang (China University of Petroleum (Beijing)), Adrian Orive Oneca (IKERLAN), Kyle Chard (University of Chicago), Liang Zhang (Fudan University), The-Vu Tran (Da Nang University), Huu-Hung Huynh (Da Nang University), Nam Huynh (HoChiMinh City University of Technology)

Results

Our GitHub prototypes: https://github.com/rdsea

Our Docker Hub: https://hub.docker.com/u/rdsea/

Concepts & Prototypes

Publications & Theses

See our full list here. Three recent publications: