Seif Haridi

Kompics

Kompics is a message-passing component model for building distributed systems by putting together protocols programmed as event-driven components. Systems built with Kompics leverage multi-core machines out of the box and can be dynamically reconfigured to support hot software upgrades. A simulation framework enables deterministic debugging and reproducible performance evaluation of unmodified Kompics distributed systems.

AKL (Agents Kernel Language)

AKL is a concurrent constraint programming language developed at the Swedish Institute of Computer Science (SICS). In AKL, computation is performed by agents interacting through stores of constraints. This notion accommodates multiple programming paradigms; in appropriate contexts, AKL agents may be thought of as processes, objects, functions, relations, or constraints.

Continuous Deep Analytics (CDA)

SSF, 2018-2022

Modern end-to-end data pipelines are highly complex and unoptimized. They combine code from different frontends (e.g., SQL, Beam, Keras), declared in different programming languages (e.g., Python, Scala) and execute across many backend runtimes (e.g., Spark, Flink, Tensorflow). Data and intermediate results take a long and slow path through excessive materialization, conversions down to different partially supported hardware accelerators. End-to-End guarantees are typically complex to reason due to the mismatch of processing semantics across runtimes.

The Continuous Deep Analytics (CDA) project aims to shape the next-generation software for scalable, data-driven applications and pipelines. Our work binds state of the art mechanisms in compiler and database technology together with hardware-accelerated machine learning and distributed stream processing.

ExtremeEarth

H2020, 2019-2021

ExtremeEarth concentrates on developing techniques and software that will enable the extraction of information and knowledge from big Copernicus data using deep learning techniques and extreme geospatial analytics, and the development of two use cases based on this information and knowledge and other relevant non-EO data sets.

ExtremeEarth will impact developments in the Integrated Ground Segment of Copernicus and the Sentinel Collaborative Ground Segment. ExtremeEarth tools and techniques can be used for extracting information and knowledge from big Copernicus data and making this information and knowledge available as linked data, allowing easy development of applications by developers with minimal or no knowledge of EO techniques, file formats, data access protocols etc.

A Big Data Analytics Framework for a Smart Society (BIDAF)

KK-stiftelsen (KKS), 2014-2019

The overall aim of the BIDAF project is to significantly further the research within massive data analysis, by means of machine learning, in response to the increasing demand of retrieving value from data in all of society. This will be done by creating a strong distributed research environment for big data analytics.

There are challenges on several levels that must be addressed: (i) platforms to store and process the data, (ii) machine learning algorithms to analyze the data, and (iii) high level tools to access the results.

StreamLine

H2020, 2016-2018

Streamline is funded by the European Union's Horizon 2020 research and innovation program to enhance the European data platform Apache Flink to handle both stream data and batch data in a unified way. The project includes both research and use cases to validate the results.

The project has the following objectives: (i) to research, design, and develop a massively scalable, robust, and efficient processing platform for data at rest and data in motion in a single system, (ii) to develop a high accuracy, massively scalable data stream-oriented machine learning library based on new algorithms and approximate data structures, (iii) to provide a unified interactive programming environment that is user-friendly and easy to deploy in the cloud, (iv) to implement a real-time contextualization engine, enabling analytical and predictive models to take real world context into account, and (v) to develop multi-faceted, effective dissemination of Streamline results to the research, academic, and international community.

E2E-Clouds

SSF (Swedish Foundation for Strategic Research), 2012-2017

E2E-Clouds was a five-year research project financed by the Swedish Foundation for Strategic Research. The goal of the project is to develop an End-to-End information-centric Cloud (E2E-Cloud) for data intensive services and applications.

The E2E-Clouds is a distributed and federated cloud infrastructure that meets the challenge of scale by aggregating, provisioning and managing computational, storage and networking resources from multiple centers and providers. Like some current data-center clouds it manages computation and storage in an integrated fashion for efficiency, but adds wide-scale distribution.

iSocial

FP7 Marie Curie ITN, 2013-2017

The rapid proliferation of Online Social Networking (OSN) sites is expected to reshape the Internet's structure, design, and utility. We believe that OSNs create a potentially transformational change in consumer behavior and will bring a far-reaching impact on traditional industries of content, media, and communications.

The iSocial ITN aspires to bring a transformational change in OSN provision, pushing the state-of-the-art from centralized services towards totally decentralized systems that will pervade our environment and seamlessly integrate with future Internet and media services. OSN decentralization can address privacy considerations and improve service scalability, performance and fault-tolerance in the presence of an expanding base of users and applications.

The main objective of iSocial is to provide world class training for a next generation of researchers, computer scientists, and Web engineers, emphasizing on a strong combination of advanced understanding in both theoretical and experimental approaches, methodologies and tools that are required to develop DOSN platforms.

A Community Networking Cloud in a Box (CLOMMUNITY)

FP7 EU-project, 2013-2015

Community networking is an emerging model for the Future Internet across Europe and beyond where communities of citizens can build, operate and own open IP-based networks, a key infrastructure for individual and collective digital participation.

The CLOMMUNITY project aims at addressing the obstacles for communities of citizens in bootstrapping, running and expanding community-owned networks that provide community services organised as community clouds. That requires solving specific research challenges: self-managing and scalable (decentralized) infrastructure services for the management and aggregation of a large number of widespread low-cost unreliable networking, storage and home computing resources; distributed platform services to support and facilitate the design and operation of elastic, resilient and scalable service overlays.