Architecture for Big Data & Machine Learning

Intel Domain Leader : Debbie Marr

Big Data Computing results in huge (and costly) energy consumption. Computing Technology energy is dominated by data movement. The research aims at new paradigms in handling data movements in Big Data environment consisting of minimizing data movement, moving the computing closer to the data, accelerating the computing, and exploiting more effective novel memory technologies.

The projects 

Conversational Speech Understanding

Intel Domain Leader : Moshe Wasserllat

The Converstaional Speech Understanding technology deals with understanding, analyzing and extracting valuable insight from human-to-human, verbal and/or textual interactions (e.g. meetings). Unlike human-to-machine existing solutions (e.g. SIRI), the challenges induced by Conversational Understanding are currently unaddressed by the industry. It is a generic technology that can enable multiple capabilities critical to rising usages (e.g. Meeting Assistants, Business Analytics, Customers Experience etc…)
The key developments will include: Integrated Speech and Text understanding, Natural Language knowledge Graph representation, Personal user modeling (e.g. behavioral patterns), Events and relations extraction and discourse analysis (e.g. argumentation & deliberation)…

The projects

Distributed Open Deep Learning Library for IA

Intel Domain Leader: Shai Fine

We plan to develop open-source library for large scale distributed training of deep networks, which is:
1) optimized for IA (Xeon, Xeon-Phi),
2) based on open-source data analytics cluster computing framework (Spark, Hadoop).

The research project will:
(1) Employ advanced ML concepts such as distributed learning and improved deep learning architecture.
(2) Include new, advanced & demanding, deep learning based use cases.

The projects 

Visual Processing and Understating

Intel Domain Leader – Ronny Ronen
In addition to the ICRI-CI 3-layered capstone research, ICRI-CI host several research project in the visual processing and understanding domain. These research projects were added because of their potential high value to Intel, the industry, or the academia.

Past Projects

Advanced Machine Learning

Novel Heterogeneous Computing Platforms


Learning Visual Systems

Brain-inspired computing

Intelligent Agents