Nevine Rizkalla

Nevine Rizkalla

IT RnD - Section Head at Orascom Construction Industries (OCI)

Location
Egypt
Industry
Construction

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Nevine Rizkalla's Overview

Current
Past
  • Intern-Software Engineer at ITWorx

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see all

Education
  • The American University in Cairo
  • Ramses College for Girls
Connections

175 connections

Nevine Rizkalla's Experience

IT RnD - Section Head

Orascom Construction Industries (OCI)

Privately Held; 10,001+ employees; Construction industry

August 2012 – Present (11 months) Nile City

Senior Software Developer

Orascom Construction Industries (OCI)

Privately Held; 10,001+ employees; Construction industry

February 2010 – August 2012 (2 years 7 months)

Software Developer

Orascom Construction Industries (OCI)

Privately Held; 10,001+ employees; Construction industry

January 2009 – February 2010 (1 year 2 months)

Intern

BG Group

Public Company; 5001-10,000 employees; BG.L; Oil & Energy industry

July 2006 – August 2006 (2 months)

Intern-Software Engineer

ITWorx

Privately Held; 501-1000 employees; Computer Software industry

June 2006 – August 2006 (3 months)

Nevine Rizkalla's Publications

  • Neural Prosthetic Asynchronous Control (NPAC)

    • ACSE 2010 - ACTA Press
    • March 2010
    Authors: Nevine Rizkalla, Mina Farid

    Brain Computer Interface (BCI) provides a direct neural interface and communication pathway between the human brain and an external device such as a computer or artificial limb. With such an interface a severely handicapped person, such as an Amyotrophic Lateral Sclerosis (ALS) patient, with severe muscle disorder may still communicate with and even control their environment relying using his brain activity. Even patients suffering from locked-in syndrome where they cannot move or communicate due to complete paralysis can communicate and control using BCI technology. The Neural Prosthetic Asynchronous Control (NPAC) system described asynchronously controls neural prosthetic devices for paralyzed patients. It captures EEG signals emitted from the brain, performs signal processing and classification on the captured raw signals, and produces appropriate control actions accordingly. NPAC analyzes Mu signals whose activity is associated with the motor cortex and altered with motion or intended (imagined) motion. In this paper, we describe our method, and empirically show that NPAC achieved good accuracy for trained sub jects in real-time environment. NPAC classifies right hand “imagined” movement, brain rest state, eye blinks, and eye looking down. It was tested on a trained non-paralyzedsub ject who managed to do several control activities such as controlling a wheelchair, moving a prosthetic device (both emulated on a robot), playing simple games, and navigating through virtual reality.

Nevine Rizkalla's Languages

  • English

  • Arabic

Nevine Rizkalla's Education

The American University in Cairo

BS, Computer Science

2004 – 2009

Ramses College for Girls

Thanawaya Amma

Nevine Rizkalla's Additional Information

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