Sahand Behnam

Sahand Behnam

About

Detail

CEO & Founder | Entrepreneur | Rebuilding Telemedicine with AI | HealthTech | Digital Health | Clinical Collaboration | Coach | EMBA, DBA
Düsseldorf, North Rhine-Westphalia, Germany

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Résumé


Jobs verified_user 0% verified
  • Telemedicall
    CEO & Founder
    Telemedicall
    Sep 2022 - Current (3 years 11 months)
    Telemedicall is a next-generation real-time clinical tele-collaboration platform designed to go beyond traditional telemedicine. While most telemedicine solutions are limited to video consultations, Telemedicall enables true clinical collaboration by connecting caregivers, specialists, medical devices, and data streams in real time. We are building the infrastructure for a new model of care — where expertise is accessible instantly, regardless of location. 🔹 What we do: – Enable collaboration before, during, and after medical procedures – Provide multi-channel real-time streaming (video, devices, data) – Integrate medical equipment outputs into live clinical workflows – Enhance decision-making with AI-powered insights – Support cross-b
  • Teleminer
    CEO & Founder
    Teleminer
    Apr 2018 - Current (8 years 4 months)
    Teleminer is an AI-driven technology company focused on building scalable digital infrastructure across healthcare, data systems, and intelligent platforms. We design and develop solutions that transform complex data into actionable insights, enabling organizations to operate more efficiently, make smarter decisions, and unlock new opportunities through AI. 🔹 What we do: – Develop AI-powered platforms for data analysis and automation – Build scalable backend systems for high-volume, real-time data – Design cloud-based infrastructures for modern digital products – Enable data-driven decision-making across industries – Support innovation in healthtech and intelligent systems 🔹 Focus areas: – Artificial Intelligence & Machine Learning –
  • Sharif Tarasheh Electronics
    CEO & Founder
    Sharif Tarasheh Electronics
    Oct 2005 - Mar 2017 (11 years 6 months)
    I established my second company in 2005, Sharif Tarasheh Co., focused on projects in the Telemetry and SCADA.
  • N
    Senior IoT Develper
    NOCC Computing
    Apr 2002 - Mar 2005 (3 years)
    Following the early closure of my first business, I pursued higher education. While studying computer engineering at university, I worked part-time in technical roles.
  • I
    CEO & Founder
    Iratelnet
    Apr 1998 - Mar 2001 (3 years)
    Founded and operated a local internet service provider at the age of 18, delivering internet connectivity services to users. Led all aspects of the business, including technical infrastructure, operations, and customer support, within a highly regulated market. Gained early experience navigating regulatory constraints and building resilient systems. The company later ceased operations due to market regulatory changes.
Education verified_user 0% verified
  • U
    Doctor of Business Administration, Intelligence and Agile Businesses
    UT
    Jan 2017 - Dec 2019 (3 years)
  • I
    EMBA, Executive Master of Business Administration
    IMI Business School
    Jan 2012 - Dec 2014 (3 years)
  • S
    SUT
    SUT
    Jan 2000 - Dec 2004 (5 years)
Publications verified_user 0% verified
  • I
    A Novel Data-driven and Feature-based Forecasting Framework for Wasted Water (NRW) Optimization of Network Pressure Mana
    INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING RESEARCH AND DEVELOPMENT
    Sep 2020
    In this paper, a novel data-driven approach to improving the performance of wasted water (NRW) management and pumping system is proposed, in which necessary data are obtained by data mining methods as the input parameters of optimization problem to be solved in nonlinear programming environment. In this regard, first, CART classifier decision tree is used to classify the operation mode, or the number of active pumps, based on the historical data of Austin-Texas infrastructure. Then, SOM is utilized to classify the customers and select the most important features that might have effect on the consumption pattern. Further, the extracted features is fed to Levenberg-Marquardt (LM) neural network that predicts the required outflow rate of the p
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