Loghman Mohammadzadeh

Data Scientist at University of Salford

I am a data scientist and senior software developer with 15+ years of experience in implementing machine learning systems, coding, leading development teams and developing software for desktop computers, web and mobile devices. I have experience working in the AI field from my academic background and within my professional career. The main areas of my interest are deep learning, especially computer vision, and natural language processing(NLP) and bias in AI. 

Tell us about your role and what you’ll be doing for the AI Foundry:

Whilst working on the AI Foundry, I’ll be involved in delivering sessions on “AI lifecycle management methodologies”, “Algorithmic bias and fairness in AI” and “Cloud technologies, Deployment of AI systems and MLOps” in phase one of the programme.

I will be helping the SMEs to scope their ideas and deliver technical assistance to accepted organisations in the second phase of the project.

What excites you the most about the programme?

Working on any AI project is always exciting for me. Normally when working for a company, you are focused on one project or area however, within the AI Foundry, I have the opportunity to deal with different SMEs across different AI fields and support them to develop or extend their ideas, bringing them to reality.

The most exciting part of the programme is the economic impact on the Greater Manchester area and creating new opportunities to increase the employment of specialised people.

Loghman’s Background

Skills and experience:

  • Experience with object-oriented/object function scripting languages: Python, R and Java, C++
  • Expertise with developing machine learning models and developing NLP and computer vision models using TensorFlow, Keras and OpenCV
  • Experience with relational databases and NoSQL databases 
  • Skill of developing big data solutions on Hadoop based technologies such as MapReduce, Hive, Apache Spark
  • Knowledge of using the cloud technologies on AWS and CD/CI Pipeline 
  • Experience in using different AI/Software development life cycle methodologies such as CRISP-DM, Kanban, TDSP and Scrum

The project is providing innovation consultancy and advisory aid in line with the De Minimis Exemption (in accordance with Commission Regulation (EU) No 1407/2013, OJ L 352/1) and Innovation R&D aid in line with the General Block Exemption Regulation (in accordance with Commission Regulation (EU) No 651/2014 of 17 June 2014, OJ L 187/1)

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