Best Machine Learning Specialists New Castle Near You

Tom Ryder

Skills

• Python
• Machine Learning
• Statistical Modeling
• Research
• R
• SQL
• Neo4j
• Microsoft Azure
• Amazon Web Services (AWS)
• Java
• Matlab
• Big Data Analytics
• Apache Spark
• Cloud Computing
• NoSQL
• Shell Scripting
• Secure Shell (SSH)
• Web Servers
• Data Science
• Reinforcement Learning

• Position: Machine Learning Scientist (Senior Engineer)
• Current company: Qualcomm

Machine learning researcher with experience in computer vision, Bayesian statistics, generative modelling and data compression.

Jake Cowton

Skills

• Deep Learning
• DevOps
• PyTorch
• Computer Vision
• Machine Learning
• Research
• Programming
• Project Management
• Computer Science
• Big Data
• Web Development
• Artificial Intelligence (AI)
• Amazon Web Services (AWS)
• Python
• Linux
• HTML
• Visual Basic
• CSS
• SQL
• Git

• Position: Machine Learning & Lead Data Engineer
• Current company: Welcome: Real time travel plans
• Languages: English · French · German

I'm an experienced ML engineer with expertise in the full life cycle of Deep Learning and Computer Vision models, from data collection and pipelines, to custom model design and deployment at scale.

My PhD research focused on applications of deep learning in precision agriculture. Alongside my academic work, I also have experience working in startups and bigger businesses. Whilst working towards my PhD, I co-founded two startups, which gave me an incredible rage of experiences.

Though my research background is in computer vision and time series analysis, my interests also lie in NLP, DevOps/MLOps, and privacy-preserving AI.

Bing Zhai

Skills

• Navision
• Experienced Business Analyst
• ERP
• Machine Learning
• Data Warehousing
• Data Mining
• SharePoint
• C#
• .NET
• T-SQL
• Unix
• Microsoft SQL Server
• Databases
• Database Design
• ETL
• SSIS
• SSRS
• Business Intelligence
• Embedded Software Programming
• Machine

• Position: EPSRC Applied Machine Learning PhD Student (FT)
• Current company: Newcastle University
• Languages: English

Stephan Chalup

Skills

• Higher Education
• Theory
• University Teaching
• Research
• Management
• Autonomous Agents
• Machine Learning Applications
• Aged Care Research
• Big Data
• Robotics
• C
• Computer Vision
• Java
• Artificial Neural Networks
• Artificial Intelligence (AI)
• Data Analytics
• Deep Learning
• Machine Learning
• Programming
• Software Development

• Position: Professor
• Current company: The University of Newcastle, Australia
• Languages: English · German

Professor Stephan Chalup works in the areas of Artificial Intelligence and Machine Learning at the University of Newcastle, Australia. He was awarded his PhD in Computing in 2001 by QUT where he had studied at the Machine Learning Research Centre. Before he came to Australia he completed postgraduate studies in mathematics and neuroscience at the University of Heidelberg in Germany. His research interests include artificial neural networks, topological data analysis, manifold learning, humanoid robots, and autonomous agents. He is on the editorial boards of several journals, chaired conferences, and acted in various administrative roles including Head of Discipline. He heads and built up the Newcastle Robotics Lab and the Interdisciplinary Machine Learning Research Group.

https://www.newcastle.edu.au/profile/stephan-chalup
https://orcid.org/0000-0002-7886-3653

Amir Ebrahimi

Skills

• Pspice
• Pattern Recognition
• Image Processing
• Neural Networks
• Machine Vision
• Matlab
• Simulink
• Labview
• C
• C++
• VHDL
• Machine Learning
• Engineering
• Orcad
• Verilog
• Simulations
• Digital Signal Processors
• Proteus
• Signal Processing
• Artificial Intelligence

• Position: Machine Learning Engineer
• Current company: EMVision Medical Devices Ltd
• Languages: American English · Arabic · Persian

I received my master’s degree in Digital Electronics from the Amirkabir University of Technology, Tehran, Iran, in 2012. Currently, I am a PhD student in Information Technology at the University of Newcastle, Australia. I have academic publications and experience in software/hardware programming for several companies. My research interests are image processing, computer vision, machine learning, and artificial intelligence.

Farshid Keivanian

Skills

• Evolutionary Computation
• Multi-objective Optimization
• Machine Learning
• Fuzzy Logic
• Fuzzy Systems
• Metaheuristics
• Many-objective optimization
• Neural Networks
• Pattern Recognition
• Artificial Neural Networks
• Prediction
• Google Colab
• Microsoft Excel
• Microsoft Access
• NVivo
• Tableau
• Camtasia
• MATLAB
• Simulink
• PostgreSQL

• Position: Research and Development of Novel Software and Mobile Apps-Machine Learning and Data Analysis
• Current company: Faraz Danesh Keivan Co.
• Languages: English · Persian

Biography – Spearheaded the establishment of novel parallel search algorithms and decision-making models as the PhD student of Prof. Raymond Chiong. Refined accountability, problem-solving, self-motivated, innovative multi-skilled, independent researcher, and interpersonal skills introducing novel open-source platforms. Planned learning agility with a passion for solving new health, science, and engineering challenges using Artificial Intelligence. Processed data and performed complex calculations with Unix shell and High-Performance Computing (HPC). Trained top skills include Machine Learning, Quantitative and Qualitative Data Analysis, Statistical Analysis, Microsoft 365, LaTeX, Advanced Academic Writing and Speaking Style, and high-level expertise in a range of programming languages (MATLAB, Python, R, C/C++, bash, Java, and SQL). Excellent written scientific communication skills by completing six research studies sent to or published by the journals of Expert Systems with Applications (ESWA), Fuzzy Sets and Systems (FSS), Soft Computing (SC), Computational Science (CS), and PLOS ONE.
- Published paper fuzzy-metaheuristic single and multi-objective methods in ESWA to solve (or optimise) complex multimodal single and multi-objective optimisation problems by performing a fuzzy logic-based parallel search in the solution space. Comprehensive experiments have been conducted, and the results showed that our proposed approaches' performance is superior to well-established algorithms on complex benchmarks. The article has a direct link to the developed open-source software.
- Collected and analysed body fat lipids and circumferences data and established a novel, multi-objective fuzzy-evolutionary machine learning framework. The model can track fat deposits across the most vital features and produce more precise predictions than the current machine learning models in the literature (SC).
- Proposed a novel fuzzy logic-based suppressed/reinforced learning mechanism to identify representative patterns in highly overlapped, high-dimensional, and large-scale datasets (FSS).
- Designed a novel fuzzy evolutionary optimiser with my supervisor and the research team (Prof. Amir H Gandomi and Dr Alireza Kashani) to solve a complex geotechnical problem with minimum cost, weight, CO2 emission, and earthquake resistance (CS).

Awarded 4th place on the mobile app integration of a novel body fat prediction model at the Life Science Innovation export hub's pitch program at QUT. Hold the University of Newcastle fully funded stipend and tuition fees.