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Nick ****** AI Research Scientist

$1080 / day


Passionate and driven Data Scientist and Machine/Deep Learning specialist with over 15 years of experience, adept at developing and implementing innovative solutions for complex business challenges. Backed by a robust academic background, I excel in data science, machine learning, and statistical modelling, leveraging advanced AI technologies to drive company innovation and improve operational efficiency. With a proven track record of creativity in applying and developing cutting-edge AI methods, I possess strong problem-solving abilities and a knack for innovative thinking. Comfortable working both independently and collaboratively, I consistently deliver high-quality results.


AEsAWS (SageMaker)AzureBig Data TechnologiesC#C++Chatbot developmentChatbot platforms (StreamlitChatGPT)CLIP)Cloud ServicesConvolutional Neural Networks (CNNs)Data CleaningData EngineeringData preprocessingData TransformationData VisualizationDatabricksDecision TreesDeep LearningDialogflow)Diffusion)DockerEntity recognitionGenerative AIGenerative Neural Networks (GANsGITGoogle Cloud Platform (GCP)High-Performance ComputingHPC-GPU clustersK-Nearest Neighbors (KNN)Keras)LangChain)Large dataset handlingLarge Language Models (LLMs: e.g. LLaMALaTeXLinear RegressionMachine LearningMATLABMatplotlibMulti-Modal models (e.g.Neural NetworksNLPNLP libraries (spaCyNLTKOpenCVPower BIProgramming LanguagesPython (PyTorchRandom ForestsRecurrent Neural Networks (RNNs)Retrieval-augmented generation (RAG)Scientific ProgrammingScikit-LearnseabornSelf-supervised learningSparkSQLStable DiffusionSupervised learningSupport Vector Machines (SVM)TableauTensorFlowText processingToolsTransformersUnsupervised learningXGBoost
AI ConsultantAI ProgrammerAI Research ScientistAI Software DeveloperDeep Learning EngineerMachine Learning Engineer


Nov 2021 PhD in Artificial Intelligence at Griffith University


Feb 2022 - Present Postdoctoral Research Fellow at Griffith University

– Exploring innovative enhancements for Large Language Models (LLMs), Vision Transformers (ViTs), and Diffusion models.
– Developing a monitoring system incorporating advanced AI technologies such as Deep Neural Networks, Object Detection, Classification, and Tracking algorithms for animals in a
production aquatic tank system.
– Deploying Machine/Deep Learning and Computer Vision models on embedded/edge devices.
– Developing customized LLMs and Stable Diffusion models.
– Created a COVID-19 detection model using chest CT scans.
– Designed a novel Attention Network for Image Recognition and Object Detection.
– Engineered a lightweight Attention-based Lattice Network for Hyperspectral Image Classification.
– Innovated an attention-based Deep Network for Image Restoration.
– Developed a state-of-the-art Speech Enhancement model.

May 2021 - Feb 2022 Machine Learning-Software Engineer at Olitek Design Solutions Pty Ltd

– Designed and developed Machine Vision (2D/3D) and Machine/Deep Learning packages for the Blast Hole Sampling (BHS) robot using C++.
– Integrated vision control smoothly with SCADA Indusoft Web Studio (IWS).
– Improved and addressed issues in the Vision system of the Temperature Monitoring Unit (TMU) robot using C++.
– Developed and presented technical solutions and proposals for new product development.

Oct 2013 - Sept 2017 Software Engineer-Data Scientist Manager at Pishgaman Kavir Asia Company

– Developed an intelligent VoIP and Internet traffic data monitoring and analysis system using C#.
– Utilized data visualization tools such as Power BI, along with anomaly and pattern recognition techniques.
– Designed and implemented necessary SQL databases.

Sept 2012 - Sept 2012 Research Fellow at K.N.Toosi University of Technology

– Developed a visual search engine funded by Information and Communication Technology (ICT) organization in Iran.
– Image Processing techniques and GA, KNN, and Neural Networks algorithms were utilized.

May 2008 - March 2009 AI Engineer (Contractor) at National Traffic and Driving Organization

Developed and implemented a Genetic Algorithm (GA)-based algorithm for optimizing the traffic network’s parameters.
– Conducted extensive testing and validation of the GA algorithm to ensure robustness and efficiency.
– Collaborated with stakeholders to define requirements and refine algorithm objectives.
– Documented the algorithm design, implementation steps, and outcomes for future reference.
– Presented findings and recommendations to management and technical teams.
– Contributed to the enhancement of existing traffic management systems through innovative algorithmic solutions.

Aug 2006 - June 2012 Software Engineer-Data Scientist at Pishgaman KaiPod Company

Developed an Intelligent License Plate Recognition system using C++ and C#.
Implemented Image Processing and Machine Vision techniques, incorporating Machine Learning algorithms such as K-Nearest Neighbors (KNN) and Neural Networks.
– Created an automatic car speed detection system tailored for national traffic and driving organizations.
– Designed and implemented necessary SQL databases to store and manage system data effectively.
– Conducted thorough testing and validation of both systems to ensure accuracy and reliability.
– Collaborated with stakeholders to refine system requirements and optimize performance.
– Documented system architectures, algorithms, and implementation details for future maintenance and scalability.