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Dr Soheil Varastehpour

Senior Lecturer
School of Computing, Electrical and Applied Technology
Location: Building 183, Room 3001

Professional memberships

Member of IEEE

Profile

 Research Interests:

  • Machine Learning & Deep Learning
  • Image Processing
  • Software Development

Teaching

Current Papers:

  • Cryptography (Cyber security_Level 6 course)
  • Programming Principles and Practice (undergrad course)
  • Networking Fundamentals (undergrad course)

Past Papers:

  • Introduction to Data Science (postgrad course)
  • Hardware Fundamentals
  • Operating System Fundamentals
  • Programming Fundamentals
  • UPC 2&3

 

Publications

Lin , F., Shakiba, M., Zhang, E., & Varastehpour, S. (2025). A Recommendation System Model for Instagram Influencer Marketing Campaign. 11th International Conference on Computer Technology Applications (ICCTA 2025), Vienna, Austria (pp. 1-6).

Singh, S P., Shakiba , M., Varastehpour, S., & Aharari, A. (2025). Apple Leaf Disease Detection: A Comprehensive Analysis of Pre-Trained Models and Platform Development. Future Technologies Conference (FTC), Munich, Germany. , Vol. 3 https://doi.org/10.1007/978-3-032-07995-4_6

Debnath, B., Varastehpour, S., & Shakiba, M. (2025). Clustering and Prediction: Evaluation of Machine Learning Models for Robust Business Operation. 3rd International Conference on Artificial Intelligence and Applications (ICAIA 2025) (pp. 1-11).

Varastehpour, S., Abdolahi, A., Modares, A. F. A., & Varastehpour, S. (2025). Comparison of CNN-Transformer and LSTM models for forex market forecasting. In S. Varastehpour & M. Shakiba (Ed.), Proceedings: AIOT Global Summit 2025: Economic Growth, ePress, Unitec (pp. 73–79). https://doi.org/10.34074/proc.250114

Thu Tun, M., Varastehpour, S., & Shakiba, M. (2025). Deep Learning Approaches for Predicting Stock Market Trends: A Comparative Study of New Zealand and Australian Markets. 5th International Conference on Advances in Electrical, Electronics and Computing Technology (EECT 2025) (pp. 6-12).

Mangotra, B. D., Varastehpour, S., Shakiba, M., & Sharifzadeh, H. (2025). Evaluating Deep Learning on Deepfake Media across Multi-Datasets. The 6th International Conference on Trends in Computing and Information Technology (ICTCIT 2025), Turkey

Varastehpour, S., Abdolahi, A., Modares, A. F. A., & Varastehpour, S. (2025). Forecasting AUD/USD Forex Trends Using Advanced CNN-Based Hybrid Models. In S. Varastehpour & M. Shakiba (Ed.), AIOT Global Summit 2025: Economic Growth, ePress, Unitec. (pp. 87–92). https://doi.org/10.34074/proc.250116

Sojan, G., Varastehpour, S., & Shakiba, M. (2025). Forex Prediction using Deep Learning: CNN, LSTM, GRU and hybrid models. 3rd International Conference on Artificial Intelligence and Applications (ICAIA 2025) (pp. 1-15).

BARMADA, B., KANNANGARA, M., RAMIREZ-PRADO, G., POUR, S., & SHAKIBA, M. (2025). Humanizing AI Chatbots: The Role of Speech Emotion Recognition with Deep Learning. In Khalid S. Soliman (Ed.), 45th IBIMA Computer Science Conference (pp. 1-9).

Zhang, E., Shakiba, M., Lin, F., Hassandoust, F., & Varastehpour, S. (2025). Optimising Social Media with Gen AI - A Study on SEO Strategies for Influencers. 11th International Conference on Computer Technology Applications (ICCTA 2025), Vienna, Austria (pp. 7-13).

Dave, Y., Varastehpour, S., & Shakiba, M. (2025). Predicting Forex Prices: An Evaluation of Long Short-Term Memory, XGBoost and Transformer Architectures. 5th International Conference on Advances in Electrical, Electronics and Computing Technology (EECT 2025) (pp. 1-6).

Varastehpour, S., Abdolahi, A., Modares, A. F. A., & Varastehpour, S. (2025). Predicting the Forex Market with CNN-BiLSTM and CNN-LSTM. In S. Varastehpour & M. Shakiba (Ed.), Proceedings: AIOT Global Summit 2025: Economic Growth, ePress, Unitec. (pp. 100–105). https://doi.org/10.34074/proc.250118

Chhetri, S., Sharifzadeh, H., Keivanmarz, A., & Varastehpour, S. (2025). Visualising Vein Pattern using Conditional Transformer-based GAN for Forensic Investigations. 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC) (pp. 1990-1995). https://doi.org/10.1109/COMPSAC65507.2025.00277

Fonseka, H., Varastehpour, S., Shakiba, M., Golkar, E., & Tien, D. (2025). May ∕ Jun 2025. Convolutional variational auto-encoder and vision transformer hybrid approach for enhanced early Alzheimer’s detection. Journal of Medical Imaging, 12(3), 1-14. 10.1117/1.JMI.12.3.034501

HADDAOUI, Seloua., KHLIFA, Nawres., CHIKHI, Salim., VARASTEHPOUR, Soheil., & ADJAILIA, Fouzia. (2024). A Comprehensive Review of Beekeeping Datasets for Precision Apiculture Research. 10th International Conference on Control, Decision and Information Technologies (CoDIT) (pp. 1-6).

Sharma, A., Varastehpour, S., Ardekani, I., & Sharifzadeh, H. (2024). Bee Disease Varroa Prediction: Utilizing Convolutional Neural Networks with Augmentation for Robust Detection and Identification of Honeybee Infection. 1st International Conference on Innovative Engineering Sciences & Technological Research (ICIESTR-2024) (pp. 1-6).

Dangwal, Karikeye., Ardekani, Iman., Varastehpour, Soheil., & Sarrafzadeh, Abdolhossein. (2024). Bioacoustic Data Augmentation Techniques for Data-Driven Apicultur. 2024 IEEE International Conference on Future Machine Learning and Data Science (FMLDS) (pp. 1-6).

Adlakha, R., Varastehpour, S., Shakiba, M., & Ardekani, I. (2024). Comparative Analysis of Long-Short Term Memory, Gated Recurrent Unit, and eXtreme Gradient Boosting for Forex Prediction: A Deep Learning Approach. 1st International Conference on Innovative Engineering Sciences & Technological Research (ICIESTR-2024) (pp. 1-6).

Dave, Yash., Varastehpour, Soheil., & Shakiba, Masoud. (2024). Forex Price Prediction: A Multi-Model Approach Integrating Sentiment Analysis Using LLMs with LSTM, XGBoost, Transformer Models. In 18th International Conference on Information Technology and Applications (ICITA) (Ed.), Sydney, Australia (pp. 6-12).

Trehan, Mohita., Varastehpour, Soheil., Shakiba, Masoud., Ramirez Prado, Guillermo., & Barmada, Bashar. (2024). Predicting New Zealand’s Stock Market Trends: Combining Sentiment Analysis and Deep Learning. In 18th International Conference on Information Technology and Applications (ICITA) (Ed.), Sydney, Australia (pp. 1-6).

Ramirez-Prado, Guillermo., Barmada,, Bashar., Varastehpour, Soheil., & Shakiba, Masoud. (2024, September). Empowering Homes: On Navigating Energy Hardship with Consumption Monitoring in New Zealand [Poster presentation]. The International Conference on Sustainable Development, New York.

Li, T., Varastehpour, S., & Shakiba, M. (2024, Oct). Methods in Skill Extraction from Job Descriptions [Poster presentation]. Computing and Information Technology Research and Education New Zealand (CITRENZ), Dunedin, New Zealand.

Chishti, Shafquat., Ardekani, Iman., & Varastehpour, Soheil. (2024). AI-Enhanced Personality Identification of Websites. Information, 15, 1-16. https://doi.org/10.3390/info15100623

Sharifzadeh, Hamid., Keivanmarz, Ali., Varastehpour, Soheil., & Ardekani, Iman. (2024, April). Vein Pattern Visualisation for CSAM Investigation Using Deep Learning. Australian Journal of Forensic Sciences, 56, 167-169. https://doi.org/10.1080/00450618.2024.2324774

Wang, Changjin., Sharifzadeh, Hamid., Varastehpour, Soheil., & Ardekani, Iman. (2023). Analysis and Comparison of Deepfakes Detection Methods for Cross-Library Generalisation. The 20th Annual International Conference on Privacy, Security & Trust, Copenhagen, Denmark (PST2023) (pp. 1-6).

Ardekani, Iman., Sharifzadeh, Hamid., & Varastehpour, Soheil. (2023). Dynamic Control of Active Noise Control Systems with Simplified Secondary Path Models. 2023 IEEE 12th Global Conference on Consumer Electronics (GCCE 2023) (pp. 1_4).

Ardekani, Iman., Varastehpour, Soheil., Sharifzadeh, Hamid., & Abdulla, Waleed. (2023). Improving ANC Computational Efficiency: A Novel FxLMS Algorithm with Dynamic Response Control. 29th IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND MACHINE VISION IN PRACTICE (pp. 1-5).

Ardekani, Iman., Varastehpour, Soheil., & Sharifzadeh, Hamid. (2023). Real-time swarming detection in honeybees: Leveraging audio signal processing and machine learning techniques. The Journal of the Acoustical Society of America, 154, 1-5. https://doi.org/10.1121/10.0023330

Sharifzadeh, H., Varastehpour, S., Francis, X., Keivanmarz, A., Fleming, R., Ardekani, I., & Newton, A. (2022, November). Aiding Forensic Investigations using Machine Learning [Paper presentation]. The 2022 Artificial Intelligence Researchers Association, Christchurch, New Zealand.

Kaur, Manjit., Ardekani, Iman., Sharifzadeh, Hamid., & Varastehpour, Soheil. (2022). A CNN-Based Identification of Honeybees’ Infection using Augmentation. Proceeding of the International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) 16-18 November 2022, Maldives (pp. 1-6).

Ardekani, Iman., Varastehpour, Soheil., & Sharifzadeh, Hamid. (2022). Acoustic signal processing systems for intelligent beehive monitoring. Conference of the Acoustical Society of New Zealand (pp. 1-4).

Ardekani, Iman., Sharifzadeh, Hamid., & Varastehpour, Soheil. (2022). Bayesian Active Noise Control. Conference of the Acoustical Society of New Zealand (pp. 1-6).

Ardekani, Iman., Sharifzadeh, Hamid., & Varastehpour, Soheil. (2022). Practical Active Noise Control Algorithms in Bayesian Inversion Framework. Proceeding of the International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) 16-18 November 2022, Maldives (pp. 7-13).

Varastehpour, Soheil., & Sharifzadeh, Hamid. (2021, December). Visualising Vein Pattern using Deep Learning for Forensic Investigation [Paper presentation]. Rangahau Horonuku Hou - 2021 MIT/Unitec Research Symposium, Auckland, New Zealand.

Varastehpour, Soheil., Sharifzadeh, Hamid., & Ardekani, Iman. (2021). A Comprehensive Review of Deep Learning Algorithms. 1-29. Auckland, New Zealand. Shannon, M.

Varastehpour, Soheil. (2020). Visualising Vein Pattern Based on Sparse Auto-Encoder Algorithm [Doctoral thesis,Unitec Institute of Technology]

Varastehpour, Soheil., Sharifzadeh, Hamid., Ardekani, Iman., & Sarrafzadeh, Abdolhossein. (2020). Human Biometric Traits: A Systematic Review Focusing on Vascular Patterns. In Shannon, M. (Eds.), Occasional and Discussion Papers Series (2020:3) (pp. 1-33). Auckland, New Zealand.

Xavier, F., Sharifzadeh, H., Angus, N., Baghaei, N., & Varastehpour, S. (2019). Learning Wear Patterns on Footwear Outsoles Using Convolutional Neural Networks. The 18th IEEE International Conference on Trust, Security.

Varastehpour, S., Sharifzadeh, H., Ardekani, I., Baghaei, N., & Francis., X. (2019). An Adaptive Method for Vein Recognition Enhancement Using Deep Learning. IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY, Ajman, United Arab Emirates.

Francis., X., Sharifzadeh, H., Newton., A., Baghaei, N., & Varastehpour, S. (2019). Feature Enhancement and Denoising of a Forensic Shoeprint Dataset for Tracking Wear-And-Tear Effects. IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY, Ajman, United Arab Emirates.

Varastehpour, S., Sharifzadeh, H., Ardekani, I., & Francis., X. (2019). Vein Pattern Visualisation and Feature Extraction Using Sparse Auto-encoder for Forensic Purposes. The 16-th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS), Taipei, Taiwan.

Varastehpour, S., Sharifzadeh, H., Ardekani, I., & Xavier, F. (2018). A Review of Biometric Traits with Insight into Vein Pattern Recognition. In 16th Annual Conference on Privacy.