Omid Hajipoor | Text Generation | Best Researcher Award

Mr. Omid Hajipoor | Text Generation | Best Researcher Award

Omid Hajipoor | Amirkabir University of Technology (Tehran Polytechnic) | Iran

Omid Hajipoor is a researcher in artificial intelligence with a strong focus on natural language processing, generative adversarial networks, and large language models. He is currently pursuing his PhD in Computer Engineering at Amirkabir University of Technology, Tehran, building on earlier academic training with a master’s in artificial intelligence and robotics from Malekashtar University and a bachelor’s in software engineering from Birjand University. His professional experience spans roles such as technical product manager, project manager, NLP team leader, and engineer, where he has contributed to the design and development of advanced NLP solutions, chatbots, social media text generation systems, error detection models, and sentiment lexicons. His research interests lie in text generation, adversarial learning, transformers, diffusion models, and applied AI systems for social media and multilingual contexts. He has been involved in impactful projects including railway optimization software, abusive language detection, and generative Persian text applications, and he has published in respected venues such as Neurocomputing and Scopus-indexed journals. In addition to his academic and industrial contributions, he has served as a teaching assistant and lecturer for undergraduate and postgraduate students, and he has mentored teams in innovation events that won recognition. His research skills include programming in Python, MATLAB, and C++, expertise in PyTorch, TensorFlow, and other machine learning frameworks, and strong experience in project management tools like Git and Docker. He has demonstrated leadership, creativity, and technical proficiency throughout his career. His research record shows citations by 2 documents from 1 publication with an h-index of 1.

Profile: Google Scholar | Scopus 

Featured Publications

Hajipoor, O., Nickabadi, A., & Homayounpour, M. M. (2025). GPTGAN: Utilizing the GPT language model and GAN to enhance adversarial text generation. Neurocomputing, 617, 128865.

Hajipoor, O., & Sadidpour, S. S. (2022). Automatic Persian text generation using rule-based models and word embedding. Electronic and Cyber Defense, 9(4), 43–54.

Hajipoor, O., & Sadidpour, S. S. (2020). Automatic keyword extraction from Persian short text using word2vec. Electronic and Cyber Defense, 8(2), 105–114.

Dr. Na Yi | Deep Metric Learning | Best Researcher Award

Dr. Na Yi | Deep Metric Learning | Best Researcher Award

Doctorate at Heilongjiang University of Science and Technology, China

Profiles

Scopus

Orcid

Academic Background

Dr. Na Yi, born in June 1997 in Acheng, Harbin, is an Associate Professor and a committed member of the Communist Party of China. With a strong academic foundation in Electrical Engineering and Automation, she has quickly risen as a prominent figure in the field of Petroleum and Natural Gas Engineering.

Education

Dr. Na Yi graduated with a degree in Electrical Engineering and Automation from Northeast Petroleum University in 2019. She was subsequently recommended for a doctoral program in Petroleum and Natural Gas Engineering, during which she also studied at Southeast University, earning her doctorate in 2024.

Professional Experience

Throughout her career, Dr. Na Yi has published over 20 research papers in esteemed journals, with 10 SCI-indexed and 5 EI-indexed papers, including highly cited and hot papers. She holds 6 national patents and has participated in 5 significant scientific research projects. Her achievements have earned her more than 10 national and provincial awards.

Research Interests

Dr. Na Yi’s research interests lie in Petroleum Engineering, with a focus on sustainable energy, power systems, and technological innovation. She is an active reviewer for multiple international and Chinese academic journals and has been invited to present her research at several international and domestic conferences.

 Publications

A multi-stage low-cost false data injection attack method for power CPS

  • Authors: Yi, N., Xu, J., Chen, Y., Pan, F.
  • Journal: Zhejiang Electric Power
  • Year: 2023
A New Distributed Power Supply for Distribution Network Considering SOP Access
  • Authors: Peng, C., Xu, J., Zhao, S., Yi, N.
  • Year: 2023
Multi-stage coordinated cyber-physical topology attack method based on deep reinforcement learning
  • Authors: Yi, N., Xu, J., Chen, Y., Sun, D.
  • Journal: Electric Power Engineering Technology
  • Year: 2023
A multi-stage game model for the false data injection attack from attacker’s perspective
  • Authors: Yi, N., Wang, Q., Yan, L., Tang, Y., Xu, J.
  • Journal: Sustainable Energy, Grids and Networks
  • Year: 2021
Insulator Self-Explosion Defect Detection Based on Hierarchical Multi-Task Deep Learning
  • Authors: Xu, J., Huang, L., Yan, L., Yi, N.
  • Journal: Diangong Jishu Xuebao/Transactions of China Electrotechnical Society
  • Year: 2021