Amar Salehi | Reinforcement Learning | Best Researcher Award

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Dr. Amar Salehi | Reinforcement Learning | Best Researcher Award

Dr. Amar Salehi is a postdoctoral researcher at South China University of Technology 🇨🇳, specializing in microrobotics 🤖, AI 🧠, and biosystems engineering 🌱. With a Ph.D. in Mechanical Engineering of Biosystems 🎓 from the University of Tehran 🇮🇷, he developed intelligent and independent control systems for magnetic microrobots. His work integrates machine learning, deep learning, and bio-inspired design for environmental and biomedical applications 🌍🧬. Passionate about innovation, he has contributed to several peer-reviewed journals 📚, international conferences 🌐, and interdisciplinary projects. He also served as a teaching assistant and reviewer and held leadership roles in scientific societies 👨‍🏫. A top-ranked scholar in national entrance exams 🏆, Dr. Salehi actively collaborates across borders for research and development in cutting-edge AI and robotics 🔬.

Profile

Education 🎓

Dr. Salehi earned his Ph.D. in Mechanical Engineering of Biosystems 🎓 from the University of Tehran (2019–2024), focusing on intelligent magnetic microrobot control 🤖. He completed his M.S. at Isfahan University of Technology (2013–2015) 🧪, where he explored fluid heat transfer using CFD methods and mechanical behavior modeling with neural networks. His B.S. was from Razi University (2008–2012) in Biosystems Mechanical Engineering 🔧🌾. A consistent top performer, he ranked 2nd in the Ph.D. entrance exam and 90th in the M.S. exam among thousands 🏅. His academic record features exceptional GPAs and thesis scores 🌟. Dr. Salehi’s interdisciplinary education blends mechanical systems, AI, and biology, building a strong foundation for his current microrobotics and biosensor research 🔬📊.

Experience 👨‍🏫

Experience (150 words): Dr. Salehi is currently a Postdoctoral Fellow at the Shien-Ming Wu School of Intelligent Engineering, South China University of Technology 🇨🇳 (2024–present), working on intelligent agents and microrobotics 🤖. Previously, he was a teaching assistant at the University of Tehran, supporting physics and mechanical engineering courses 👨‍🏫. He also taught part-time at Azad University, Iran (2016–2019) 📘. As a research assistant at the AIAX Lab, he contributed to AI and advanced control systems. He led several interdisciplinary projects, including a joint Iran-Turkey research on microfluidic biochips 🧫. A reviewer for “The Innovation” journal, he is proficient in tools like COMSOL, SolidWorks, Python, and statistical analysis 📊🖥️. He also chaired a student startup “Green Daal Mechanics” and served in university and parliamentary scientific committees 🚀📈.

Awards & Recognitions 🏅

Awards and Honors (150 words): Dr. Salehi received the Best Oral Presentation Award 🥇 at IRAC 2024 for his work on deep learning and microrobots 🤖. Ranked 2nd in the national Ph.D. entrance exam and 90th in the M.S. exam, he also achieved excellent scores in his thesis evaluations (Ph.D.: 19.65/20, M.S.: 19.49/20) 🏆. His academic and research excellence has earned him recognition in national and international forums 📜. He has been an active member of the Scientific Association of Biosystems Engineering and the Interdisciplinary Scientific Student Association at the University of Tehran 🧠. He also served as Editor-in-Chief of the New Green Industry Journal 🌱. With strong leadership in university-industry interaction, he contributes to Iran’s agricultural, food, and energy research panels and policy discussions 🧑‍🔬📢.

Research Interests 🔬

.Research Focus (150 words): Dr. Salehi’s research lies at the intersection of microrobotics 🤖, artificial intelligence 🧠, and biosystems 🌱. His Ph.D. work focused on intelligent, model-free control of magnetic microrobots using deep reinforcement learning in real-world environments 🔍. He explores biosensor optimization using genetic algorithms 🧬, natural language interfaces for microrobot control 🗣️, and micro/nano-systems for biomedical and environmental applications 🌍. He integrates fuzzy logic, ANN, and reinforcement learning in his predictive modeling. Ongoing research includes yield prediction in intercropping systems 🌾 and AI-driven environmental cleanup technologies. Dr. Salehi’s goal is to create autonomous, intelligent microsystems that can navigate, sense, and interact with biological and physical environments, with potential applications in diagnostics, therapy, and sustainability 🧪♻️.

Publications 

 

 

 

Mahmoud Alimoradi | Machine Learning | Best Researcher Award

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Mr. Mahmoud Alimoradi | Machine Learning | Best Researcher Award

Lahijan Azad ,Iran

He understands the growing need for Machine Learning and has a keen interest in the field, which he considers a blessing. Recognizing the importance of managing large and complex computations to control various aspects of the human environment has led him into this vast world. He is particularly fascinated by machine learning, especially reinforcement learning, supervised learning, semi-supervised learning, outliers, and basic data challenges. Furthermore, optimization, an area of artificial intelligence that requires fundamental studies and a change in approach, is another of his key research interests.

Profile

Education

He holds a Master’s degree in Artificial Intelligence Engineering from the University of Shafagh, completed in 2020. His thesis was titled “Trees Social Relations Optimization Algorithm: A New Swarm-Based Metaheuristic Technique to Solve Continuous and Discrete Optimization Problems.” He also earned a Bachelor’s degree in Software Engineering from Azad Lahijan University, which he attended from 2007 to 2011.

Research Interests

Theory: Reinforcement Learning (high-dimensional problems, regularized algorithms, model
learning,
representation learning and deep RL, learning from demonstration, inverse optimal control, deep
Reinforcement Learning); Machine Learning (statistical learning theory, nonparametric
algorithms, time series. processes, manifold learning, online learning); Large-scale Optimization;
Evolutionary Computation, Metaheuristic Algorithm, Deep Learning, Healthcare Machine
learning, Big Data, Data Problems (Imbalanced), Signal Analysis
Applications: Automated control, space affairs, robotic control, medicine and health, asymmetric
data, data science, scheduling, proposing systems, self-enhancing systems

Work Experience

He is a freelance programmer with expertise in various operating systems, including Microsoft Windows and Linux (Arch, Ubuntu, Fedora). He is proficient in software tools such as Microsoft Office, Anaconda, Jupyter, PyCharm, Visual Studio, Tableau, RapidMiner, MATLAB, and Visual Studio. His programming skills include Matlab, Python, C++, Scala, Java, and Julia, with a focus on data mining, data science, computer vision, and machine learning. He is experienced with Python libraries like Pandas, Numpy, Matplotlib, Seaborn, PyCV, TensorFlow, Time Series Analysis, Spark, Hadoop, and Cassandra. Additionally, he is skilled in using Github, Docker, and MySQL. His expertise spans machine learning, deep learning, imbalanced data, missing data, semi-supervised learning, healthcare machine learning, algorithm design, and metaheuristic algorithms. He is fluent in English and Persian.

Publications