Nastaran Mehrabi Hashjin | Artificial intelligence | Best Researcher Award

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Mr. Nastaran Mehrabi Hashjin | Artificial intelligence | Best Researcher Award

Mr at Shahid beheshti university Iran

Nastaran Mehrabi Hashjin is a researcher and engineer with a background in control and electronic engineering. She specializes in AI, medical imaging, and brain-computer interfaces. With a focus on diagnosing Alzheimer’s disease and optimizing AI algorithms, she has published multiple articles in top-tier journals. Nastaran has also contributed to UAV monitoring and fault detection in power systems. A member of Iranā€™s National Elite Foundation, she actively engages in research on neural networks, optimization algorithms, and advanced medical data processing. She is proficient in programming, circuit design, and VLSI systems, showcasing her technical acumen.

Profile

Scopus

Orcid

Scholar

šŸŽ“ Education

Ph.D. Candidate, Control Engineering (2023-2024) Shahid Beheshti University, Tehran, Iran | Elite Foundation Member. M.Sc. in Control Engineering (2021-2024) Shahid Beheshti University, Tehran, Iran | GPA: 3.54/4.0 | Alzheimerā€™s diagnosis using neural networks. B.Sc. in Electronic Engineering (2016-2020) Shomal University, Amol, Iran | GPA: 3.52/4.0 | PIR sensor system design

šŸ’¼ Experience

Graduate: System Identification, Non-linear Control, Modern Systems. Undergraduate: Electromagnetism, Electrical Machines, Labs Engineer, Tarashe Pardazane Jahan. Designed electronic circuits for smart doors. Intern, Mazandaran Electric Company. Energy distribution monitoring and operational map updates.

šŸ† Awards and Honors

Member, Iranā€™s National Elite Foundation. Ph.D. admission via Elite Foundation. Certifications in neuroscience and medical imaging (TUMS). Advanced neuroscience and AI courses (Shahid Beheshti University)

šŸ”¬ Research Focus

AI-driven fault detection in power plants. Brain-computer interfaces and Alzheimer’s diagnostics. Optimization algorithms: Type-3 fuzzy logic, HO algorithm. Medical imaging: FSL, CONN, Freesurfer

šŸŒŸ Conclusion

Nastaran Mehrabi Hashjin is an exemplary candidate for the Best Researcher Award due to their innovative contributions to AI-driven fault diagnosis, optimization, and medical imaging. Their rigorous academic record, diverse expertise, and impactful publications make them a strong contender. Addressing minor gaps in global collaboration and community engagement will further enhance their standing as a leader in their field.

Publications šŸ“š

Bhanu Shrestha | Computer Science | Best Researcher Award

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Prof. Bhanu Shrestha | Computer Science | Best Researcher Award

Professor at Kwangwoon University, South Korea

Bhanu Shrestha is a Full Professor at Kwangwoon University, Korea. He holds expertise in electronic engineering with a background in various academic and professional roles, including Assistant and Associate Professorships at the same institution. A native of Nepal, he is passionate about research, education, and cultural exchange. Bhanu has also published books, research papers, and contributed to documentaries and music albums. His involvement extends to editorial positions, being Editor-in-Chief of the International Journal of Advanced Engineering since 2018. He is known for his academic and social contributions, particularly in the field of information technology and engineering.

 

Profile

Scopus

Orcid

Ā šŸŽ“ Education

Ph.D. in Electronic Engineering, Kwangwoon University, Seoul, Korea (2004-2008). M.S. in Electronic Engineering, Kwangwoon University, Seoul, Korea (2002-2004). B.S. in Electronic Engineering, Kwangwoon University, Seoul, Korea (1994-1998). S.L.C. from Bhim Secondary School, Dolakha, Nepal (1982)

šŸ’¼ Experience

Adjunct Professor, Kwangwoon University, Korea (2008-2011). Assistant Professor, Kwangwoon University, Korea (2011-2016). Associate Professor, Kwangwoon University, Korea (2016-2021). Full Professor, Kwangwoon University, Korea (2021-Present). Bhanu Shrestha has held various academic positions, contributing significantly to the field of electronic engineering and nurturing the next generation of engineers. He has also been involved in leadership roles in professional organizations.

šŸ† Awards and Honors

Achievement Award, IIBC Korea (2015). Best Paper Award, ISSAC 214 & ICACT 2014, IIBC, Seoul, Korea (2014). Excellent Paper Award, Korea Institute of Information Technology (2012). Certificate of Honorary Citizenship, Seong-buk District Office, Seoul, Korea (2012). Bellwave Excellent Paper Award, Korea Electromagnetic Engineering Society (2005). Vidhyabhusan Padak (Gold Medal), Nepal (2009) Bhanu has earned several prestigious awards, recognizing his academic excellence and contributions to research and development in engineering.

šŸ”¬ Research Focus

Bhanu Shrestha’s research interests include Internet of Things (IoT), artificial intelligence (AI), microelectromechanical systems (MEMS), and fuzzy logic applications in communication technology. His work also explores biosensors and nanotechnology for environmental remediation. As a guest editor for multiple journals, Bhanu’s research aims to push the boundaries of innovation in electronic engineering and its practical applications, particularly in smart systems and AI.

Conclusion

Bhanu Shresthaā€™s contributions to electronic engineering and technology, coupled with his leadership in academia, make him a highly deserving candidate for the Best Researcher Award. His accomplishments in publishing influential works, along with his global impact in the fields of artificial intelligence, IoT, and nanotechnology, showcase his research excellence. With continued collaboration and expansion into emerging areas, he is well-positioned to make even more significant strides in the scientific community, further cementing his legacy as a top researcher.

Publications šŸ“š

Hyung-Pil Chang | Deep Learning | Best Researcher Award

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Mr. Hyung-Pil Chang | Deep Learning | Best Researcher Award

Mr at Korea University,Ā  South Korea

Hyung-pil Chang is a dedicated graduate student at Korea University, pursuing a Ph.D. in Computer Science and Engineering. With a keen interest in deep learning and speech processing, he focuses on enhancing communication between humans and machines. He has contributed to several innovative projects in voice conversion and speech recognition, demonstrating a commitment to advancing technology in these fields. In addition to his academic pursuits, Chang actively engages in various sports and cultural activities, reflecting a well-rounded personality. His passion for research is complemented by his desire to develop practical solutions for real-world problems in artificial intelligence.

Profile

Scopus

Orcid

Scholar

Education šŸŽ“

Hyung-pil Chang began his academic journey at Hansung University, where he earned a Bachelor of Science in Information System and Engineering from March 2014 to February 2020. He continued his studies at Korea University, obtaining a Master of Science in Computer Science and Engineering from 2020 to 2022. Currently, he is pursuing his Doctor of Philosophy in the same field at Korea University, enhancing his knowledge and expertise in deep learning, speech recognition, and human-computer interaction.

Experience šŸ’¼

Chang has gained valuable experience as a research assistant at Korea University’s Artificial Intelligence Laboratory since March 2020, working under the guidance of Prof. Dongsuk Yook. He has also served as a teaching assistant for undergraduate courses in Artificial Intelligence and Machine Learning, honing his teaching skills and sharing his knowledge with students. Additionally, he briefly worked in the Voice Generation Team at KT on a multi-modal project, where he contributed to advancements in voice conversion technologies, further solidifying his practical experience in the field.

Awards and Honors šŸ†

Hyung-pil Chang has received recognition for his academic and research achievements, including publications in reputable journals such as MDPI Applied Sciences and IEEE Access. His contributions to voice conversion and speaker anonymization research have garnered attention in the field of speech processing. While specific awards are not listed, his active participation in conferences and collaboration on innovative projects highlight his commitment to excellence in research and development, positioning him as an emerging talent in artificial intelligence and deep learning.

Research Focus šŸ”¬

Changā€™s research centers on enhancing communication between people and machines, particularly in speech processing. He aims to improve speech recognition models using self-training techniques on large amounts of unlabeled data. His work also explores explainable AI and the development of a general-purpose domain agent capable of interacting with humans across various tasks, including vision and natural language processing. Key areas of focus include speech recognition, synthesis, voice conversion, and human-computer interaction, contributing to advancements in multi-modal language models.

šŸ“ Conclusion

Hyung-pil Chang demonstrates strong potential as a leading researcher in deep learning and speech processing. His academic background, research contributions, and innovative spirit position him well for the Best Researcher Award. By focusing on collaboration, expanding his publication record, and engaging more with the broader community, he can enhance his impact even further. Given his current trajectory, he is well on his way to making significant contributions to his field and is a worthy candidate for recognition.

Publications Top Notes

  • Wav2wav: Wave-to-Wave Voice Conversion
    C Jeong, H Chang, IC Yoo, D Yook
    Applied Sciences, 2024, 14(10), 4251.

 

  • Zero-Shot Unseen Speaker Anonymization via Voice Conversion
    HP Chang, IC Yoo, C Jeong, D Yook
    IEEE Access, 2022, 10, 130190-130199.

 

  • CycleDiffusion: Voice Conversion Using Cycle-Consistent Diffusion Models
    D Yook, G Han, HP Chang, IC Yoo
    Applied Sciences, 2024, 14(20), 9595.

 

 

 

ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

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Mr. ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

PHD at SWINBURNE UNIVERSITY OF TECHNOLOGY SARAWAK CAMPUS Malaysia

Abel Chai Yu Hao is a PhD candidate at Swinburne University of Technology Sarawak, specializing in computer vision, machine learning, and deep learning. His research focuses on developing interpretable deep learning models for plant disease identification, collaborating with CIRAD and INRIA on innovative agricultural projects. With a Masterā€™s degree in wireless communication, Abel has contributed to improving rural connectivity in Sarawak through cost-effective wireless solutions. He has co-authored numerous journal articles and conference papers on topics ranging from unseen plant disease recognition to wireless data transmission. Abel is a recipient of multiple awards, including the Gold Award at the Innovation Technology Exposition 2023, and is an active IEEE member.

scholar

šŸŽ“ Education

Doctor of Philosophy (2022 – Present) Swinburne University of Technology Sarawak Campus Research focus: Computer Vision, Machine Learning, Deep Learning, AI. Master of Engineering (2019 – 2021) Swinburne University of Technology Sarawak Campus Research focus: Wireless communication, Wi-Fi, Rural connectivity. Bachelor of Engineering (Honours), Electrical & Electronics Engineering (2014 – 2018) Swinburne University of Technology Sarawak Campus CGPA: 3.97/4 (High Distinction)

šŸ« Professional Experience

Teaching Assistant (2019 – Present) Swinburne University of Technology Sarawak Campus Assisting in course delivery, tutorials, and research guidance

šŸ† Awards & Scholarships

Gold Award in Innovation Technology Exposition (2023). Best Paper Award at International UNIMAS Engineering Conference (EnCon) (2020). Sarawak Energy External Scholarship (2015-2018). Swinburne Entrance Scholarship (2014)

šŸŒ± Research Projects

Plant Disease Identification with Deep Learning (2022 – ongoing) Collaborating with experts from CIRAD, INRIA, focusing on AI-based plant disease detection. Rural Internet Connectivity Solutions (2019 – 2021) Conducted cost-performance analysis for wireless solutions in partnership with Sarawak Multimedia Authority (SMA)

Publication

  • Pairwise Feature Learning for Unseen Plant Disease Recognition
    Conference: International Conference on Image Processing (ICIP)
    Year: 2023
    Pages: 306ā€“310
    Contributors: Hao Chai A.Y., Han Lee S., Tay F.S., Bonnet P., Joly A.

 

  • Unveiling Robust Feature Spaces: Image vs. Embedding-Oriented Approaches for Plant Disease Identification
    Conference: Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
    Year: 2023
    Pages: 666ā€“673
    Contributors: Ishrat H.A., Chai A.Y.H., Lee S.H., Then P.H.H.

 

  • Development and Application of Outdoor Router Cost Estimation with Parametric Modelling Technique
    Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
    Year: 2022
    Contributors: Chai A.Y.H., Lai C.H., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

 

  • Model Study for Outdoor Data Transmission Performance
    Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
    Year: 2022
    Contributors: Chai A.Y.H., Then Y.L., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

 

  • Parametric Model Study for Outdoor Routers Cost Estimation
    Conference: 13th International UNIMAS Engineering Conference (EnCon)
    Year: 2020
    Contributors: Hao Chai A.Y., Hung Lai C., Su H.T., Siang Tay F., Yong L.

šŸ† Conclusion:

Abel Chai Yu Hao is a highly qualified candidate for the Best Researcher Award, given his solid academic background, impactful publications, international collaborations, and ongoing contributions to the field of AI and wireless communication. With continuous focus on expanding his research and increasing engagement, his profile can only continue to rise.

seyed matin malakouti | AI | Best Researcher Award

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seyed matin malakouti | AI | Best Researcher Award

Seyed Matin Malakouti is an accomplished Electrical Engineering professional specializing in machine learning and control systems. He holds an MS in Control System Engineering from the University of Tabriz and a BS in Electrical Engineering from Isfahan University of Technology. Malakouti has published extensively on topics including wind power prediction, temperature change modeling, and heart disease classification. His work has appeared in prominent journals such as Energy Exploration & Exploitation and Case Studies in Chemical and Environmental Engineering. He has received recognition for his research, including awards for Best Researcher and nominations for Best Paper. Malakoutiā€™s research interests span applied machine learning, renewable energy, and biomedical signal processing. He is also an active peer reviewer for various scientific journals.

Publication profile

google scholar

šŸŽ“ Education

MS in Electrical Engineering ā€“ Control System Engineering University of Tabriz, Tabriz, Iran (2019 – 2022). BS in Electrical Engineering
Isfahan University of Technology (IUT), Isfahan, Iran (2014 – 2019)

šŸ¢ Professional Experience

Undergraduate Teaching Assistant Dept. of Electrical Engineering, Isfahan University of Technology (IUT) (2015 – 2018) Assisted in teaching core courses such as Calculus I, II, Electrical Circuit I, II, and Electronics II.

šŸ† Awards & Fellowships

Best Researcher, International Conference on Cardiology and Cardiovascular Medicine (2023). Nominated for Best Paper Award, International Research Awards on Mathematics and Optimization Methods (2023)

šŸ‘Øā€šŸ« Teaching Experience

Spring 2018: Calculus I, Teaching Assistant. Spring 2017: Calculus II, Teaching Assistant. Fall 2016: Electrical Circuit I, Teaching Assistant. Spring 2015: Electrical Circuit II, Teaching Assistant

Research for Best Researcher Award: Seyed Matin Malakouti

šŸŒŸ Strengths for the Award

  1. Diverse Research Contributions: Seyed Matin Malakouti has an extensive list of publications covering a broad range of topics, from wind power generation and temperature change prediction to heart disease classification and asteroid detection. This indicates a high level of versatility and a strong ability to apply machine learning across different domains.
  2. Cutting-Edge Techniques: His work utilizes advanced machine learning techniques such as CNN-LSTM, ensemble methods, and Bayesian optimization. This demonstrates a commitment to leveraging state-of-the-art methods to address complex problems.
  3. High-Impact Publications: Malakouti has published in high-impact journals such as Energy Exploration & Exploitation, Biomedical Signal Processing and Control, and Case Studies in Chemical and Environmental Engineering. His work is also recognized by prestigious conferences and has received nominations for awards.
  4. Peer Review Engagement: Active involvement in peer review for numerous reputable journals reflects his expertise and recognition within the academic community.
  5. Awards and Recognition: Being named the Best Researcher at an international conference and receiving nominations for best paper awards highlights his research’s quality and impact.

šŸ” Areas for Improvement

  1. Broader Impact Assessment: While his technical contributions are substantial, including a focus on how his research impacts broader societal and industrial contexts could further enhance his profile. Emphasizing real-world applications and collaborations could demonstrate the practical significance of his work.
  2. Interdisciplinary Collaboration: Engaging in interdisciplinary projects could further enrich his research profile. Collaborating with researchers from other fields, such as environmental science or healthcare, could lead to innovative solutions and increase the impact of his work.
  3. Public Engagement and Outreach: Increasing efforts in public science communication and outreach could help bridge the gap between academic research and public understanding. Engaging with non-academic audiences through popular science articles, talks, or educational programs could be beneficial.

Publication top notes

  1. Title: Predicting wind power generation using machine learning and CNN-LSTM approaches
    Citations: 46
    Year: 2022
    Journal: Wind Engineering 46(6), 1853-1869

 

  1. Title: Heart disease classification based on ECG using machine learning models
    Citations: 39
    Year: 2023
    Journal: Biomedical Signal Processing and Control 84, 104796

 

  1. Title: Utilizing time series data from 1961 to 2019 recorded around the world and machine learning to create a Global Temperature Change Prediction Model
    Citations: 37
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 7, 100312

 

  1. Title: The usage of 10-fold cross-validation and grid search to enhance ML methods performance in solar farm power generation prediction
    Citations: 32
    Year: 2023
    Journal: Cleaner Engineering and Technology 15, 100664

 

  1. Title: Use machine learning algorithms to predict turbine power generation to replace renewable energy with fossil fuels
    Citations: 26
    Year: 2023
    Journal: Energy Exploration & Exploitation 41(2), 836-857

 

  1. Title: Evaluation of the application of computational model machine learning methods to simulate wind speed in predicting the production capacity of the Swiss basel wind farm
    Citations: 21
    Year: 2022
    Journal: 2022 26th International Electrical Power Distribution Conference (EPDC), 31-36

 

  1. Title: Improving the prediction of wind speed and power production of SCADA system with ensemble method and 10-fold cross-validation
    Citations: 19
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 8, 100351

 

  1. Title: Estimating the output power and wind speed with ML methods: a case study in Texas
    Citations: 17
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 7, 100324

 

  1. Title: Babysitting hyperparameter optimization and 10-fold-cross-validation to enhance the performance of ML methods in Predicting Wind Speed and Energy Generation
    Citations: 15
    Year: 2023
    Journal: Intelligent Systems with Applications 19, 200248

 

  1. Title: AERO2022-flying danger reduction for quadcopters by using machine learning to estimate current, voltage, and flight area
    Citations: 15
    Year: 2022
    Journal: e-Prime-Advances in Electrical Engineering, Electronics and Energy 2, 100084

 

  1. Title: Prediction of wind speed and power with LightGBM and grid search: case study based on Scada system in Turkey
    Citations: 8
    Year: 2023
    Journal: International Journal of Energy Production and Management 8.

 

šŸ† Conclusion

Seyed Matin Malakouti is a strong candidate for the Research for Best Researcher Award due to his diverse and impactful research contributions, utilization of advanced machine learning techniques, and recognition within the academic community. By focusing on broader impact, interdisciplinary collaboration, and public engagement, he can further enhance his research profile and increase the overall impact of his work.

Sayandeep Dutta | Computer Science | Young Scientist Award

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Ā Mr. Sayandeep Dutta | Computer Science | Young Scientist AwardĀ 

Mr. Doon Heritage School, India

šŸ‘©ā€šŸ”¬Driven by a passion for entrepreneurship and cybersecurity, aims to excel as a developer and analyst, leveraging diverse skills in machine learning and creative writing. With a track record of achievements, including prestigious awards and contributions to projects like Krishi Sarthi and OWASP Juice Shop, they possess a strong foundation in tech innovation. As founder of Krishi Sarthi and a penetration tester, they combine technical expertise with leadership in organizing cybersecurity events. Certified in HTML and web application penetration testing, they exhibit a keen aptitude for continuous learning and advancement in the field.šŸŒŸ

 

Profile

 

orcid

 

šŸš€Ā Career Aspiration

Aspiring to excel as an entrepreneur, developer, and cybersecurity analyst, I aim to reach the pinnacle of success in my chosen field. With a diverse background in projects ranging from NFT artistry to ethical hacking and machine learning development, I strive to make a significant impact in the tech industry. Recognized for my dedication, I continuously engage with communities and contribute to public development research.

šŸŽ“ Ā Education

  • High School Diploma (Class 10) ā€“ Jermelā€™s Academy, Siliguri (Apr 2011 ā€“ Apr 2022)
  • High School Senior Diploma (Class 12) ā€“ Doon Heritage School, Siliguri (Apr 2022 ā€“ Apr 2024)

šŸ† Ā Achievements

  • Nomination for Pradhan Mantri Rashtriya Bal Puraskar 2024
  • Youngest Participant at Young Scientist Conference, IISF 2023
  • Global Digital Innovation Award 2023

šŸ”Project Details

KrishiSarthi: Developed a project for calculating crop yield per hectare using geographical data. Bugbase Hall Of Fame: Recognized for contributions to bug bounty programs. CVE Issuances: Discovered and reported security vulnerabilities in web applications.

šŸ› ļøProjects

  • OWASP Juice Shop (Contributed): A sophisticated insecure web application for security training.
  • DialDetect (Self): A phone number details finder tool providing comprehensive information.

šŸ’¼Work Experience

Founder, KrishiSarthi: Calculated Crop Yield per hectare using geographical data. Content Writer, MAGICSTEP SOLUTIONS PRIVATE LIMITED: Learned project management and teamwork. Penetration Tester, WPScan – WordPress Security: Discovered CVEs and contributed to cybersecurity magazines. Team Leader, CyRaksha: Organized cybersecurity events to nurture talents. Digital Artist, OpenSea: Created NFTs and connected with other artists.

šŸ“œ Certification

HTML Workshop (2021). Technical Workshop on Web Application Penetration Testing (2023). High School Certificates – Certificate for n00bzCTF2023 (2023). Advance Javascript (2022). Effective Listening (2021)

šŸ”§ Ā Skill Highlights

Cybersecurity, Machine Learning, Creative Writing, Conference Speaking, Team Management

Publications Top Notes šŸ“

  • Development and bioavailability assessment of ramipril nanoemulsion formulation
    • Authors: S Shafiq, F Shakeel, S Talegaonkar, FJ Ahmad, RK Khar, M Ali
    • Journal: European journal of pharmaceutics and biopharmaceutics
    • Year: 2007
    • Volume: 66
    • Issue: 2
    • Pages: 227-243
    • Citations: 1006

 

  • Nanoemulsions as vehicles for transdermal delivery of aceclofenac
    • Authors: F Shakeel, S Baboota, A Ahuja, J Ali, M Aqil, S Shafiq
    • Journal: Aaps Pharmscitech
    • Year: 2007
    • Volume: 8
    • Pages: 191-199
    • Citations: 427

 

  • Formulation development and optimization using nanoemulsion technique: a technical note
    • Authors: S Shafiq-un-Nabi, F Shakeel, S Talegaonkar, J Ali, S Baboota, A Ahuja, …
    • Journal: AAPS pharmscitech
    • Year: 2007
    • Volume: 8
    • Pages: E12-E17
    • Citations: 420

 

  • Design, development and evaluation of novel nanoemulsion formulations for transdermal potential of celecoxib
    • Authors: S Baboota, F Shakeel, A Ahuja, J Ali, S Shafiq
    • Journal: Acta pharmaceutica
    • Year: 2007
    • Volume: 57
    • Issue: 3
    • Pages: 315-332
    • Citations: 397

 

  • A review on the strategies for oral delivery of proteins and peptides and their clinical perspectives
    • Authors: A Muheem, F Shakeel, MA Jahangir, M Anwar, N Mallick, GK Jain, …
    • Journal: Saudi Pharmaceutical Journal
    • Year: 2016
    • Volume: 24
    • Issue: 4
    • Pages: 413-428
    • Citations: 384

 

Mohammad Mohammadpour | Motion planning | Best Researcher Award

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Dr. Mohammad Mohammadpour | Motion planning| Best Researcher Award

Ā Dr. University of Quebec at Trois-RiviĆØres, Canada

šŸ‘©ā€šŸ”¬ Ph.D. in Mechanical Engineering with over eight years of specialized experience in R&D, contributing to cutting-edge projects at two renowned institutions.

 

Profile

Scopus

 

Education šŸŽ“

Ph.D. in Mechanical Engineering (Robotics), University of Quebec at Trois RiviĆØres, QC, Trois RiviĆØres, Canada; May 2019-Feb 2024Masterā€™s degree in Aerospace Engineering (Flight Dynamic & Control), Amirkabir University of Technology, Tehran, Iran; 2014Bachelor’s degree in Mechanical Engineering, Tehran, Iran; 2011

Skills šŸ› ļø

Programming Language: Python, C++Software: ROS, Gazebo, Rviz, MATLAB & Simulink Research: Navigation and Sensor Data Fusion Motion Planning (Guidance)Movement Sciences (Kinetic & Kinematic)Dynamic Modelling and Control Machine Learning and Deep Learning Obstacle Avoidance Applications: Autonomous Mobile Robots (simulation and experiment)Learning Frameworks: Scikit-learn, Keras, TensorFlow

Experience šŸš€ Robotics Engineer

Hydrogen Research Institute, University of Quebec at Trois RiviĆØres, Trois RiviĆØres, QC, Canada; 2019-2024Dynamic modeling, simulating, and analyzing robotsā€™ motion Implementing motion planning (guidance) algorithms on an Autonomous Mobile Robot and an Autonomous Forklift (simulation and experiment)Developing motion planning (guidance) algorithms using deep neural networks and the robotsā€™ kinetic models (simulation and experiment)Designing and implementing motion controllers (simulation and experiment). Research And Development Engineer Research Center of Amirkabir University of Technology, Tehran, Iran; 2015-2019Contributed to the Attitude Determination And Control System Executed MIL, SIL, PIL, and HIL simulation and testing Conducted operation and calibration tests of sensors Participated in dynamic modelling

Publications Top Notes šŸ“

i. Energy-efficient motion planning of an autonomous forklift using deep neural networks and kinetic model, Authors: M. Mohammadpour et al., 2023

 

ii. Energy-efficient Local Path Planning of a Self-Guided Vehicle by Considering the Load Position, Authors: Not provided, 2022

 

iii. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots, Authors: M. Mohammadpour et al., 2021

 

 

Computer Science

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Introduction of Computer ScienceĀ 

Computer Science research is at the forefront of innovation and technology, shaping the digital landscape and driving advancements that impact virtually every aspect of our lives. It encompasses a wide array of subfields, each with its unique challenges and opportunities

Artificial Intelligence (AI)

AI research focuses on creating intelligent systems capable of learning, reasoning, and making decisions. It has far-reaching applications in autonomous vehicles, natural language processing, image recognition, and healthcare, among others, revolutionizing how we interact with technology.

Cybersecurity

Cybersecurity research is vital for protecting digital assets and privacy in an increasingly connected world. Researchers in this field work on developing robust encryption techniques, intrusion detection systems, and threat mitigation strategies to safeguard data and networks from cyberattacks.

Machine Learning

Machine Learning is a subset of AI that emphasizes the development of algorithms capable of improving their performance over time through data analysis. It has led to breakthroughs in predictive analytics, recommendation systems, and personalized medicine, enhancing decision-making processes across industries.

Quantum Computing

Quantum computing research explores the potential of quantum bits (qubits) to perform complex calculations exponentially faster than classical computers. This subfield has the potential to revolutionize cryptography, optimization problems, and material science, unlocking new frontiers in computational power.

Data Science and Big Data

Data Science research focuses on extracting valuable insights from vast and complex datasets. Researchers in this area develop data-driven models, algorithms, and visualization tools to tackle real-world problems in fields like finance, healthcare, and social sciences, facilitating data-informed decision-making.

Computer Science

Posted on by ScienceFather

Introduction of Computer ScienceĀ 

Computer Science research is at the forefront of innovation and technology, shaping the digital landscape and driving advancements that impact virtually every aspect of our lives. It encompasses a wide array of subfields, each with its unique challenges and opportunities

Artificial Intelligence (AI)

AI research focuses on creating intelligent systems capable of learning, reasoning, and making decisions. It has far-reaching applications in autonomous vehicles, natural language processing, image recognition, and healthcare, among others, revolutionizing how we interact with technology.

Cybersecurity

Cybersecurity research is vital for protecting digital assets and privacy in an increasingly connected world. Researchers in this field work on developing robust encryption techniques, intrusion detection systems, and threat mitigation strategies to safeguard data and networks from cyberattacks.

Machine Learning

Machine Learning is a subset of AI that emphasizes the development of algorithms capable of improving their performance over time through data analysis. It has led to breakthroughs in predictive analytics, recommendation systems, and personalized medicine, enhancing decision-making processes across industries.

Quantum Computing

Quantum computing research explores the potential of quantum bits (qubits) to perform complex calculations exponentially faster than classical computers. This subfield has the potential to revolutionize cryptography, optimization problems, and material science, unlocking new frontiers in computational power.

Data Science and Big Data

Data Science research focuses on extracting valuable insights from vast and complex datasets. Researchers in this area develop data-driven models, algorithms, and visualization tools to tackle real-world problems in fields like finance, healthcare, and social sciences, facilitating data-informed decision-making.