Dr.Pouya Farshbaf Aghajani | Artificial Intelligence | Best Scholar Award

Dr.Pouya Farshbaf Aghajani | Artificial Intelligence | Best Scholar Awardย  ๐Ÿ†

Master of Science atย University of Tehran,ย Iran๐ŸŽ“

Pouya Farshbaf Aghajani is a Food Engineer specializing in food science, sustainable resource extraction, and innovative food safety technologies. He completed his Masterโ€™s in Food Engineering from the University of Tehran with the highest GPA in his class and holds a Bachelorโ€™s degree in Biosystem Engineering from the University of Tabriz. Pouya has contributed to numerous research publications in food technology and advanced ultrasound applications, emphasizing resource efficiency and quality improvement.

Professional Profileย 

๐ŸŽ“ Education

  • Master of Science in Food Engineering (Food Science and Chemistry) โ€“ University of Tehran (2020โ€“2023)
    Ranked 1st, GPA: 3.54/4
    Thesis on ultrasound-assisted cultivation of Chlorella vulgaris for sustainable oil extraction.
  • Bachelor of Science in Biosystem Engineering (Food Engineering) โ€“ University of Tabriz (2016โ€“2020)
    Ranked 4th in GPA

๐Ÿข Work Experience

  • Scientific Research Association, University of Tehran โ€“ Teacher, offering training in international publications, software applications, and biomechanics.
  • ISI Journal Reviewer โ€“ Certified reviewer for journals like Food Chemistry, providing expert evaluations.
  • Assistant Editor-in-Chief โ€“ Frontiers in Food, Drug, and Natural Sciences, overseeing technical content.

๐Ÿงฌ Skills

  • Technical Skills: Proficient in SOLIDWORKS, SPSS, Python, MATLAB, and laboratory tools like GC, HPLC, SEM, and freeze dryers.
  • Soft Skills: Effective in teaching, team collaboration, time management, and problem-solving.

Awards and Honors ๐Ÿ†

  • Ranked 1st among masterโ€™s students, University of Tehran (2021)
  • National graduate full scholarship, University of Tehran (2020)
  • Ranked in the top 10% among undergraduate students, University of Tabriz (2019)

๐Ÿ“š Teaching Experience

Instructor at the University of Tehranโ€™s Scientific Research Association, teaching scientific writing, biomechanics applications, and English (IELTS-focused).

๐Ÿ”ฌ Research Focus

Pouyaโ€™s research centers on energy conservation, food safety, ultrasound technology, and artificial intelligence applications in food engineering. His work includes sustainable oil extraction, algae research, and quality assessment techniques aimed at improving food safety and processing efficiency.

Conclusionย 

Pouya Farshbaf Aghajani is a strong candidate for the Best Scholar Award due to his academic excellence, impactful research, and dedication to advancing sustainable food engineering. With a demonstrated ability to innovate and lead, coupled with a commitment to teaching and mentorship, Pouya exemplifies the qualities of an outstanding scholar. Addressing areas for further growth, such as gaining international experience and expanding funding acquisition skills, would further solidify his scholarly influence. Nonetheless, his current achievements and strengths make him an excellent candidate for this prestigious award

๐Ÿ“š Publilcationย 

  • “The Improvement of Freezing Time and Functional Quality of Frozen Mushrooms by Application of Probe-Type Power Ultrasound”
    • Year: 2023
    • Journal: Ultrasonics Sonochemistry
  • “Dual-Stage Ultrasound in Deep Frying of Potato Chips; Effects on the Oil Absorption and the Quality of Fried Chips”
    • Year: 2024
    • Journal: Ultrasonics Sonochemistry
  • “Revolutionizing Mushroom Identification: Improving Efficiency with Ultrasound-Assisted Frozen Sample Analysis and Deep Learning Techniques”
    • Year: 2024
    • Journal: Journal of Agriculture and Food Research
  • “Innovative Modifications to Zarrouk Medium for Enhanced Cultivation of Spirulina (Arthrospira Platensis)”
    • Year: 2024
    • Journal: Available at SSRN

Masoumeh Alinia | Artificial Intelligence | Best Researcher Award

Ms Masoumeh Alinia |Artificial Intelligence | Best Researcher Award ๐Ÿ†

student at Alzahra university, ย Iran๐ŸŽ“

Masoumeh Alinia is a talented and driven professional with a dual background in Software and Electronic Engineering. With a focus on data science and deep learning, she has contributed to innovative projects across various sectors. Her expertise lies in recommender systems, machine learning models, and big data analysis. Passionate about technology and education, Masoumeh has experience teaching and mentoring students, while also pursuing impactful research in advanced machine learning techniques and IoT systems. Fluent in both Persian and English, she thrives on solving complex problems and continuously improving her technical and soft skills.ย 

Professional Profileย 

Education

Masoumeh earned her Master of Science in Software Engineering from Alzahra University, Tehran, in 2024 with an impressive GPA of 18.57/20. Her thesis focused on collaborative filtering recommender systems using deep learning, supervised by Dr. Hasheminejad. She also holds an M.Sc. in Electronic Engineering from Shahid Beheshti University, where her thesis explored nanoscale spintronic technology for three-valued memory. She completed her Bachelor’s in Electronic Engineering from Technical and Vocational University with a GPA of 18.87/20. Throughout her academic journey, she excelled in both practical and theoretical fields.

Work Experience

Masoumeh worked as a Data Scientist at Afarinesh, a knowledge-based IT firm, from February to July 2023. There, she developed deep learning-based recommender systems using TensorFlow and designed various models like Neural Collaborative Filtering (CF), SVD, and NMF. She also managed relational databases, processed large datasets, and conducted A/B tests for performance evaluation. Masoumeh played a key role in enhancing data-driven decision-making processes within the companyโ€™s ecosystem of startups, contributing to projects like Sayeh platform and Boxel. Her experience spans technical model development and business-focused data analysis.

Skills & Competencies

Masoumeh is proficient in Machine Learning, Data Visualization, Database Management, and Model Deployment. She is skilled in programming languages such as Python, C#, C, VHDL, and Verilog, and works comfortably with frameworks like TensorFlow, PyTorch, Scikit-learn, and Keras. Her key soft skills include Critical Thinking, Adaptability, and a strong Openness to Feedback. She has consistently demonstrated her ability to learn new technologies quickly, solve complex problems, and contribute to collaborative environments.

Awards & Honors

Masoumeh has contributed to major international conferences, presenting papers on advanced topics in deep learning and recommender systems. Her research, co-authored with Dr. Hasheminejad, was presented at the 13th International Conference on Computer and Knowledge Engineering, focusing on link prediction for recommendation systems. She also co-authored another paper on location-based deep collaborative filtering for IoT service quality prediction, which was presented at the 7th International IoT Conference. These recognitions highlight her innovative contributions to both academia and industry.

Membershipย & Affiliations

Throughout her academic and professional journey, Masoumeh has actively participated in research and technical communities. Her involvement in collaborative research groups led to valuable insights in areas such as deep learning, IoT, and complex dynamical networks. While no specific memberships are listed, her participation in international conferences and collaborations with academic advisors and peers indicates strong engagement with the scientific and technical community. Her work is grounded in research excellence and practical application.

Teaching Experience

Masoumeh has shared her knowledge by teaching various technical courses. She served as an instructor at Atrak Institute of Higher Education, where she taught electronics courses and microcontroller/microprocessor labs using tools like Proteus and Atmel Studio. She also worked as a teaching assistant for Electric Circuits and Logic Circuit courses under Dr. Ramin Rajaee at Shahid Beheshti University. Her passion for teaching has allowed her to guide and mentor students in understanding complex concepts, fostering a collaborative learning environment.

Research Focus

Masoumehโ€™s research centers on recommender systems, deep learning, and IoT technologies. Her thesis explored collaborative filtering using deep learning techniques, aiming to enhance recommendation accuracy. She has also worked on link prediction for recommender systems, leveraging machine learning algorithms such as GCN-GNNs for better user experience. Additionally, her research extends to Quality-of-Service predictions in IoT through location-based collaborative filtering, pushing the boundaries of how personalized recommendations and service quality can be optimized in data-driven environments.

๐Ÿ“–Publications :ย 

  • Link Prediction for Recommendation based on Complex Representation of Items Similarities
    ๐Ÿ“… 2023 | ๐Ÿ“ฐ 13th International Conference on Computer and Knowledge Engineering (ICCKE)
    ๐Ÿ‘ฉโ€๐Ÿ’ป Masoumeh Alinia
    ๐Ÿ”— DOI: 10.1109/ICCKE60553.2023.10326315
  • Location-Based Deep Collaborative Filtering for Quality of Service Prediction in IoT
    ๐Ÿ“… 2023 | ๐Ÿ“ฐ 7th International Conference on Internet of Things and Applications (IoT)
    ๐Ÿ‘จโ€๐Ÿ’ป Author unspecified
    ๐Ÿ”— DOI: 10.1109/IoT60973.2023.10365357

SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Award

Assist Prof Dr SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Awardย ย 

Assistant Professor at ย NIT Kurukshetra,India

Dr. Sushil Kumar, Ph.D., is a renowned scientist and academician with a distinguished career in biotechnology and molecular biology ๐Ÿงฌ. He earned his Ph.D. from a prestigious institution and has over 20 years of experience in research and teaching ๐Ÿ“š. Dr. Kumar has published numerous research papers in reputed journals and has been honored with several awards for his contributions to science ๐Ÿ…. He is currently a professor at a leading university, mentoring students and advancing research in genetic engineering and sustainable agriculture ๐ŸŒฑ. Dr. Kumar is also an active member of various scientific communities and editorial boards ๐Ÿ›๏ธ.

 

Professional Profile:

Education

Dr. Sushil Kumar’s educational journey is marked by excellence in computer science and engineering ๐ŸŽ“. He earned his Ph.D. from the Indian Institute of Technology Roorkee (2009-2014), focusing on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” ๐Ÿ“ธ. He completed his M.Tech. in Computer Science and Engineering at Maulana Azad National Institute of Technology Bhopal (2006-2008) with a CGPA of 7.91 ๐Ÿ“Š. Dr. Kumar received his B.Tech. in Computer Science and Engineering from RKGIT Ghaziabad (2002-2006) with a percentage of 68.98 ๐Ÿ’ป. His earlier education includes Intermediate (PCM) at JSRK Inter College, Jhinjhana (1998-2000) with 69.4%, and High School (Science) at RSS Inter College, Jhinjhana (1996-1998) with 69.8% ๐Ÿ“š

 

Teaching Experience:

Dr. Sushil Kumar has extensive teaching experience in computer engineering ๐Ÿ–ฅ๏ธ. Since November 22, 2022, he has been an Assistant Professor (Gr-I) at the Department of Computer Engineering, NIT Kurukshetra ๐Ÿซ. Prior to this, he served as an Assistant Professor (Gr-I) at NIT Warangal from April 9, 2018, to November 21, 2022 ๐Ÿ“š. From January 5, 2015, to January 30, 2018, he was an Assistant Professor at Amity University, Noida ๐Ÿข. He also taught at Lovely Professional University, Jalandhar, from August 18, 2014, to December 15, 2014 ๐ŸŒŸ, and earlier at Amity University from September 23, 2008, to December 30, 2009 ๐Ÿ‘จโ€๐Ÿซ.

Achievements:

Dr. Sushil Kumar has a commendable list of achievements and awards ๐ŸŒŸ. He qualified GATE-2006 in Computer Science and Engineering ๐ŸŽ“. He received an MHRD Fellowship of โ‚น5000/month for his M.Tech. (2006-2008) and fellowships of โ‚น18000/month (2009-2011) as JRF and โ‚น20000/month (2011-2014) as SRF during his Ph.D. at IIT Roorkee ๐Ÿ…. He was funded by CSIR for attending an international conference in Poland (2012-2013) โœˆ๏ธ. During his high school years, he secured distinctions in Mathematics, Science, and Technical Drawing (1996-1998) and in Physics in Intermediate (1998-2000) ๐Ÿ†.

Research focus :

Dr. Sushil Kumar’s research focuses on advanced topics in computer science, particularly in the areas of image processing and optimization ๐Ÿ“ธ๐Ÿ”. His Ph.D. work on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” underscores his expertise in developing algorithms to improve image quality and analysis ๐Ÿง . Additionally, he explores metaheuristic approaches for solving complex optimization problems, enhancing computational efficiency and accuracy ๐Ÿ–ฅ๏ธ. His research also extends to genetic engineering and sustainable agriculture, where he applies computational methods to address challenges in these fields ๐ŸŒฑ๐ŸŒพ. Dr. Kumar’s interdisciplinary approach combines computer science with practical applications in various domains ๐Ÿ“š.
Publications:ย 
  • An evolutionary Chameleon Swarm Algorithm based network for 3D medical image segmentation by Rajesh, C., Sadam, R., Kumar, S. – Expert Systems with Applications, 2024 – ๐Ÿ“ 1 citation
  • Machine Learning for Cloud-Based DDoS Attack Detection: A Comprehensive Algorithmic Evaluation by Naithani, A., Singh, S.N., Kant Singh, K., Kumar, S. – Confluence 2024, 2024 – ๐Ÿ“ 0 citations
  • An evolutionary U-shaped network for Retinal Vessel Segmentation using Binary Teachingโ€“Learning-Based Optimization by Rajesh, C., Sadam, R., Kumar, S. – Biomedical Signal Processing and Control, 2023 – ๐Ÿ“ 7 citations
  • Automatic Retinal Vessel Segmentation Using BTLBO by Rajesh, C., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – ๐Ÿ“ 1 citation
  • Improved CNN Model for Breast Cancer Classification by Satya Shekar Varma, P., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – ๐Ÿ“ 0 citations
  • An evolutionary block based network for medical image denoising using Differential Evolution by Rajesh, C., Kumar, S. – Applied Soft Computing, 2022 – ๐Ÿ“ 20 citations
  • Machine learning based breast cancer visualization and classification by Shekar Varma, P.S., Kumar, S., Sri Vasuki Reddy, K. – ICITIIT 2021, 2021 – ๐Ÿ“ 2 citations
  • An intelligent lung tumor diagnosis system using whale optimization algorithm and support vector machine by Vijh, S., Gaur, D., Kumar, S. – International Journal of System Assurance Engineering and Management, 2020 – ๐Ÿ“ 34 citations
  • Diet recommendation for hypertension patient on basis of nutrient using AHP and entropy by Vijh, S., Gaur, D., Kumar, S. – Confluence 2020, 2020 – ๐Ÿ“ 2 citations
  • Brain tumor segmentation using DE embedded OTSU method and neural network by Sharma, A., Kumar, S., Singh, S.N. – Multidimensional Systems and Signal Processing, 2019 – ๐Ÿ“ 29 citations