Marco Cirillo | Interactive Analytics | Best Researcher Award

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Dr. Marco Cirillo | Interactive Analytics | Best Researcher Award

Non-Profit Polyambulance Foundation | Italy

Dr. Marco Cirillo is a distinguished cardiac surgeon whose career seamlessly bridges clinical excellence and experimental research. After completing classical studies, he graduated in Medicine and Surgery with highest honors  from the University of Bologna and specialized in Cardiac and Great Vessels Surgery. His career has encompassed leadership roles as Head of the Cardiac Surgery Unit in Bologna for six years and the Heart Failure Surgery Unit in Brescia for twelve years. With expertise spanning the full range of traditional cardiac surgery-including mitral repair, coronary bypass, valve replacement, and aortic arch procedures-Dr. Cirillo has performed over 8,000 surgeries as first surgeon. His innovative contributions include the KISS procedure for physiological left ventricular reconstruction, the “Arterial-source No-touch Aorta” technique for off-pump coronary revascularization, and the NINFEA method for annular stabilization in endocarditis. Renowned for his commitment to quality and risk management (JCI accreditation), he continues to advance the field through research on bioprostheses and ventricular assist systems, recognized internationally through publications and awards. In 2025, he earned a Master’s degree in Echocardiography from the University of Verona. Beyond medicine, his intellectual pursuits extend to writing, photography, and cosmology, where he recently published a paper exploring Darwinian natural evolution as applied to the development of the Universe.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

"Achilles and the Tortoise: Rethinking Evidence Generation in Cardiovascular Surgery and Interventional Cardiology", Marco Cirillo, Hearts, 2025.

"Abiotrophia defectiva and Granulicatella: A Literature Review on Prosthetic Joint Infection and a Case Report on defectiva PJI and Concurrent Native Valve Endocarditis", MCristina Seguiti; Edda Piacentini; Angelica Fraghì; Mattia Zappa; Elia Croce; Angelo Meloni; Marco Cirillo; Clarissa Ferrari; Chiara Zani; David Belli et al., Microorganisms, 2025.

"Finger ischemia in a young lady: an unusual presentation of papillary fibroelastoma with intraventricular location", Matteo Pernigo; Elisabetta Dinatolo; Marco Cirillo; Zean Mhagna; Alida Filippini; Fabiana Cozza; Marco Berti; Roberto Bazzani; Tony Sabatini; Claudio Cuccia et al., Monaldi Archives for Chest Disease, 2023.

"Exploring Personal Protection During High-Risk PCI in a COVID-19 Patient", Marco Cirillo, JACC: Case Reports, 2020.

Farhad Hossain Sojib | Data Science | Best Researcher Award

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Mr. Farhad Hossain Sojib | Data Science | Best Researcher Award 

University of Hull | Bangladesh

Mr. Farhad Hossain Sojib is an engineer with a strong foundation in electronics and communication engineering and a growing specialization in data science and artificial intelligence. He is currently pursuing his M.Sc. in Artificial Intelligence and Data Science at the University of Hull, United Kingdom, following the completion of his B.Sc. in Engineering from Hajee Mohammad Danesh Science and Technology University, Bangladesh, where he conducted notable research on explainable AI in educational data mining and machine learning applications in 5G antenna optimization. With professional experience as an IELTS Instructor at Lexicon Plus, he has trained over 50 students, developed course materials, and mentored junior instructors. His leadership and organizational skills were further demonstrated through his role as a Program Committee Member at the IEEE Student Branch, HSTU, where he managed events, seminars, and competitions. Additionally, his internship at BRACNet Limited provided hands-on experience in ISP operations, ICT technologies, and server management. Farhad combines his technical expertise, research acumen, and collaborative mindset to contribute meaningfully to the fields of machine learning and data-driven innovation.

Profiles: Orcid 

Featured Publications

"The integration of explainable AI in Educational Data Mining for student academic performance prediction and support systems", Md. Mahmudul Islam; Farhad Hossain Sojib; Md. Fazle Hasan Mihad; Mahmudul Hasan; Mahfujur Rahman, Telematics and Informatics Reports, 2025.

"A Bioinformatics Approach to Uncover Hub Genes and Potential Drug Targets of Stroke, Heart-Disease, Hyperglycemia, and Hypertension", Md. Emran Biswas; M D. Fazle Hasan Mihad; Farhad Hossain Sojib; Mohammad Jubair Ahmmed; M D Galib Hasan; Md. Jobare Hossain; Md. Abul Basar; Md. Mehedi Islam; Md. Delowar Hossain; Md. Selim Hossain et al., 27th International Conference on Computer and Information Technology (ICCIT), 2024.

"An Explainable Educational Data Mining System for Predicting Student Academic Performance", Md. Mahmudul Islam; Farhad Hossain Sojib; Md. Fazle Hasan Mihad; Mahmudul Hasan; Mahfujur Rahman; FARHAD HOSSAIN SOJIB, 2024 IEEE International Conference on Signal Processing, Information, Communication and Systems, 2024.

Touraj BaniRostam | Big Data | Best Researcher Award

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Assist. Prof. Dr. Touraj BaniRostam | Big Data | Best Researcher Award

Assistant Professor at University of Niagara Falls Canada, Canada📖

Dr. Touraj BaniRostam is a seasoned Computer Science and Artificial Intelligence (AI) expert with extensive academic and industry experience. Holding a Ph.D. in Computer Science, he is currently a Full-Time Faculty Member and Assistant Professor at the University of Niagara Falls, Canada. With a strong focus on AI, machine learning (ML), data analytics, and intelligent autonomous agents, Dr. BaniRostam is committed to advancing the fields of AI, cognitive science, and philosophy of AI. He has significantly contributed to the academic community, having supervised over 85 master’s and 5 Ph.D. students and published various impactful research works in AI, machine learning, cognitive science, and multi-agent systems.

Profile

Scopus Profile

Google Scholar Profile

Education Background🎓

  • Ph.D. in Computer Science – Science and Research Branch, Islamic Azad University, Tehran, Iran (Sep. 2006 – Sep. 2011)
  • M.Sc. in Philosophy of Science – Science and Research Branch, Islamic Azad University, Tehran, Iran (Sep. 2016 – Sep. 2019)
  • M.A. in Psychology – Islamic Azad University, Tehran, Iran (Feb. 2014 – Sep. 2016)
  • M.Sc. in Artificial Intelligence – Science and Research Branch, Islamic Azad University, Tehran, Iran (Sep. 2001 – Sep. 2004)
  • B.Sc. in Computer Hardware – Islamic Azad University, Central Tehran Branch, Tehran, Iran (Sep. 1996 – Jul. 2000)

Professional Experience🌱

1. University of Niagara Falls, Canada

  • Full-Time Faculty Member & Assistant Professor (May 2024 – Present)
    • Data Analytics, Medical Computing, and Data Visualization
    • Teaching various courses related to data analytics, business intelligence, and medical & scientific computing.

2. International Business University (IBU), Toronto, Canada

  • Lecturer (Adjunct Professor) (Jan 2024 – Present)
    • Courses: Business Analytics, Technology Literacy, and Digital Transformation, including cloud computing, AI & machine learning, and cybersecurity compliance.

3. Georgian College, Barrie Campus, Canada

  • Lecturer (Part-Time) (May 2023 – Present)
    • Courses: Reinforcement Learning, System Vision, and Conversational AI.

4. Humber College, Toronto, Canada

  • Lecturer (Part-Time) (Jan 2024 – Aug 2024)
    • Emerging Technologies in AI, Generative AI, and Quantum Computing.

5. Durham College, Oshawa, Canada

  • Lecturer (Part-Time) (Jan 2024 – May 2024)
    • AI Algorithms and teaching various machine learning techniques such as supervised, unsupervised learning, and ensemble methods.

6. DAPCCO, Toronto, Canada

  • Research Manager (Part-Time) (Apr 2023 – Apr 2024)
    • Research on AI for intelligent waterproofing estimation, including machine learning, data mining, and deep neural networks.

7. Islamic Azad University, Tehran, Iran

  • Faculty Member & Assistant Professor (Feb 2007 – Feb 2023)
    • Taught courses on machine learning, business intelligence, intelligent decision support systems, and supervised numerous student theses in AI, data mining, and big data.

8. Islamic Azad University, Central Organization, Tehran, Iran

  • Vice Chancellor of Science and Engineering (Jun 2022 – Feb 2023)
    • Led the development of AI curricula and served as a policy advisor for AI development across the university system.
Research Interests🔬

Her research interests include:

  • Artificial Intelligence & Machine Learning: Development of intelligent systems, deep learning, and autonomous agents.
  • Data Science & Analytics: Applications of data mining, predictive modeling, and business intelligence.
  • Cognitive Science & Philosophy of AI: Exploring human cognition and decision-making through AI and cognitive models.
  • Multi-Agent Systems: Designing and analyzing autonomous agents in distributed systems.
  • Medical AI: Applications of AI in healthcare, including disease prediction and diagnostics.

Author Metrics

  1. Publications:
    • Published in journals such as PLOS One, SN Computer Science, BMC Bioinformatics, and presented at IEEE conferences such as ICASSP and CONECCT.
    • Notable papers on AI for medical diagnostics and autonomous vehicles.
  2. Supervision:
    • Successfully supervised 85 master’s and 5 Ph.D. students, with a focus on AI and machine learning in diverse applications.
Awards and Honors
  1. Full Scholarship for Ph.D. – Awarded based on academic excellence and research contributions.
  2. Rank 1 in Visvesvaraya PhD Fellowship Entrance Test (2024) – Kalinga Institute of Industrial Technology, MeitY (Govt. of India).
  3. Qualified GATE (2022) – Computer Science & Information Technology.
  4. Qualified JEE (2018) – Secured admission in IIIT Gwalior.
Publications Top Notes 📄

1. Classification of Pima Indian Diabetes Dataset using Ensemble of Decision Tree, Logistic Regression, and Neural Network

  • Authors: M. Abedini, A. Bijari, T. Banirostam
  • Journal: International Journal of Advanced Research in Computer and Communication Engineering
  • Year: 2020
  • Citations: 37
  • Summary: This paper presents an ensemble approach combining decision tree, logistic regression, and neural network for classifying the Pima Indian Diabetes Dataset, improving prediction accuracy and robustness in medical data analysis.

2. Resolving Cold Start and Sparse Data Challenge in Recommender Systems using Multi-Level Singular Value Decomposition

  • Authors: K.V. Rodpysh, S.J. Mirabedini, T. Banirostam
  • Journal: Computers & Electrical Engineering
  • Volume: 94
  • Article: 107361
  • Year: 2021
  • Citations: 23
  • Summary: This research addresses the cold start and sparse data challenges in recommender systems, utilizing multi-level singular value decomposition to enhance system performance and recommendation accuracy in real-time applications.

3. Design, Modeling and Experimental Analysis of Wheeled Mobile Robot

  • Authors: M.H. Korayem, T. Banirostam
  • Conference: 3rd IFAC Symposium on Mechatronic Systems
  • Pages: 629-634
  • Year: 2004
  • Citations: 23
  • Summary: The paper presents the design, modeling, and experimental analysis of a wheeled mobile robot, with a focus on the integration of mechatronic systems for autonomous robotic applications.

4. Employing Singular Value Decomposition and Similarity Criteria for Alleviating Cold Start and Sparse Data in Context-Aware Recommender Systems

  • Authors: K.V. Rodpysh, S.J. Mirabedini, T. Banirostam
  • Journal: Electronic Commerce Research
  • Volume: 23, Issue 2
  • Pages: 681-707
  • Year: 2023
  • Citations: 19
  • Summary: This paper further builds upon the cold start issue in context-aware recommender systems, applying singular value decomposition and similarity criteria to address data sparsity and improve recommendation accuracy.

5. Functional Control of Users by Biometric Behavior Features in Cloud Computing

  • Authors: H. Banirostam, E. Shamsinezhad, T. Banirostam
  • Conference: Intelligent Systems Modeling & Simulation (ISMS-IEEE)
  • Year: 2013
  • Citations: 19
  • Summary: This study explores the use of biometric behavior features to provide functional control of users in cloud computing environments, enhancing security and user authentication in distributed systems.

Conclusion

Dr. Touraj BaniRostam is a highly deserving candidate for the Best Researcher Award. His exceptional academic track record, contributions to AI and machine learning, leadership in educational curricula development, and impactful research in fields such as healthcare AI, autonomous systems, and data science make him a leading figure in the field. Expanding his efforts to industry collaborations, increasing his participation in global conferences, and focusing on scalability and commercialization will further solidify his impact on the global research and technology landscape.