Gholamreza Anbarjafari | Generative AI | Best Researcher Award

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Prof. Gholamreza Anbarjafari | Generative AI | Best Researcher Award

Professor at Estonian Business School Estonia.

Professor Gholamreza Anbarjafari, also known as Shahab, is a distinguished AI scientist with over 15 years of experience in leading and developing cutting-edge solutions in AI, Generative AI, Machine Learning, Medical Signal Processing, and Computer Vision. He has held prominent academic positions, including Professor and Head of the iCV Lab at the University of Tartu and Visiting Professor roles at Yildiz Technical University and Estonian Business School. His professional journey includes significant contributions to industry, notably as Director of AI at PwC Finland, where he leads AI and GenAI initiatives across the Nordic region. An IEEE Senior Member, Professor Anbarjafari has been recognized with several awards, including the Best Lecturer award and the Best Paper award by ETRI Journal. His research has garnered substantial funding, and he has a robust publication record with a high h-index and numerous citations, reflecting his impact in the field.​

Publication Profile

ORCID

Scopus

Google Scholar

Education

  • Ph.D. in Electrical and Electronic Engineering
    Eastern Mediterranean University, Cyprus (January 2011)
    Thesis: Probability Distribution Function Based Face Recognition Boosted by Data Fusion
    Supervisor: Prof. Hasan Demirel

  • M.Sc. in Electrical and Electronic Engineering
    Eastern Mediterranean University, Cyprus (June 2008)
    Thesis: A New Face Recognition System Based on Colour Statistics
    Supervisor: Prof. Hasan Demirel ​

  • B.Sc. in Electrical and Electronic Engineering (High Honors)
    Eastern Mediterranean University, Cyprus (January 2007)
    Project: Explorer Robot
    Supervisor: Dr. Mustafa K. Uyguroğlu

Professional Experience

  • Director of AI, PwC Finland (March 2020 – Present)
    Leads AI and Generative AI (GenAI) strategy development, spearheading initiatives across the Nordic region. Provides consultancy on AI, GenAI, and computer vision solutions to diverse industries, including FinTech, AgriTech, EduTech, and SecurTech. Developed multiple LLM and deep learning-based solutions for clients in HRTech, banking, and cybersecurity sectors.​

  • Visiting Professor, Estonian Business School, Tallinn, Estonia (September 2024 – Present)
    Assists in developing AI-related grants and R&D projects.​

  • Visiting Professor, Yildiz Technical University, Istanbul, Turkey (September 2020 – May 2024)
    Taught Artificial Intelligence courses for postgraduate students and consulted on smart city and digitalization projects.

  • Discovery Search Team Lead, Rakuten Inc., via iCV Lab, Tartu, Estonia (September 2018 – August 2020)
    Led research on multimodal and multilingual discovery search for e-commerce, analyzing user behaviors during e-shopping.​

  • Co-founder and Chief Technology Officer (CTO), Alpha3D, Tallinn, Estonia (November 2019 – September 2023)
    Developed 3D content creation using stable diffusion models for AR applications.​

  • Professor/Head of iCV Lab, University of Tartu, Tartu, Estonia (September 2013 – April 2024)
    Led research in human behavior analysis, conducting R&D on data-driven AI solutions for various DeepTech applications. Secured over €10 million in funding from 47 contracts, collaborating with notable partners such as Veriff, Clevon, AuveTech, and others.

Research Interest 

Professor Anbarjafari’s research encompasses a broad spectrum of areas within artificial intelligence and computer vision, including:​

  • AI/Generative AI & Machine Learning

  • Computer Vision & Affective Computing

  • Natural Language Processing (NLP)

  • DeepTech Solutions across various domains

  • Human-Robot Interaction

  • Medical Signal Processing (EEG and ECG analysis)

  • 3D Modeling and Visualization

  • Image and Video Super Resolution

  • Biometric Recognition

  • Image Compression and Watermarking​

Author Metrics

  • h-index: 44

  • i10-index: 115

  • Total Citations: 8,271

Top Noted Publication

1. Action Recognition Using Single-Pixel Time-of-Flight Detection

Authors: I. Ofodile, A. Helmi, A. Clapés, E. Avots, K. M. Peensoo, S. M. Valdma, G. Anbarjafari, et al.
Journal: Entropy, Vol. 21, Issue 4, Article 414 (2019)
Citations: 16
Summary: This paper explores a novel method for action recognition using single-pixel Time-of-Flight (ToF) detection rather than conventional RGB or depth cameras. The study emphasizes:

  • Utilizing a ToF sensor for motion capture by detecting temporal variations in backscattered light.

  • A compressed sensing approach that allows action recognition from a limited number of photons (i.e., low-light or cost-constrained scenarios).

  • Demonstrated high accuracy in recognizing actions like waving, walking, and jumping using neural networks trained on ToF data.

2. An Objective No-Reference Measure of Illumination Assessment

Author: G. Anbarjafari
Journal: Measurement Science Review, Vol. 15, Issue 6, pp. 319–326 (2015)
Citations: 16
Summary: This paper proposes a no-reference (NR) metric for evaluating the illumination quality of digital images. Key contributions include:

  • Development of an algorithm that assesses brightness consistency and contrast without requiring a reference image.

  • Use of statistical parameters from histogram analysis to predict human visual satisfaction with image lighting.

3. Prediction of sgRNA Off-Target Activity in CRISPR/Cas9 Gene Editing Using Graph Convolution Network

Authors: P. K. Vinodkumar, C. Ozcinar, G. Anbarjafari
Journal: Entropy, Vol. 23, Issue 5, Article 608 (2021)
Citations: 15
Summary: This study applies graph convolutional networks (GCNs) to predict off-target effects of sgRNA sequences in CRISPR/Cas9 gene editing. Contributions:

  • Modeling nucleotide sequences as graphs to capture spatial and relational properties.

  • Achieves superior prediction accuracy over traditional machine learning methods.

  • Addresses a critical concern in genome editing: unintended mutations.

4. Size-Dictionary Interpolation for Robot’s Adjustment

Authors: M. Daneshmand, A. Aabloo, G. Anbarjafari
Journal: Frontiers in Bioengineering and Biotechnology, Vol. 3, Article 63 (2015)
Citations: 15
Summary: This research presents an adaptive algorithm for robot movement adjustment based on size-dictionary interpolation. Highlights:

  • A size-dictionary is created from previously observed environmental objects and used to adjust robot motion dynamically.

  • Enables robots to adapt quickly to new object dimensions without full reprocessing.

5. Multifunctionality of Polypyrrole Polyethylene Oxide Composites: Concurrent Sensing, Actuation and Energy Storage

Authors: N. Q. Khuyen, R. Kiefer, Z. Zondaka, G. Anbarjafari, A. L. Peikolainen, T. F. Otero, et al.
Journal: Polymers, Vol. 12, Issue 9, Article 2060 (2020)
Citations: 14
Summary: The paper investigates polypyrrole–polyethylene oxide (PPy–PEO) composites with integrated functionalities for:

  • Sensing (via electrical resistance changes),

  • Actuation (due to electrochemical expansion/contraction), and

  • Energy storage (as supercapacitor materials). The work includes both material synthesis and experimental validation.

Conclusion

Professor Gholamreza Anbarjafari is exceptionally qualified for the Best Researcher Award. His interdisciplinary research, academic leadership, and tangible impact in both academia and industry mark him as a pioneer in the field of Generative AI and applied computer vision.

While he could further strengthen his global outreach and public engagement, his credentials, innovation, and contribution trajectory make him a highly deserving recipient of such recognition.

 

Swati Jitendrakmar Patel | Artificial Intelligence | Best Researcher Award

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Ms. Swati Jitendrakmar Patel | Artificial Intelligence | Best Researcher Award

Software Engineer at Skyline Software Solutions, India

Ms. Swati Patel is an accomplished Data Analyst and Software Developer with extensive expertise in data science, machine learning, and software engineering. She has contributed significantly to academic research, publishing 8 journal papers, 2 IEEE conference papers, and 5 books on topics ranging from software security to predictive analytics. With strong analytical skills and a track record of developing efficient workflows and impactful applications, she has consistently delivered data-driven solutions for business optimization and research innovation.

Publication Profile

Google Scholar

Educational Details

Ms. Swati Patel holds a Master of Science in Advanced Computing Technologies from Birkbeck, University of London (2022-2023), where her projects included Principal Component Analysis on the Pima Indians Diabetes Dataset and predicting DDoS attacks using Darknet Time-Series data. She earned a Master’s degree in Computer Science from SES’s R. C. Patel Institute of Technology (NMU, India, 2012-2014), completing her thesis on software birthmark-based theft detection of JavaScript programs. Her Bachelor’s degree in Computer Engineering was completed at PSGVPM’s D. N. Patel College of Engineering, Shahada (NMU, India, 2008-2012), where she developed an Online Voting System using ASP.NET and SQL.

Professional Experience

Swati Patel is a Data Analyst and Entrepreneur with proven expertise in designing and optimizing workflows, data visualization, and software development. She served as a Data Analyst at SSP Group PLC, UK (2023-2024), where she created interactive Power BI dashboards to analyze sales data, optimized EPOS systems for data accuracy, and reduced data processing time by 30% through SQL optimization. As an entrepreneur, she successfully led Skyline Software Solutions (2014-2022), developing over 35 applications in Java, .NET, and other technologies. She managed end-to-end project execution, providing high-quality software solutions to diverse industries.

Research Interest

Swati’s research focuses on applied machine learning, natural language processing, and predictive modeling. She is particularly interested in statistical methods for data anomaly detection, speech-based health diagnostics, and secure systems in computing environments. Her work also extends to innovative clustering techniques for theft detection in software and dimensionality reduction in large datasets.

Author Metrics

  • Publications: 2 IEEE papers, 8 journal papers, 5 books.
  • Key Topics: Data science, machine learning, NLP, secure computing systems, predictive analytics.
  • Notable Works:
    • “A Review on Statistical Analysis-Based Approaches for Data Poison Detection Using Machine Learning.”
    • “Automated Depression Assessment from Speech Signals Using Pitch and Energy Features.”
    • “Long Short-Term Memory and Gated Recurrent Unit Networks for Accurate Stock Price Prediction.”
    • Books: COVID-19 Data Analysis for the United Kingdom and Data Exploration and Machine Learning using R.

Publication Top Notes

  • Software Birthmark Based Theft Detection of JavaScript Programs Using Agglomerative Clustering and Frequent Subgraph Mining
    • Authors: S.J. Patel, T.M. Pattewar
    • Conference: 2014 International Conference on Embedded Systems (ICES)
    • Pages: 63–68
    • Citations: 9
    • Year: 2014
    • Summary: This paper presents a novel method for detecting software theft in JavaScript programs using software birthmarks. The approach employs agglomerative clustering and frequent subgraph mining to identify similarities between programs, aiding in theft detection.
  • K-Means Clustering Algorithm: Implementation and Critical Analysis
    • Author: S. Patel
    • Publisher: Scholars’ Press
    • Citations: 8
    • Year: 2019
    • Summary: This publication provides an in-depth exploration of the K-means clustering algorithm, including its implementation and a critical analysis of its efficiency and limitations in clustering diverse datasets.
  • Software Birthmark Based Theft Detection of JavaScript Programs Using Agglomerative Clustering and Improved Frequent Subgraph Mining
    • Authors: S. Patel, T. Pattewar
    • Conference: 2014 International Conference on Advances in Electronics, Computers, and Communications
    • Citations: 7
    • Year: 2014
    • Summary: This paper builds upon earlier research by introducing an improved method for frequent subgraph mining, enhancing the detection accuracy of JavaScript program theft through advanced birthmark-based techniques.
  • Software Birthmark for Theft Detection of JavaScript Programs: A Survey
    • Authors: S.J. Patel, T.M. Pattewar
    • Journal: IJAFRC (International Journal of Advanced Foundation and Research in Computers)
    • Volume: 1, Issue 2, Pages: 29–38
    • Citations: 2
    • Year: 2014
    • Summary: This survey reviews existing methods for detecting software theft in JavaScript programs, with a focus on software birthmark techniques. It outlines challenges, solutions, and future research directions.
  • Emerging Trends in Computer Technology (NCETCT)
    • Authors: S.J. Patel, T.M. Pattewar
    • Journal: IJCA (International Journal of Computer Applications)
    • Conference Issue: NCETCT, Number 1
    • Year: 2014
    • Summary: This conference paper discusses advancements in computer technology with a focus on software security. It explores the use of software birthmarks as a means of detecting and preventing intellectual property theft in programming.

Conclusion

Ms. Swati Patel is a highly qualified and deserving candidate for the Best Researcher Award. Her combination of academic excellence, impactful research, and real-world contributions to artificial intelligence and software engineering set her apart as an innovative thinker. To maximize her potential and visibility, she could focus on strengthening her citation impact, pursuing international collaborations, and contributing to higher-impact conferences. Overall, her track record reflects dedication, skill, and the ability to drive meaningful advancements in her field.

 

 

 

Jatin Pal Singh | Artificial Intelligence | Industry Insightful Paper Award

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Mr. Jatin Pal Singh, Artificial Intelligence, Industry Insightful Paper Award

Jatin Pal Singh at Amazon Web Services INC, United States

Summary:

Jatin Pal Singh is a seasoned professional in the technology sector, currently serving as the Principal Solutions Architect at Amazon Web Services (AWS) in Seattle, WA. With a career spanning over two decades, he has showcased his expertise and leadership in various roles within AWS, starting as a Database Engineer and progressing to Senior Solutions Architect before assuming his current position.

Jatin holds a Bachelor of Technology degree, earned from his studies between 2000 and 2004. His commitment to professional development is evident through certifications such as AWS Certified SA Professional, AWS Certified Devops Assoc, and Oracle Certified Professional in Database Administration. Additionally, he has pursued certifications in Generative AI, Apache Spark, and DataBricks through Coursera, showcasing his dedication to staying at the forefront of technological advancements.

Professional Profile:

Google Scholar Profile 

👩‍🎓Education & Qualification:

Jatin Pal Singh’s educational and professional development background is outlined as follows:

Bachelor of Technology (2000-2004): Jatin Pal Singh earned a Bachelor of Technology degree, completing his undergraduate studies between 2000 and 2004.

Certifications:

AWS Certified SA Professional

AWS Certified Devops Assoc

Oracle Certified Professional – 8i/9i/10g/11g Database Administrator

Coursera Certifications:

  • Generative AI Certification
  • Apache Spark Certification
  • DataBricks Certification

ITIL Certification

Six Sigma Certification

These certifications reflect Jatin Pal Singh’s commitment to continuous learning and professional development, covering a range of relevant areas such as cloud services, database administration, artificial intelligence, big data processing, and IT service management methodologies. These qualifications demonstrate his expertise and proficiency in various domains, aligning with contemporary technology trends and best practices.

Experience:

Jatin Pal Singh’s professional work experience showcases a progressive journey in the technology sector:

Principal, Solutions Architect | Amazon Web Services, Seattle, WA August 2022 – Present

Senior Solutions Architect | Amazon Web Services, Seattle, WA April 2019 – August 2022

Solutions Architect | Amazon Web Services, Seattle, WA April 2018 – April 2019

Database Engineer | Amazon Web Services, Seattle, WA April 2018 – April 2019

Associate Consultant | Tata Consultancy Services, St Paul, MN September 2004 – August 2014

Throughout his tenure, Jatin Pal Singh has played pivotal roles, progressively advancing from Associate Consultant at Tata Consultancy Services to his current position as Principal Solutions Architect at Amazon Web Services. His extensive experience in various roles within Amazon Web Services underscores his expertise in the field.

Accomplishments:

Jatin Pal Singh has demonstrated exceptional achievements and leadership in the following areas:

Practice Development:

Instrumental in scaling partner business from $1M to $25M within a year. Established relationships with key business and technical decision-makers, created practice frameworks, and developed collaterals such as sales battle cards, offerings, differentiators, proof of concept, and demos. Specialized in AWS Cloud solutions, particularly in Database, Analytics, and AI/ML services.

Thought Leadership:

Generated impactful technical collateral, including blogs and whitepapers, reaching an extensive audience of 50,000+ views. Played a pivotal role in closing multiple deals, addressing challenges in AWS services implementation through innovative architecture solutions. Led technical presales thought leadership in diverse domains such as Healthcare, Artificial Intelligence, Analytics, Migrations, Resilience, and Replication. Produced AWS ReInvent YouTube videos and chalk talks widely utilized by clients for tier1 workloads.

Solution Architecture:

Developed tools, accelerators, and solution architecture frameworks to address custom customer challenges. Created repeatable solutions and blueprints for broader adoption. Resolved technical blockers for customer opportunities by providing best practices, managing escalations, and offering hands-on troubleshooting or workarounds.

Trusted Advisor:

Collaborated with internal stakeholders, including engineering, product, and sales teams, to build strong relationships with customer and partner technical specialists. Implemented a structured feedback mechanism program across multiple teams, influencing product roadmaps based on customer requirements. Jatin Pal Singh’s expertise lies in being a trusted advisor and facilitator of effective collaboration within the organization.

Publication Top Noted:

“An integrative perspective on the role of touch in the development of intersubjectivity”

  • Published in Brain and Cognition, 2022
  • Volume 163, Page 105915
  • Citation Count: 6

“Testing the Magnitude of Correlations Across Experimental Conditions”

  • Published in Frontiers in Psychology, 2022
  • Volume 13 (860213), Pages 1-9
  • Citation Count: 6

“Brain and behavioral contributions to individual choices in response to affective–cognitive persuasion”

  • Published in Cerebral Cortex, 2022
  • Volume 5
  • Citation Count: 5

“Probabilistically Weighted Multilayer Networks disclose the link between default mode network instability and psychosis-like experiences in healthy adults”

  • Published in NeuroImage, 2022
  • Volume 257 (119291), Pages 1-11
  • Citation Count: 3

“Appropriately tuning stochastic-psychometric properties of the Balloon Analog Risk Task”

  • Published in Frontiers in Psychology, 2022
  • Volume 13
  • Citation Count: 3