Hamna Baig | Artificial Intelligence | Young Researcher Award

Ms. Hamna Baig | Artificial Intelligence | Young Researcher Award

Research Internee | COMSATS University Islamabad, Attock Campus | Pakistan

Hamna Baig πŸŽ“ is a passionate and award-winning Electrical Engineering graduate from COMSATS University Islamabad, Attock Campus. A gold medalist πŸ₯‡ with a CGPA of 3.66, she blends academic brilliance with innovative research in AI, IoT, and robotics πŸ€–. Hamna’s dynamic work spans smart environments, RF sensing, and machine learning applications πŸ’‘. She has published multiple research papers πŸ“š, led various technical projects, and participated in prestigious conferences πŸ›οΈ. Her leadership roles and technical writing expertise further reflect her versatility 🧠. Hamna aims to revolutionize engineering solutions through creativity, technology, and social impact 🌍.

Professional profile :Β 

Google Scholar

OrcidΒ 

Summary of Suitability :Β 

Hamna Baig exemplifies the essence of a young and emerging researcher through her exceptional academic performance, innovative contributions to AI-driven engineering, and a prolific portfolio of research publications. A gold medalist in Electrical Engineering from COMSATS University Islamabad, she has demonstrated consistent excellence in both theoretical knowledge and practical application. With multiple high-impact publications, advanced project implementations, and recognized conference presentations, she brings outstanding promise to the future of intelligent systems and healthcare engineering. Her dedication to interdisciplinary innovation, backed by hands-on experience and leadership roles, showcases her as a rising star in engineering research.

πŸ”Ή Education & Experience :

πŸ“˜ Education:

  • πŸŽ“ B.Sc. Electrical Engineering, COMSATS University Islamabad, Attock Campus (2020–2024) – CGPA: 3.66/4.00, Gold Medalist πŸ…

  • πŸ“‘ Final Year Project: AI-based Environmental Control Model for Smart Homes πŸ πŸ€–

πŸ§‘β€πŸ’Ό Experience:

  • πŸ§ͺ Internee, Electrical & Computer Engineering Dept., COMSATS, under PEC GIT Program (2024–Present)

  • ⚑ Internee, Ghazi-Barotha Hydro Power Plant (GBHPP), WAPDA (2023)

  • πŸ–‹οΈ Technical Writer (Electrical/Electronics), CDR Professionals (2023–Present)

Professional Development :

Hamna Baig has actively pursued professional growth through certifications, leadership, and community engagement 🌱. She completed the prestigious “Machine Learning Specialization” by DeepLearning.AI πŸ€–, “Generative AI for Everyone” 🧠, and several tech courses from Stanford, Yonsei, and the University of Michigan via Coursera πŸŽ“. As a proactive learner, she enhances her skills in AI, IoT, wireless communication, and public speaking 🎀. Hamna has held key roles such as President of the Sports Society 🏸, Co-Campus Director of AICP πŸ§‘β€πŸ”¬, and VP of COMSATS Science Society. Her drive to uplift communities and advance technology sets her apart 🌟.

Research Focus :Β 

Hamna’s research centers on the integration of Artificial Intelligence and Machine Learning into real-world electrical and biomedical systems πŸ€–πŸ§ . She explores SDR-based gait monitoring for Parkinson’s patients πŸ§“, AI-controlled environmental systems for energy-efficient smart homes 🌑️, and intelligent robotic applications in agriculture πŸ€–πŸŽ. Her work emphasizes non-invasive health monitoring using RF sensing πŸ›οΈ and AI-powered automation solutions. She is deeply invested in translating complex algorithms into practical, user-centric applications that elevate health, comfort, and productivity ⚑. Her interdisciplinary approach bridges electrical engineering with innovative computing solutions πŸ”ŒπŸ“Š.

Awards & Honors :

  • πŸ† Awards & Certificates:

    • πŸ₯‡ Gold Medalist, COMSATS University Islamabad (2024)

    • 🧾 Certificate of Gratitude, ICTIS Conference, UET Peshawar (2024)

    • πŸ“œ Certificate of Gratitude, ICCSI Conference, University of Haripur (2024)

    • 🧠 ML Specialization Certificate, DeepLearning.AI – Stanford (2023)

    • 🧬 Generative AI for Everyone – DeepLearning.AI (2025)

    • πŸ§β€β™€οΈ Public Speaking Specialization – University of Michigan (2024)

    • πŸ“Ά Wireless Communications Course – Yonsei University (2024)

    • πŸŽ“ Prime Minister’s Youth Laptop Scheme Awardee (2023)

    • πŸ₯‡ Winner – IoT Pick and Place Robotic Competition, COMSATS (2024)

    • πŸ§’ Student of the Year – COMSATS University, Attock (2023)

Publication Top Notes :Β 

  • β€’ Title: Intelligent Frozen Gait Monitoring using Software Defined Radio Frequency Sensing
    Citation: Electronics, 14(8), 1603, 2025
    Authors: Khan, M. B., Baig, H., Hayat, R., Tanoli, S. A. K., Rehman, M., Thakor, V. A., & Haider, D.
    Year: 2025

  • β€’ Title: Machine Learning-Based Estimation of End Effector Position in Three-Dimension Robotic Workspace
    Citation: IJIST Journal (Impact Factor: 4.312)
    Authors: Baig, H., Ahmed, E., Jadoon, I., & Pakistan, K. C. A.
    Year: 2024

  • β€’ Title: A Robotic Approach for Fruit Harvesting with Machine Learning-Based Joint Angles Prediction
    Citation: Submitted to ICCSI – International Conference on Computational Sciences and Innovations
    Authors: Baig, H., Baig, A.A, Ahmed, E., Jadoon, I., & Pakistan
    Year: 2024

  • β€’ Title: Artificial Intelligence Based Adaptive Fan Control in Office Settings for Energy Efficiency
    Citation: Submitted to ICCIS – Proceedings to Springer Journal
    Authors: Baig, H.
    Year: 2024

  • β€’ Title: A Robotic Arm Based Intelligent Biopsy System
    Citation: Submitted to ICCIS – Kohat University, Springer Proceedings
    Authors: Baig, H.
    Year: 2024

  • β€’ Title: Design of an Intelligent Wireless Channel State Information Sensing System to Prevent Bedsores
    Citation: IEEE Sensors Journal (Under Review)
    Authors: Baig, H.
    Year: 2024

  • β€’ Title: Enhancing Home Comfort and Energy Consumption with an Artificial Intelligence-Based Environmental Sensing Control Model
    Citation: PeerJ (Computer Science) (Under Review)
    Authors: Baig, H.
    Year: 2024

  • β€’ Title: Breathing Techniques Redefined: The Pros and Cons of Traditional Methods and the Promise of SDRF Sensing
    Citation: Elsevier – Digital Communications and Networks (Under Review)
    Authors: Baig, H.
    Year: 2024

Conclusion :Β 

  • Hamna Baig not only meets but exceeds the expectations of a Young Researcher Award recipient. Her innovative mindset, research productivity, and real-world problem-solving approach make her an ideal candidate. Her work is not just academically sound but socially impactfulβ€”especially in the domains of healthcare and automation. She is a beacon of excellence and innovation, representing the future of engineering research. 🌟

 

Prof. Ching Yee Suen | Artificial Intelligence | Best Researcher Award

Prof. Ching Yee Suen | Artificial Intelligence | Best Researcher Award

Prof. Ching Yee Suen, Concordia University, Canada

Prof. Ching Yee Suen is a globally recognized expert in Pattern Recognition, AI, and Document Analysis. As the Founding Director and Co-Director of CENPARMI at Concordia University, he has shaped advancements in handwriting recognition, multiple classifiers, and font analysis. A Fellow of IEEE, IAPR, and the Royal Society of Canada, he has mentored 120+ graduate students and 100 visiting scientists. With 550+ research papers, 16 books, and an h-index of 74, his contributions are widely cited. His innovations power millions of devices worldwide. He has led $20M+ research projects, collaborated with global industries, and serves as an editor for top-tier journals.

🌍 Professional Profile:

Google Scholar

πŸ† Suitability for Best Researcher AwardΒ 

Prof. Suen is an exceptional candidate for the Best Researcher Award due to his pioneering contributions in AI, pattern recognition, and handwriting analysis. His research has real-world impact, with millions of users benefiting from his handwriting recognition algorithms. He has received top international awards, including the King-Sun Fu Prize (2021) and ICDAR Award (2005). As a leading AI researcher, he has secured $20M+ in funding, supervised over 120 Ph.D. and master’s students, and led groundbreaking industrial collaborations. His global influence, leadership in AI, and outstanding research output make him a worthy recipient of this prestigious honor.

πŸŽ“ EducationΒ 

Prof. Ching Yee Suen holds a Ph.D. from the University of British Columbia (UBC), Vancouver, and a Master’s degree from the University of Hong Kong. His academic journey has been marked by a deep focus on Artificial Intelligence, Pattern Recognition, and Computational Vision. His early research laid the foundation for his groundbreaking work in handwriting recognition, document analysis, and AI-powered classification systems. He has spent sabbatical leaves at MIT, McGill University, Ecole Polytechnique, and IBM, further expanding his expertise. His academic credentials have established him as a leading scholar in AI and pattern recognition on a global scale.

πŸ’Ό ExperienceΒ 

With a career spanning 50+ years, Prof. Suen has held key leadership roles at Concordia University, serving as Chairman of Computer Science, Associate Dean (Research), and Concordia Chair in AI & Pattern Recognition. He is the Founding Director and Co-Director of CENPARMI, where he has driven cutting-edge research. He has supervised 120+ graduate students and collaborated with top institutions worldwide. As a consultant to Microsoft, Xerox, Canada Post, and the US Congress, his work has had real-world impact. His editorial leadership in top AI journals and conference organization further cements his global influence in the research community.

πŸ… Awards and Honors

Prof. Suen’s excellence is recognized globally, earning him top honors in AI and pattern recognition. He received the King-Sun Fu Prize (2021) πŸ†, the ICDAR Award (2005) πŸŽ–οΈ, and the Elsevier Distinguished Editorial Award (2016)πŸ“œ. His Concordia Lifetime Research Achievement Award (2008) and Teaching Excellence Award (1995) πŸŽ“ highlight his impact in academia. Internationally, he was honored with the Gold Medal from the University of Bari, Italy (2012) πŸ₯‡. As a Fellow of IEEE, IAPR, and the Royal Society of Canada, his contributions to AI, document analysis, and handwriting recognition are celebrated at the highest levels.

πŸ”¬ Research FocusΒ 

Prof. Suen specializes in Pattern Recognition, Artificial Intelligence, and Document Analysis. His innovations in handwriting recognition, fake coin detection, license plate recognition, and multi-classifier systems have transformed industry applications. His research integrates AI, deep learning, and image processing to solve complex problems in computer vision, natural language processing, and fraud detection. His high-impact contributions are widely used in mobile devices, banking security, and postal services. His multi-disciplinary approach in AI has led to real-world solutions adopted by Microsoft, Bell Canada, Canada Post, and global tech firms, making him a pioneer in intelligent pattern analysis.

πŸ“Š Publication Top notes:

  • Title: Developing Knowledge Management Metrics for Measuring Intellectual Capital
    • Year: 2000
    • Citations: 442
  • Title: Modified Hebbian Learning for Curve and Surface Fitting
    • Year: 1992
    • Citations: 322
  • Title: N-Gram Statistics for Natural Language Understanding and Text Processing
    • Year: 1979
    • Citations: 315
  • Title: Analysis and Design of a Decision Tree Based on Entropy Reduction and Its Application to Large Character Set Recognition
    • Year: 1984
    • Citations: 176
  • Title: Large Tree Classifier with Heuristic Search and Global Training
    • Year: 1987
    • Citations: 102

 

 

Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

Dr. Satish Mahadevan Srinivasan, Penn State Great Valley , United States.

Dr. Satish Mahadevan Srinivasan is a Tenured Associate Professor of Information Science at Penn State Great Valley, with expertise spanning data mining, machine learning, cybersecurity, and bioinformatics. With a Ph.D. in Information Technology from the University of Nebraska, his research contributions include class-specific motif discovery in protein classification and tools for metagenomic analysis. Dr. Srinivasan’s work merges cutting-edge technologies with practical applications, contributing to bioinformatics, distributed computing, and artificial intelligence. He has a rich academic and professional journey, publishing impactful research and developing transformative software tools.Β πŸŒπŸ“ŠπŸ”¬

Publication Profiles

Googlescholar

Education and Experience

Education

  • πŸŽ“Β Ph.D. in Information Technology, University of Nebraska, 2010
  • πŸŽ“Β M.S. in Industrial Engineering & Management, IIT Kharagpur, 2005
  • πŸŽ“Β B.E. in Information Technology, Bharathidasan University, 2001

Experience

  • πŸ“šΒ Tenured Associate Professor, Penn State Great Valley (2019–Present)
  • πŸ“šΒ Assistant Professor, Penn State Great Valley (2013–2019)
  • πŸ”¬Β Postdoctoral Researcher, Computational Bioinformatics, UNMC (2011–2013)
  • πŸ’»Β Postdoctoral Research Assistant, Computer Science, University of Nebraska (2010–2011)
  • πŸ› οΈΒ Project Assistant, IIT Kharagpur (2001–2005)

Suitability For The Award

Dr. Satish Mahadevan Srinivasan, a Tenured Associate Professor at Penn State, excels in interdisciplinary research spanning data mining, bioinformatics, machine learning, and cybersecurity. His groundbreaking tools like MetaID and Monarch have advanced microbial analysis and software engineering. With impactful publications, innovative solutions, and practical applications, Dr. Srinivasan exemplifies research excellence, making him highly deserving of the Best Researcher Award.

Professional Development

Dr. Srinivasan has developed innovative tools and frameworks, including MetaID for metagenomic studies and Monarch for transforming Java programs for embedded systems. His interdisciplinary research bridges machine learning, predictive analytics, and cybersecurity with bioinformatics, aiding microbial classification and software optimization. By integrating artificial intelligence and distributed computing, he has addressed complex challenges in data science, genomics, and engineering. His professional journey reflects a commitment to cutting-edge technology, impactful research, and knowledge dissemination through teaching and mentorship.Β πŸŒŸπŸ”

Research Focus

Dr. Satish Mahadevan Srinivasan’s research focuses on leveraging advanced technologies to address complex problems in data science, bioinformatics, and cybersecurity. His work inΒ data miningΒ andΒ machine learningΒ aims to uncover patterns and develop predictive models for diverse applications. InΒ bioinformatics, he has designed tools like MetaID for microbial classification and motif discovery in protein sequences, contributing to genomics and medical advancements. His expertise extends toΒ cybersecurity, where he explores cryptographic techniques to enhance internet security, andΒ distributed computing, optimizing system performance. Dr. Srinivasan’s interdisciplinary approach bridgesΒ artificial intelligence,Β predictive analytics, andΒ software engineeringΒ to create impactful solutions.Β πŸŒπŸ”¬πŸ“Š

Awards and Honors

  • πŸ†Β Awarded research grants for innovative bioinformatics tools.
  • πŸ“œΒ Recognized for contributions to cybersecurity and internet authentication.
  • 🌟 Acknowledged as a leading researcher in predictive analytics and machine learning.
  • πŸ“ŠΒ Published in high-impact journals like BMC Bioinformatics and BMC Genomics.

Publication Top Notes

  • Effect of negation in sentences on sentiment analysis and polarity detectionΒ  – Cited by 93, 2021Β πŸ“ŠπŸ“š
  • LocSigDB: A database of protein localization signalsΒ  – Cited by 49, 2015Β πŸ§¬πŸ“–
  • K-means clustering and principal components analysis of microarray data of L1000 landmark genes– Cited by 46, 2020Β πŸ§ͺπŸ“Š
  • Mining for class-specific motifs in protein sequence classification – Cited by 29, 2013Β πŸ”¬πŸ“œ
  • Web app security: A comparison and categorization of testing frameworks– Cited by 27, 2017Β πŸ”’πŸ–₯️
  • MetaID: A novel method for identification and quantification of metagenomic samples – Cited by 23, 2013Β πŸŒπŸ”
  • Sensation seeking and impulsivity as predictors of high-risk sexual behaviours among international travellers – Cited by 21, 2019 ✈️🧠
  • Cybersecurity for AI systems: A survey – Cited by 20, 2023Β πŸ€–πŸ”