Obsa Gilo Wakuma | Artificial Intelligence | Best Researcher Award

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Dr Obsa Gilo Wakuma  | Artificial Intelligence | Best Researcher Award 

 Ass. Prof at Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated researcher and academician with a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, where his thesis focused on “Deep Learning Approaches for Efficient Domain Adaptation.” He holds an M.Sc. in Computer Science (CGPA: 3.78) and a B.Sc. in Computer Science (CGPA: 3.56) from Wallaga University, Ethiopia.Dr. Obsa Gilo Wakuma continues to contribute to the academic and research community with his expertise in deep learning and domain adaptation, leveraging his strong background in computer science and engineering to drive innovative solutions.

🎓 Education:

  • Ph.D. in Computer Science and Engineering, IIT Patna (2024)
  • M.Sc. in Computer Science, Wallaga University (2018)
  • B.Sc. in Computer Science, Wallaga University (2014)
  • XII Class, Sibu Sire Preparatory School (2010)
  • X Class, Sibu Sire High School (2008)

💼 Work Experience:

Dr. Wakuma began his professional journey as a Recorder at Wallaga University’s main Registrar in Oromia, Ethiopia, from October 2014 to June 2015. He then served as a Laboratory Technician at Wallaga University’s Shambu campus until February 2016. From February 2016 to September 2018, he worked as a Graduate Assistant (GA-II) at Wallaga University, eventually becoming a Lecturer from February 2019 to September 2019. From September 2019 to December 2023, he was a Research Scholar at IIT Patna.

📚 Research Focus:

Dr. Wakuma’s research primarily revolves around deep learning and domain adaptation. His notable publications include articles in prestigious journals such as Expert Systems with Applications, Pattern Analysis and Applications, IEEE Access, and the Journal of Visual Communication and Image Representation. His work often explores robust unsupervised deep sub-domain adaptation and optimal transport for image classification.

🛠️ Skills:

Dr. Wakuma possesses strong competencies in multiple languages, including English, Afaan Oromoo, and Amharic. His technical skills encompass programming languages such as Java, PHP, Python, C, C++, and R. He is proficient in databases like MySQL, PostgreSQL, HSQL, and SQLite, and has experience in web development using HTML, CSS, JavaScript, and Apache Web Server. Additionally, he is skilled in academic research, teaching, training, consultation, and community service.

Research and Publications

  1. Journal Articles: Published in prestigious journals such as “Expert Systems with Applications,” “Pattern Analysis and Applications,” “IEEE Access,” and “Journal of Visual Communication and Image Representation.” Topics covered include domain adaptation in sensor data, subdomain adaptation via correlation alignment, robust unsupervised deep sub-domain adaptation, and unsupervised sub-domain adaptation using optimal transport.
  2. Conference Proceedings: Presented at the IEEE 19th India Council International Conference (INDICON), discussing the integration of discriminate features and similarity preserving for unsupervised domain adaptation.

Conclusion

Given his strong academic background, extensive research publications, practical skills, and teaching experience, Obsa Gilo Wakuma is a highly suitable candidate for the Best Researcher Award. His contributions to the field of computer science, particularly in deep learning and domain adaptation, demonstrate a high level of expertise and impact, making him deserving of such recognition.

📜 Publications:

  • Unsupervised sub-domain adaptation using optimal transport
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    Journal of Visual Communication and Image Representation (2023)
    🖼️🔄🚚
  • Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    Pattern Analysis and Applications (2024)
    📊🔄🌐
  • Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation
    O. Gilo, J. Mathew, S. Mondal
    2022 IEEE 19th India Council International Conference (INDICON) (2022)
    📚🔍🤝
  • Kernelized Bures metric: A framework for effective domain adaptation in sensor data analysis
    O. Gilo, J. Mathew, S. Mondal
    Expert Systems with Applications (2024)
    📈🔄🔬
  • RDAOT: Robust Unsupervised Deep Sub-domain Adaptation through Optimal Transport for Image Classification
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    IEEE Access (2023)
    🖼️🔄🧠
  • Information Extraction For Afaan Oromo News Texts Using Hybrid Approach
    O. Gilo
    Journal of Innovation in Computer Science and Engineering (2019)
    📰🔍🇪🇹
  • Unified Domain Adaptation with Discriminative Features and Similarity Preservation
    O. Gilo, J. Mathew, S. Mondal
    (Journal/Conference not specified)
    🔄🌐🤝

Cicil Denny | AI and Machine Learning | Best Researcher Award |

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Mr Cicil Denny | AI and Machine Learning |  Best Researcher Award

Student/Member at Vellore Institute of Technology, Chennai ,India

🌟 Cicil Melbin Denny J is a versatile Data Analyst with a strong background in Artificial Intelligence, Machine Learning, and Software Engineering. With hands-on experience in programming languages like Python, Java, C++, and JavaScript, and advanced skills in AI, ML, and Deep Learning frameworks such as PyTorch and TensorFlow, Cicil excels in tackling complex data problems. Notably, he led a research project on Semantic Segmentation for Underwater Imagery (SUIM), achieving an impressive mIoU of 84.83%, which was published in the prestigious “Results in Engineering” journal. Cicil’s technical prowess extends to data analytics tools like MySQL and NoSQL, and he is adept at using PowerBI and Tableau for business insights. His proficiency in network administration, cloud services (AWS, Azure, Google Cloud), and cybersecurity underlines his comprehensive skill set. Recognized for his problem-solving attitude and effective communication skills, Cicil is well-equipped to contribute to product analysis and support, making him a valuable asset in any tech-driven environment. 📊💡🤖

professional profile:

📚 Education:

  • B.Tech in CSE with specialization in Artificial Intelligence and Machine Learning, CGPA: 8.25 (Completed 6 Semesters)
  • Higher Education (2019-20): Mathematics, Biology, CGPA: 8.38

💼 Work Experience:

  • Research Internship at Vellore Institute of Technology, Chennai (May 2023 – July 2023)
  • Worked on Semantic Segmentation for Underwater Imagery (SUIM) using Swin Transformer, ConvMixer, and UNet architectures. Achieved mIoU metrics of 84.83% and published in “Results in Engineering” Journal – 2024 by Elsevier.

🔍 Skills:

  • Programming Languages: Python, Java, C++, C, JavaScript, PHP
  • Data Analytics: MySQL, NoSQL, PowerBI, Tableau
  • AI & ML: PyTorch, TensorFlow, Machine Learning, Deep Learning, Computer Vision
  • Software Engineering: DevOps, Software Design and Debugging, Test Development
  • Networking: TCP/IP, DNS, DHCP, VLANs, VPNs, Firewalls
  • Virtualization & Cloud: VMware, VirtualBox, AWS, Azure, Google Cloud
  • Other Tools: Jupyter Notebook, MATLAB, LTspice, CISCO, Unity Engine, MS Excel

🏆 Certifications:

  • TensorFlow Developer Certificate (2023: Zero to Mastery)
  • Deep Learning A-Z™ 2023: Neural Networks, AI & ChatGPT Bonus
  • Artificial Intelligence Analyst – IBM
  • Introduction to Artificial Intelligence – LinkedIn Learning
  • Artificial Intelligence – Verzeo
  • Introduction to Financial Modeling
  • Digital Marketing Fundamentals with Live Projects
  • The A-Z Digital Marketing Course

🔬 Research Focus:

  • 🔬 Cicil Melbin Denny J’s research focuses on cutting-edge technologies in AI and Machine Learning. He has extensively worked on Semantic Segmentation for Underwater Imagery using advanced architectures like Swin Transformer, ConvMixer, and UNet, achieving high accuracy. His work on IoT botnet detection leverages autoencoders, LSTM-CNN, and DNN to enhance cybersecurity. Additionally, he explores route mapping algorithms, blockchain technology, and cryptocurrency trends. Cicil’s dedication to innovation is evident through his projects on malware detection using ML algorithms and IoT-based accident intimation systems, aiming to improve safety and security in various domains. 🌊🤖🔒🌐

👩‍🏫 Teaching & Knowledge Sharing:

  • Advanced skills in AI, ML, Deep Learning, and Computer Vision with hands-on experience.
  • Prepared detailed reports and suggested improvements on QA patterns for Amazon Warehouses.

 

publications🌟

Pritha N | Deep learning | Best Researcher Award

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Mrs Pritha N  | Deep learning  |  Best Researcher Award 

 

 

Assistant professor at  Panimalar Engineering College, India

 

👨‍🏫N. Pritha  With over 16.8 years of teaching experience, this dedicated educator specializes in Information and Communication Engineering. They hold a PhD from Anna University, Chennai.

Professional Profile:

🎓 Education:

🎓 PhD in Information and Communication Engineering, Anna University
🎓 M.E. in Applied Electronics, Sathyabama University (CGPA: 8.1)
🎓 B.E. in Electronics & Communication Engineering, Adhiparasakthi College of Engineering (76%)
🎓 Diploma in Electronics & Communication Engineering, Bakthavatchalam Polytechnic (83%)

💼 Work Experience:

  • 🏫 Lecturer at Adhiparasakthi College of Engineering (5.11 years)
    🏫 Assistant Professor (HOD Incharge) at John Bosco Engineering College (9 months)
    🏫 Assistant Professor at Panimalar Engineering College (10 years)

🏆 Awards and Honors:

🏅 2nd Topper in FDP on Embedded, IoT, AI, & HPC (2021)
🏅 5% Topper and Silver certification in NPTEL’s Machine Learning course (2023)

 

🔬 Research Focus:

N. Pritha’s research spans several critical areas in electronics and communication engineering. Her primary focus includes the design and optimization of RF and Microwave Engineering systems, exploring innovative techniques in Machine Learning, Deep Learning, and Artificial Neural Networks. She has contributed significantly to the development of multiband antennas for wireless applications, anomaly detection models in sensor networks, and enhancing the efficiency of digital multipliers like Wallace Tree and Dadda multipliers. Her work emphasizes low power, high-speed, and area-efficient solutions, contributing to advancements in embedded systems, IoT, and AI-driven applications.

Publications: 

 

SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Award

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Assist Prof Dr SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Award  

Assistant Professor at  NIT Kurukshetra,India

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

 

Professional Profile:

Education

Dr. Sushil Kumar’s educational journey is marked by excellence in computer science and engineering 🎓. He earned his Ph.D. from the Indian Institute of Technology Roorkee (2009-2014), focusing on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” 📸. 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 📊. Dr. Kumar received his B.Tech. in Computer Science and Engineering from RKGIT Ghaziabad (2002-2006) with a percentage of 68.98 💻. 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% 📚

 

Teaching Experience:

Dr. Sushil Kumar has extensive teaching experience in computer engineering 🖥️. Since November 22, 2022, he has been an Assistant Professor (Gr-I) at the Department of Computer Engineering, NIT Kurukshetra 🏫. Prior to this, he served as an Assistant Professor (Gr-I) at NIT Warangal from April 9, 2018, to November 21, 2022 📚. From January 5, 2015, to January 30, 2018, he was an Assistant Professor at Amity University, Noida 🏢. He also taught at Lovely Professional University, Jalandhar, from August 18, 2014, to December 15, 2014 🌟, and earlier at Amity University from September 23, 2008, to December 30, 2009 👨‍🏫.

Achievements:

Dr. Sushil Kumar has a commendable list of achievements and awards 🌟. He qualified GATE-2006 in Computer Science and Engineering 🎓. He received an MHRD Fellowship of ₹5000/month for his M.Tech. (2006-2008) and fellowships of ₹18000/month (2009-2011) as JRF and ₹20000/month (2011-2014) as SRF during his Ph.D. at IIT Roorkee 🏅. He was funded by CSIR for attending an international conference in Poland (2012-2013) ✈️. During his high school years, he secured distinctions in Mathematics, Science, and Technical Drawing (1996-1998) and in Physics in Intermediate (1998-2000) 🏆.

Research focus :

Dr. Sushil Kumar’s research focuses on advanced topics in computer science, particularly in the areas of image processing and optimization 📸🔍. 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 🧠. Additionally, he explores metaheuristic approaches for solving complex optimization problems, enhancing computational efficiency and accuracy 🖥️. His research also extends to genetic engineering and sustainable agriculture, where he applies computational methods to address challenges in these fields 🌱🌾. Dr. Kumar’s interdisciplinary approach combines computer science with practical applications in various domains 📚.
Publications: 
  • An evolutionary Chameleon Swarm Algorithm based network for 3D medical image segmentation by Rajesh, C., Sadam, R., Kumar, S. – Expert Systems with Applications, 2024 – 📝 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 – 📝 0 citations
  • An evolutionary U-shaped network for Retinal Vessel Segmentation using Binary Teaching–Learning-Based Optimization by Rajesh, C., Sadam, R., Kumar, S. – Biomedical Signal Processing and Control, 2023 – 📝 7 citations
  • Automatic Retinal Vessel Segmentation Using BTLBO by Rajesh, C., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – 📝 1 citation
  • Improved CNN Model for Breast Cancer Classification by Satya Shekar Varma, P., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – 📝 0 citations
  • An evolutionary block based network for medical image denoising using Differential Evolution by Rajesh, C., Kumar, S. – Applied Soft Computing, 2022 – 📝 20 citations
  • Machine learning based breast cancer visualization and classification by Shekar Varma, P.S., Kumar, S., Sri Vasuki Reddy, K. – ICITIIT 2021, 2021 – 📝 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 – 📝 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 – 📝 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 – 📝 29 citations