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)
    🔄🌐🤝

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