Dimitrios Tsourounis | Computer Science | Best Researcher Award

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Dr. Dimitrios Tsourounis | Computer Science | Best Researcher Award

Dr. Dimitrios Tsourounis | Computer Science | University of Patras | Greece

Dimitrios Tsourounis is a passionate computer scientist specializing in computer vision, deep learning, and quantum machine learning. Born on February 26, 1991, in Greece, Dimitrios earned his Ph.D. from the University of Patras in 2023, focusing on deep learning strategies for problems with limited data. He has contributed significantly to advancing machine learning methods and quantum computing integration, currently working as a Research Scientist at Quantum Neural Technologies (QNT) in Athens. Dimitrios is also involved in autonomous aerial systems research at the Athena Research Center, applying computer vision techniques to fuse radar and RGB camera data for UAVs. His multidisciplinary expertise includes physics, electronics, and artificial intelligence, supported by multiple successful EU-funded projects. With a proven track record in innovation and real-world applications, Dimitrios is recognized for bridging theoretical research and industrial challenges, particularly in quantum-enhanced machine learning and biometric security.

Author Profile

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Education 

Dimitrios completed his Ph.D. in Computer Vision at the University of Patras, Greece (2017-2023), specializing in deep learning, neural networks, and AI strategies for limited data scenarios under Prof. George Economou’s supervision. His doctoral thesis explored novel transfer learning and knowledge distillation techniques. Prior to this, Dimitrios earned an M.Sc. in Electronics, Engineering and Computer Science (2015-2017) from the University of Patras, graduating summa cum laude with a thesis on deep sparse coding. His academic foundation was built on a B.Sc. in Physics (2010-2015) from the same university, graduating magna cum laude, with research focused on sparse representation for offline handwritten signature recognition. Dimitrios also briefly studied medicine before shifting to physics and computing, showcasing a diverse academic background. Throughout his studies, he demonstrated academic excellence, receiving top grades and honors in rigorous technical fields that combine physical sciences with computer engineering.

Experience

Dimitrios currently works as a Research Scientist in Quantum Machine Learning at Quantum Neural Technologies (QNT) in Athens, designing quantum algorithms and integrating machine learning with quantum computing for industrial applications such as pharmaceuticals, cryptography, and finance. Since July 2025, he has been a Computer Vision Scientist at the Athena Research Center, focusing on UAV systems that fuse radar and camera data for autonomous aerial navigation. His Ph.D. research (2017-2023) involved deep learning for limited data, emphasizing convolutional neural networks and biometric applications. Dimitrios contributed to the DeepSky project on cloud type estimation using multi-sensor data and worked on Greek lip reading datasets employing deep sequential models. He also participated in RoadEye, developing AI solutions for road condition monitoring, pothole, and speed bump detection. Throughout his career, Dimitrios has utilized tools like Python, PyTorch, TensorFlow, Qiskit, and Matlab, continuously merging theoretical innovation with practical applications in computer vision, AI, and quantum technologies.

Awards and Honors

Dimitrios Tsourounis has received notable recognition for his academic and research excellence. He was awarded a prestigious scholarship from the Greek State Scholarships Foundation (IKY) to support his Ph.D. studies, reflecting his outstanding merit. Throughout his academic career, Dimitrios graduated summa cum laude for his M.Sc. and magna cum laude for his B.Sc., highlighting consistent academic distinction. His research contributions have been supported by competitive European Union and Greek national funding programs, including co-funding for projects such as DeepSky and RoadEye. Dimitrios has also been acknowledged within the quantum computing and AI research communities for pioneering integration of machine learning with quantum frameworks. His work has earned invitations to collaborate with leading academic and industry partners, reinforcing his reputation as an innovative scientist. While yet to accumulate traditional prize awards, his growing publication record and project leadership positions underscore his impact and future promise in computer science and quantum technologies.

Research Focus 

Dimitrios Tsourounis’s research centers on computer vision, deep learning, and quantum machine learning, with a particular focus on addressing challenges of limited data availability in neural network training. His Ph.D. work pioneered transfer learning and knowledge distillation methods tailored to biometric security and pattern recognition. Currently, Dimitrios explores quantum-enhanced machine learning algorithms leveraging variational quantum circuits to improve performance on complex scientific and industrial problems. His expertise also spans multimodal data fusion, combining radar and visual data in autonomous aerial systems to enhance object detection accuracy. Additionally, he investigates sequential deep learning architectures for tasks such as lip reading in the Greek language and environmental sensing through cloud type recognition using thermal and all-sky cameras. Dimitrios integrates classical machine learning frameworks like PyTorch with quantum programming tools such as Qiskit and Pennylane, pushing the frontier of hybrid classical-quantum AI. His work aims to bridge theoretical advances and practical applications across fields including cryptography, healthcare, and autonomous vehicles.

Publications 

  • “Deep Sparse Coding for Signal Representation”

  • “Neural Networks for Biometric Applications with Limited Data”

  • “Quantum Variational Circuits in Machine Learning”

  • “Fusion of Radar and RGB Data in UAV Object Detection”

  • “Lip Reading Greek Words Using Sequential Deep Learning”

  • “Cloud Type Estimation with All-Sky and Thermal Cameras”

  • “Real-Time Road Condition Monitoring via Computer Vision”

  • “Knowledge Distillation Techniques in Convolutional Neural Networks”

Conclusion

Dimitrios Tsourounis exemplifies a forward-thinking computer scientist, seamlessly integrating deep learning and quantum computing to tackle real-world challenges. His academic excellence, coupled with his innovative research in limited-data neural networks and quantum-enhanced AI, positions him as a leading researcher in computer vision and machine learning. Dimitrios’s contributions advance both theoretical knowledge and practical solutions across diverse sectors, from autonomous systems to pharmaceuticals. His dedication and interdisciplinary approach promise significant future impact in computer science and emerging quantum technologies.

 

Alimul Rajee | Computer Science | Young Scientist Award

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Mr. Alimul Rajee | Computer Science | Young Scientist Award

Mr. Alimul Rajee, Dept. of ICT, Comilla University, Kotbari, Bangladesh

Alimul Rajee is a Lecturer at the Department of Information and Communication Technology, Comilla University. His academic journey includes a stellar performance with a CGPA of 3.69 in his M.Sc. in Information Technology from Jahangirnagar University. Rajee’s research interests span Machine Learning, Data Science, Artificial Intelligence, Cyber Security, and Robotics, with a focus on real-world applications such as traffic accident data analysis and smart waste management. He has contributed significantly to several research projects, and his work has been published in prestigious journals, such as Knowledge-Based Systems and Heliyon. In addition to his research, Rajee is an active educator, mentoring students and supervising projects in areas like IoT and deep learning. His dedication extends beyond the classroom to extracurricular activities, where he has received multiple awards and recognitions, including an international award for his project at Fujitsu Research Institute in Tokyo.

Professional Profile

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Suitability Summary of Young Scientist Awards

Alimul Rajee stands out as an excellent candidate for the Research for Young Scientist Award due to his impressive academic achievements, significant research contributions, and commitment to advancing in the fields of Machine Learning, Data Science, Artificial Intelligence, Cyber Security, and IoT. He has a strong educational background, earning his M.Sc. and B.Sc. with high CGPA rankings from Jahangirnagar University, which reflects his deep knowledge and dedication to his field.

Rajee’s research work is highly commendable, with several publications in reputable, Scopus-indexed journals such as Knowledge-Based Systems and Heliyon, where he has contributed to the development of novel algorithms and methodologies, especially in big data analysis, sentiment analysis, and AI-based applications. His ongoing and completed research projects, including a hybrid smart waste management system and aspect-based sentiment analysis for Bengali text, further showcase his innovative thinking and practical application of emerging technologies to address real-world problems. Additionally, his leadership in supervising over 40 academic projects and his participation in global training programs, like those held at the Fujitsu Research Institute in Japan, illustrate his proactive approach to both learning and teaching.

🎓  Education

Alimul Rajee completed his M.Sc. in Information Technology from Jahangirnagar University, securing a CGPA of 3.69 out of 4, ranking 6th in his batch. Before this, he earned his B.Sc. (Hons.) in the same field, also from Jahangirnagar University, with a CGPA of 3.71, again securing the 6th position. Rajee’s academic excellence dates back to his secondary education, where he achieved the highest CGPA of 5.00 in both his HSC and SSC exams from Govt. Ananadamohan College and Islamnagar Sailampur High School. His continuous pursuit of academic excellence earned him merit-based scholarships throughout his education. His academic prowess has laid a strong foundation for his research and professional career, as he continues to excel in his field with a focus on cutting-edge technologies such as AI and IoT.

💼 Professional Experience

Alimul Rajee’s professional career began as a Junior Data Scientist at Oculin Tech BD Ltd., where he worked from March 2020 to May 2021. He then served as a Senior Officer (ICT) at Sonali Bank PLC for a brief period before becoming a Lecturer at Comilla University in November 2021, where he currently teaches. Rajee’s teaching journey includes roles at Bangladesh University of Business and Technology (BUBT) and Jahangirnagar University (IIT-JU), where he was a Teacher Assistant. His extensive experience also includes supervising over 40 academic projects focused on machine learning, deep learning, and IoT. As an educator, he fosters a positive learning environment, guiding students through complex technical concepts while contributing to the development of innovative research and real-world applications.

🏅  Awards and Recognition

Alimul Rajee’s achievements have been recognized at both national and international levels. He has received several awards, including the UGC Research Grant from Comilla University for consecutive fiscal years, which is a testament to his research capabilities. Rajee’s work has been recognized by prestigious institutions such as Fujitsu Research Institute (FRI) in Tokyo, where his final project won 1st prize. He has also been a reviewer for the International Conference on Embracing Industry 4.0 for Sustainable Business Growth. His consistent academic and research excellence has earned him regular merit-based scholarships and fellowships, such as the National Science & Technology Fellowship from the ICT Division of Bangladesh.

🌍 Research Skills On Computer Science

Alimul Rajee specializes in the application of cutting-edge technologies such as Machine Learning, Artificial Intelligence, Cyber Security, and IoT. His research includes a diverse range of topics like traffic accident data analysis, sentiment analysis of Bengali text, and smart waste management. Rajee has honed his expertise in Data Science and deep learning methods, contributing to several high-impact publications in renowned journals such as Knowledge-Based Systems and Heliyon. His current research projects include Aspect-Category-Opinion-Sentiment Quad Extraction for Bengali Text and a Hybrid Smart Waste Management Technique using Deep Learning and IoT. Rajee’s proficiency in data analysis, algorithm design, and system integration showcases his strong research skills and his commitment to advancing technology for societal benefit.

📖 Publication Top Notes

  • “Aspect-based sentiment analysis for Bengali text using bidirectional encoder representations from transformers (BERT)”
    • Authors: MM Samia, A Rajee, MR Hasan, MO Faruq, PC Paul
    • Citation: International Journal of Advanced Computer Science and Applications, 13(12)
    • Year: 2022
  • “Detecting the provenance of price hike in agri-food supply chain using private Ethereum blockchain network”
    • Authors: MH Sayma, MR Hasan, M Khatun, A Rajee, A Begum
    • Citation: Heliyon, 10(11)
    • Year: 2024
  • “Analyzing depression on social media utilizing machine learning and deep learning methods”
    • Authors: PC Paul, MT Ahmed, MR Hasan, A Rajee, K Sultana
    • Citation: Indian Journal of Computer Science and Engineering, 14(5), 740-746
    • Year: 2023
  • “WFFS—An ensemble feature selection algorithm for heterogeneous traffic accident data analysis”
    • Authors: A Rajee, MS Satu, MZ Abedin, KMA Ali, S Aloteibi, MA Moni
    • Citation: Knowledge-Based Systems, 113089
    • Year: 2025

Nagalakshmi R Velmurugan | Computer Science | Best Faculty Award

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Dr. Nagalakshmi R Velmurugan | Computer Science | Best Faculty Award

👤 Dr. Nagalakshmi R Velmurugan, SRM institute of science and Technology, India

Dr. R. Nagalakshmi, a dedicated academician and researcher in Computer Science Engineering, has over 12 years of teaching and administrative experience. She currently serves as an Associate Professor at SRM Institute of Science and Technology, Ramapuram, Chennai. Dr. Nagalakshmi completed her Ph.D. in Computer Science Engineering from Kalinga University, focusing on grid and cluster computing. She holds an M.E. and B.E. in Computer Science Engineering from Anna University, Chennai, and a Diploma in Computer Science from Sri Balaji Polytechnic College. Her career is marked by a passion for research in AI, data science, and operating systems, complemented by proficiency in Python, Power BI, and SQL. A dynamic educator, she excels in fostering innovation and creativity through seminars, webinars, and technical events. With numerous publications and impactful projects, Dr. Nagalakshmi is committed to advancing knowledge and nurturing the next generation of technology leaders.

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🌟 Suitability For Research for Best Faculty Award

Dr. R. Nagalakshmi demonstrates strong suitability for the Research for Best Faculty Award based on her robust academic background, extensive teaching experience, and contributions to academia and research. Her qualifications, including a Ph.D. in Computer Science Engineering, coupled with her teaching experience of over 12 years, reflect her dedication to fostering knowledge and innovation in the field. Her expertise spans diverse areas such as AI-Machine Learning, Data Science, Operating Systems, and Data Structures, showcasing her alignment with contemporary advancements in technology and education.

🎓 Education 

Dr. R. Nagalakshmi pursued her Ph.D. in Computer Science Engineering at Kalinga University, focusing on grid and cluster computing technologies. She earned her M.E. in Computer Science Engineering from Jaya Engineering College, Chennai, affiliated with Anna University, achieving a commendable 74.3%. Her B.E. degree in Computer Science Engineering was completed at Sri Ramanujar Engineering College, Chennai, with a score of 72.42%. Prior to her engineering studies, she obtained a Diploma in Computer Science from Sri Balaji Polytechnic College, Chennai, securing 80.42%. Dr. Nagalakshmi’s strong foundation began with her exceptional performance in her 10th standard, scoring 87%. Throughout her academic journey, she consistently demonstrated a deep interest in technology, which has become the cornerstone of her illustrious teaching and research career.

💼  Professional Experience

Dr. R. Nagalakshmi brings 12 years of rich teaching and leadership experience to the field of Computer Science. She is currently an Associate Professor at SRM Institute of Science and Technology, Ramapuram, Chennai. Previously, she served as Head and Associate Professor at Kakinada Institute of Technological Sciences, Andhra Pradesh, where she spearheaded academic and industrial collaborations. Her earlier roles include Assistant Professor positions at ARS College of Engineering, St. Joseph’s Institute of Technology, and Dhanalakshmi College of Engineering in Chennai, where she mentored countless students. She has organized webinars, seminars, and technical events, such as an international webinar on generative AI trends and workshops on cloud computing using AWS. Her career reflects a dedication to integrating academic excellence with industry relevance, creating a dynamic learning environment for students.

🏅 Awards and Recognitions 

Dr. R. Nagalakshmi’s contributions to academia and research have been widely recognized. She organized an international webinar on generative AI trends in 2023 and conducted a national-level seminar on emerging software technologies. Her efforts in bridging academia and industry include arranging industrial visits for students and delivering guest lectures on topics such as cloud computing and Android app development. As an active participant in fostering innovation, she has received accolades for her teaching and event organization skills. Dr. Nagalakshmi’s initiatives, including technical events like Brainblitz, have significantly enriched the academic experience at institutions like SRM Institute of Science and Technology. Her achievements underscore her commitment to advancing knowledge, fostering student growth, and contributing to the field of Computer Science.

🌍 Research Skills On Computer Science

Dr. R. Nagalakshmi specializes in AI, machine learning, data science, and operating systems, with a focus on cutting-edge technologies such as grid and cluster computing. Her Ph.D. research delved into enhancing computational efficiency through grid computing infrastructures, utilizing middleware like the Globus Toolkit. Proficient in Python, Power BI, and database technologies like SQL and Oracle, she leverages these tools in innovative research and academic projects. Dr. Nagalakshmi has expertise in network security, software project management, and algorithm design, making her a versatile researcher. She is passionate about exploring emerging fields such as generative AI and has contributed significantly to academia through impactful publications and technical events. Her ability to translate complex concepts into actionable insights for students and researchers defines her excellence in research.

📖 Publication Top Notes

  • Weld quality monitoring via machine learning-enabled approaches
    • Authors: Raj, A., Chadha, U., Chadha, A., Chandramohan, V., Hadidi, H.
    • Journal: International Journal on Interactive Design and Manufacturing
    • Year: 2023
    • Citations: 14
  • Green manufacturing via machine learning enabled approaches
    • Authors: Raj, A., Gyaneshwar, A., Chadha, U., Chandramohan, V., Hadidi, H.
    • Journal: International Journal on Interactive Design and Manufacturing
    • Year: 2022
    • Citations: 6
  • Feasibility of friction stir welding for in-space joining processes: a simulation-based experimentation
    • Authors: Khanna, M., Chadha, U., Banerjee, A., Jayakumar, K., Karthikeyan, B.
    • Journal: International Journal on Interactive Design and Manufacturing
    • Year: 2022
    • Citations: 2
  • Industrial internet of things in intelligent manufacturing: a review, approaches, opportunities, open challenges, and future directions
    • Authors: Gupta, P., Krishna, C., Rajesh, R., Nagalakshmi, R., Chandramohan, V.
    • Journal: International Journal on Interactive Design and Manufacturing
    • Year: 2022
    • Citations: 35
  • Quality control tools and digitalization of real-time data in sustainable manufacturing
    • Authors: Menon, A.P., Lahoti, V., Gunreddy, N., Jayakumar, K., Karthikeyan, B.
    • Journal: International Journal on Interactive Design and Manufacturing
    • Year: 2022
    • Citations: 11
  • Caption Generation Based on Emotions Using CSPDenseNet and BiLSTM with Self-Attention
    • Authors: Priya, K., Karthika, P., Kaliappan, J., Nagalakshmi, R., Molla, B.
    • Journal: Applied Computational Intelligence and Soft Computing
    • Year: 2022
    • Citations: 3
  • Semantic Approach for Evaluation of Energy Storage Technologies under Fuzzy Environment
    • Authors: Nagaraju, D., Chiranjeevi, C., Rajasekhar, Y., Nagalakshmi, R., Paramasivam, V.
    • Journal: Advances in Fuzzy Systems
    • Year: 2022
    • Citations: 6
  • A Survey of Machine Learning in Friction Stir Welding, including Unresolved Issues and Future Research Directions
    • Authors: Chadha, U., Selvaraj, S.K., Gunreddy, N., Kumar, R.L., Adefris, A.
    • Journal: Material Design and Processing Communications
    • Year: 2022
    • Citations: 29