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.

 

SAMEERCHAND PUDARUTH | Artificial Intelligence | Academic Excellence Award

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Assoc. Prof. Dr. SAMEERCHAND PUDARUTH | Artificial Intelligence | Academic Excellence Award

Assoc. Prof. Dr. SAMEERCHAND PUDARUTH, University of Mauritius, Mauritius

Dr. Sameerchand Pudaruth is an Associate Professor in the Faculty of Information, Communication & Digital Technologies at the University of Mauritius. With a PhD in Artificial Intelligence, his expertise spans machine learning, computational linguistics, and data science. His academic journey reflects a deep commitment to technological advancement and knowledge dissemination. Having served as Head of the ICT Department (2019–2021), he played a key role in shaping academic policies and research initiatives. Dr. Pudaruth is an accomplished author and a sought-after researcher, contributing significantly to AI, distributed systems, and digital transformation. His membership in prestigious organizations such as IEEE, ACM, and IAENG highlights his standing in the global research community. Beyond academia, he is dedicated to mentoring students, fostering innovation, and driving interdisciplinary collaboration in AI. His work continues to bridge the gap between theoretical research and practical AI applications, making significant strides in Mauritius and beyond.

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Suitability for the Research for Best Researcher Award – Associate Professor Dr. Sameerchand Pudaruth

Dr. Sameerchand Pudaruth is a distinguished academic and researcher in Artificial Intelligence, Computer Science, and related fields, with a strong background in teaching, research, and leadership. With over two decades of experience, he has contributed significantly to the advancement of AI, distributed systems, multimedia, and computational linguistics. His PhD in Artificial Intelligence, combined with his legal studies, positions him uniquely at the intersection of AI and law, demonstrating an interdisciplinary approach to research.

His extensive publication record, including book chapters, conference proceedings, and journal articles, highlights his dedication to pushing the boundaries of AI, machine learning, and computational methodologies. His research contributions in legal text classification, intelligent systems, and IT support services optimization have real-world applications, making his work both academically rigorous and practically relevant. His leadership roles, including serving as Head of the ICT Department and holding senior positions in IEEE and ACM, reflect his commitment to advancing research and fostering collaboration in the global research community.

🎓 Education

Dr. Sameerchand Pudaruth holds a PhD in Artificial Intelligence from the University of Mauritius, awarded in 2020, focusing on AI-driven decision-making systems. His academic portfolio includes an MSc in Computer Science with a specialization in Distributed Systems and Multimedia (2004–2006) and a BSc (Hons) in Computer Science and Engineering (First Class) from the same institution (2000–2003). In addition, he pursued legal studies, earning an LLB from the University of London (2009–2012) and completing the Law Practitioner’s Vocational Course (2013). This diverse educational background equips him with a unique interdisciplinary perspective, blending AI, computational intelligence, and legal analytics. His continuous professional development is evident through active participation in research forums, conferences, and international collaborations. Dr. Pudaruth’s academic journey reflects a commitment to lifelong learning, innovation, and thought leadership in artificial intelligence and digital technologies.

💼 Professional Experience

Dr. Sameerchand Pudaruth has been an integral part of the University of Mauritius since 2007. Currently serving as an Associate Professor (since 2022), he previously held the positions of Senior Lecturer (2016–2022) and Lecturer (2007–2016). He also served as Head of the ICT Department (2019–2021), where he spearheaded academic advancements and research collaborations. His career is marked by expertise in AI, machine learning, and data-driven technologies, leading various projects focused on intelligent systems. He has mentored numerous postgraduate students and contributed extensively to curriculum development. Dr. Pudaruth’s industry collaborations have reinforced his reputation as a pioneer in applied AI research. His leadership in conferences and symposiums underscores his commitment to advancing knowledge in computational sciences. As an educator, researcher, and innovator, he continuously pushes the boundaries of AI applications, influencing both academia and industry.

🏅 Awards and Recognition

Dr. Sameerchand Pudaruth’s contributions to AI and computational research have earned him numerous accolades. He has been a Senior IEEE Member since 2020, recognizing his significant professional achievements. His role as a founding member and Vice-Chair of IEEE Mauritius Section (2018–2021) highlights his leadership in fostering AI research communities. He has received research grants and recognition for outstanding publications in AI, machine learning, and computational linguistics. His book “Python in One Week” (2010) and multiple Springer book chapters have cemented his reputation in AI education. His work on machine learning applications in law and data science has been widely cited, further amplifying his global impact. His membership in ACM, IAENG, and the Association for Computational Linguistics reflects his standing in the international AI research community. Through groundbreaking research, academic leadership, and scholarly contributions, Dr. Pudaruth continues to be a driving force in AI innovation.

🌍 Research Skills On Artificial Intelligence

Dr. Sameerchand Pudaruth specializes in artificial intelligence, machine learning, and computational linguistics. His expertise spans natural language processing, legal informatics, and AI-driven decision-making models. He has pioneered research in AI applications for law, healthcare, and distributed systems. With a deep understanding of neural networks, deep learning, and intelligent automation, he has contributed significantly to AI-driven knowledge systems. His work includes feature selection using evolutionary algorithms, predictive modeling, and sentiment analysis. He has led interdisciplinary collaborations to advance AI ethics, data privacy, and algorithmic fairness. His ability to translate complex AI concepts into real-world applications has led to impactful research publications. As a member of international AI organizations, he remains at the forefront of technological advancements, constantly exploring innovative solutions. Dr. Pudaruth’s research continues to influence academia, industry, and public policy, making AI more accessible and applicable across diverse domains.

 📖 Publication Top Notes

  1. Plant leaf recognition using shape features and colour histogram with K-nearest neighbour classifiers
    • Authors: T. Munisami, M. Ramsurn, S. Kishnah, S. Pudaruth
    • Citations: 262
    • Year: 2015
  2. People factors in agile software development and project management
    • Authors: V. Lalsing, S. Kishnah, S. Pudaruth
    • Citations: 195
    • Year: 2012
  3. Predicting the price of used cars using machine learning techniques
    • Authors: S. Pudaruth
    • Citations: 183
    • Year: 2014
  4. Automatic Recognition of Medicinal Plants using Machine Learning Techniques
    • Authors: A. Begue, V. Kowlessur, U. Singh, F. Mahomoodally, S. Pudaruth
    • Citations: 123
    • Year: 2017
  5. A review of mobile ad hoc NETwork (MANET) Protocols and their Applications
    • Authors: D. Ramphull, A. Mungur, S. Armoogum, S. Pudaruth
    • Citations: 98
    • Year: 2021
  6. Authorship attribution using stylometry and machine learning techniques
    • Authors: H. Ramnial, S. Panchoo, S. Pudaruth
    • Citations: 71
    • Year: 2016
  7. Sentiment analysis from Facebook comments using automatic coding in NVivo 11
    • Authors: S. Pudaruth, S. Moheeputh, N. Permessur, A. Chamroo
    • Citations: 53
    • Year: 2018
  8. Forgotten, excluded or included? Students with disabilities: A case study at the University of Mauritius
    • Authors: U. Singh, S. Pudaruth, R. Gunputh
    • Citations: 30
    • Year: 2017
  9. Resource allocation in 4G and 5G networks: A review
    • Authors: L.N. Degambur, A. Mungur, S. Armoogum, S. Pudaruth
    • Citations: 29
    • Year: 2021
  10. SuperFish: A Mobile Application for Fish Species Recognition using Image Processing Techniques and Deep Learning
  • Authors: P. Sameerchand, N. Nadeem, A. Chandani, K. Somveer, V. Munusami, S. Pudaruth
  • Citations: 26
  • Year: 2021

WEI-CHENG LIEN | Artificial Intelligence | Best Researcher Award

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Dr. WEI-CHENG LIEN | Artificial Intelligence | Best Researcher Award

👤 Dr. WEI-CHENG LIEN, Hyson Technology Inc, Taiwan

Wei-Cheng Lien is the CEO and Co-Founder of HysonTech Inc., based in Taiwan, where he leads the company’s AIoT solutions for various industries. With a Ph.D. in Electrical Engineering from National Cheng Kung University, Lien specializes in AI, AIoT hardware/software integration, and digital transformation. He has held significant leadership roles across diverse organizations, including his work as a director for the Taiwan Artificial Intelligence Association and as an industry technology advisor for the National Applied Research Laboratories. Lien’s contributions to fields such as medical diagnostics, smart traffic enforcement, and manufacturing automation have earned him recognition globally. His work has influenced both academia and industry, with numerous awards and patents to his name. He continues to innovate at the intersection of AI and IoT, driving digital transformation and leading key projects like Taiwan Taoyuan International Airport Terminal 3.

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🌟 Research for Best Researcher Award: Wei-Cheng Lien

Suitability for the Award:

Wei-Cheng Lien is exceptionally suited for the Research for Best Researcher Award due to his remarkable achievements in both the academic and entrepreneurial realms, coupled with his extensive experience in the field of electrical engineering and artificial intelligence (AI). With a Ph.D. in Electrical Engineering (EE) from National Cheng Kung University and a track record of over 50 technical papers and 9 patents, Dr. Lien has made significant contributions to various cutting-edge areas, such as AI, AIoT (Artificial Intelligence of Things) hardware/software integration, and digital transformation.

As the CEO of HysonTech Inc., he has been instrumental in driving innovative AIoT solutions across diverse industries, from aquaculture to medical diagnostics, emphasizing his capability to translate research into impactful real-world applications. His leadership extends beyond his company, as he holds prominent advisory roles with leading institutions like the Taiwan National Science and Technology Council and the Institute for Information Industry. His leadership in AI and technology is further demonstrated by his contributions to the Taiwan Artificial Intelligence Association and several high-profile projects such as the Taiwan Taoyuan International Airport Terminal 3 development.

🎓 Education 

Wei-Cheng Lien earned his Ph.D. in Electrical Engineering (EE) from National Cheng Kung University (NCKU), Taiwan, where he achieved a remarkable GPA of 4.0. His educational journey also includes a Bachelor’s degree in EE from NCKU, where he earned a GPA of 3.4. During his academic tenure, Lien demonstrated a strong focus on Artificial Intelligence, AIoT, and digital transformation, with his research laying the groundwork for his subsequent professional achievements. Lien’s time at Duke University as a visiting scholar further broadened his perspective, and his contributions to AI and electronics research gained significant recognition. His education, coupled with extensive hands-on experience in AI and hardware/software integration, has shaped him into a leader in the industry. Lien’s academic excellence and innovation are the bedrock upon which his diverse professional experiences and entrepreneurial ventures are built.

💼  Professional Experience

Wei-Cheng Lien is the CEO and Co-Founder of HysonTech Inc., where he leads innovative AIoT solutions across sectors like aquaculture, smart traffic enforcement, and medical diagnostics. Under his leadership, HysonTech integrates AI technologies into hardware and software systems, offering complete solutions to its clients. Prior to this, Lien served as the CTO of Slash Living Culture Company, where he developed reed-based plant straws and building materials, incorporating AIoT monitoring techniques. His career also includes his role as Manager of the Intelligence System Division at AVITONE CO., LTD., where he focused on image system integration for advanced X-ray scanners. Lien’s earlier experience at MediaTek Inc. as Senior Engineer and Fellow Student further honed his expertise in AI and computing technologies. His extensive professional experience spans AI integration, digital transformation, and innovative product development, driving growth and technological advancement in multiple industries.

🏅Awards and Recognition

Wei-Cheng Lien has been honored with over 60 prestigious awards throughout his career. Notably, he was named the 2025 Outstanding Alumni of Taichung Municipal Taichung First Senior High School and received the 2024 Taiwan AI Award at the AI Taiwan x Future Commerce Exhibition. Lien’s achievements in AI and digital transformation were recognized with the 2024 Taiwan InnoTech Expo’s Two Invention Medals, along with Best Paper Awards at various conferences, including the Investigative Technology and Forensic Science Symposium. He was also awarded the 2024 Best Conference Paper Award at the IEEE International Conference on Electronic Communications, Internet of Things, and Big Data. Lien’s entrepreneurial success was acknowledged with the 2024 Best Startup Selection in Beijing and other notable innovation awards. Additionally, he was recognized with the 2023 EE Times Asia Award for Best AI Product of the Year and numerous awards from government and industry organizations for his contributions to AI and digital transformation.

🌍 Research Skills Artificial Intelligence

Wei-Cheng Lien’s research skills lie at the forefront of AI, AIoT integration, and digital transformation. His expertise spans IC design, testing, diagnosis, and software-hardware systems integration, which allows him to create innovative solutions across a range of industries. Lien’s work in AI computing, particularly in CPU DFT architectures and low-cost test techniques for System on Chips (SoCs), has been instrumental in reducing test costs and improving design accuracy. His research on output selection for SOC debug systems has earned global recognition for reducing test response volumes and minimizing area overhead. Lien has authored over 50 technical papers and holds 9 patents, further demonstrating his proficiency in cutting-edge research. His ability to bridge the gap between theoretical knowledge and practical application has been a key factor in his contributions to AI-driven industries such as healthcare, smart cities, and advanced manufacturing. Lien’s ongoing research continues to push the boundaries of AI and IoT technology.

📖 Publication Top Notes

  • A rapid household mite detection and classification technology based on artificial intelligence-enhanced scanned images
    • Authors: Lin, L.H.-M., Lien, W.-C., Cheng, C.Y.-T., Lai, Y.-T., Peng, Y.-T.
    • Citation: Internet of Things (The Netherlands), 2025, 29, 101484
  • Image Demoiréing via Multiscale Fusion Networks With Moiré Data Augmentation
    • Authors: Peng, Y.-T., Hou, C.-H., Lee, Y.-C., Lin, Y.-T., Lien, W.-C.
    • Citation: IEEE Sensors Journal, 2024, 24(12), pp. 20114–20127
    • Citations: 3
  • Fully automated learning and predict price of aquatic products in Taiwan wholesale markets using multiple machine learning and deep learning methods
    • Authors: Lai, Y.-T., Peng, Y.-T., Lien, W.-C., Liao, C.-J., Chiu, Y.-S.
    • Citation: Aquaculture, 2024, 586, 740741
    • Citations: 2
  • Traffic Violation Detection via Depth and Gradient Angle Change
    • Authors: Peng, Y.-T., Liu, C.-Y., Liao, H.-H., Lien, W.-C., Hsu, G.-S.J.
    • Citation: 2022 IEEE 7th International Conference on Intelligent Transportation Engineering, ICITE 2022, 2022, pp. 326–330
    • Citations: 1
  • Unveiling of How Image Restoration Contributes to Underwater Object Detection
    • Authors: Peng, W.-Y., Peng, Y.-T., Lien, W.-C., Chen, C.-S.
    • Citation: 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021, 2021
    • Citations: 7
  • Output bit selection methodology for test response compaction
    • Authors: Lien, W.-C., Lee, K.-J.
    • Citation: Proceedings – International Test Conference, 2016, 0, 7805873
  • A Test-per-cycle BIST architecture with low area overhead and no storage requirement
    • Authors: Shiao, C.-M., Lien, W.-C., Lee, K.-J.
    • Citation: 2016 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2016, 2016, 7482556
    • Citations: 11
  • Efficient LFSR Reseeding Based on Internal-Response Feedback
    • Authors: Lien, W.-C., Lee, K.-J., Hsieh, T.-Y., Chakrabarty, K.
    • Citation: Journal of Electronic Testing: Theory and Applications (JETTA), 2014, 30(6), pp. 673–685
    • Citations: 7
  • Output-bit selection with X-avoidance using multiple counters for test-response compaction
    • Authors: Lien, W.-C., Lee, K.-J., Chakrabarty, K., Hsieh, T.-Y.
    • Citation: Proceedings – 2014 19th IEEE European Test Symposium, ETS 2014, 2014, 6847823
    • Citations: 3
  • Output selection for test response compaction based on multiple counters
    • Authors: Lien, W.-C., Lee, K.-J., Chakrabarty, K., Hsieh, T.-Y.
    • Citation: Technical Papers of 2014 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2014, 2014, 6834865
    • Citations: 2

 

Nikolaos Freris | Robotics | Best Researcher Award

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Prof. Dr. Nikolaos Freris | Robotics | Best Researcher Award

Prof. Dr. Nikolaos Freris, University of Science and Technology of China, China

Dr. Nikolaos M. Freris is a distinguished academic and researcher specializing in computer science, robotics, and artificial intelligence. Currently serving as a professor and Vice Dean at the University of Science and Technology of China (USTC), he leads the AIoT Laboratory, advancing cutting-edge innovations in distributed learning and cyber-physical systems. Dr. Freris earned his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, graduating with a perfect GPA of 4.0/4.0. With extensive international experience, including positions at IBM Research, EPFL, and NYU Abu Dhabi, his work bridges theoretical advancements and practical applications in intelligent systems. A prolific speaker and educator, he has delivered numerous keynotes and distinguished lectures worldwide. His passion for innovation and knowledge-sharing solidifies his reputation as a leader in AI-driven technologies, fostering global collaborations and pioneering impactful research.

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Prof. Dr. Nikolaos Freris Summary of Suitability for the Award

Nikolaos M. Freris is an exceptionally accomplished researcher and academic, making him a strong candidate for the Research for Best Researcher Award. His educational background is impeccable, with a Ph.D. in Electrical and Computer Engineering and two master’s degrees (Mathematics and Electrical & Computer Engineering) from the University of Illinois at Urbana-Champaign, all earned with perfect GPAs. His work bridges cutting-edge domains such as systems, decision and control, communication networks, and optimization, demonstrating a deep understanding of complex interdisciplinary challenges.

Professionally, Dr. Freris has held prestigious positions at globally recognized institutions, including his current role as a professor at the University of Science and Technology of China (USTC), where he also serves as Vice Dean of the International College and Director of the AIoT Laboratory.

🎓 Education 

Dr. Nikolaos M. Freris holds a robust academic foundation in engineering and computer science. He received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, specializing in systems, decision, and control, and achieving a perfect 4.0/4.0 GPA. During his doctoral studies, his groundbreaking dissertation explored optimization models for wireless networks, including clock synchronization and video streaming. He also earned dual Master’s degrees from the same university in Mathematics and Electrical and Computer Engineering. Prior to his postgraduate pursuits, he graduated summa cum laude with a Diploma in Electrical and Computer Engineering from the National Technical University of Athens, where his thesis addressed innovative approaches in biomedical engineering. This exceptional academic journey underpins his expertise in robotics, AI, and distributed systems, driving his impactful research and academic contributions globally.

💼  Professional Experience

Dr. Nikolaos M. Freris boasts a dynamic career in academia and industry. Since 2019, he has been a Professor of Computer Science at USTC, where he directs the AIoT Laboratory, pioneering advances in distributed learning and robotics. He also serves as Vice Dean of the International College, fostering global academic partnerships. Previously, he was an Assistant Professor at NYU Abu Dhabi and a Global Network Assistant Professor at NYU Tandon, leading research on cyber-physical systems. His industry experience includes roles as a Senior Research Scientist at EPFL, managing Qualcomm-funded projects, and as a Postdoctoral Fellow at IBM Research Zurich. His early career featured internships at Deutsche Telekom and Xerox, where he explored innovative computational solutions. With a strong track record of leadership in interdisciplinary projects, Dr. Freris continues to bridge the gap between theoretical research and real-world applications.

🏅  Awards and Recognition

Dr. Nikolaos M. Freris is a recipient of numerous prestigious awards recognizing his contributions to computer science and engineering. His academic excellence is reflected in his perfect GPA achievements during his Ph.D. and Master’s studies. He has delivered keynotes at leading conferences such as the International Conference on Internet of Things and AIoT forums. His research on distributed learning, robotics, and AIoT has earned him accolades, including invited talks at institutions like Zhejiang University and international symposiums. As a leader in global academic initiatives, he was recognized for his innovative teaching and impactful research by organizations such as IEEE and CAS. Dr. Freris’s accolades underscore his commitment to advancing intelligent systems and fostering collaborations across disciplines, enhancing the global understanding of cutting-edge technologies.

🌍 Research Skills On Robotics 

Dr. Nikolaos M. Freris demonstrates exceptional research skills in robotics, distributed systems, and artificial intelligence. His expertise spans optimization theory, machine learning, and cyber-physical systems, with applications in AIoT and intelligent transportation. He specializes in communication-efficient algorithms, real-time data learning, and bio-inspired robotics, contributing to sustainable solutions for modern technological challenges. As the founder and director of AIoT and Cyberphysical Systems Labs, he leads transformative research initiatives that bridge theoretical models and real-world implementation. His methodological rigor and creative problem-solving skills are evident in his widely cited publications and pioneering keynote addresses. Dr. Freris’s ability to synthesize complex systems into actionable innovations positions him as a thought leader in emerging AI and robotics domains.

📖 Publication Top Notes

Title: Randomized extended Kaczmarz for solving least squares
  • Authors: A. Zouzias, N. M. Freris
    Journal: SIAM Journal on Matrix Analysis and Applications
    Citations: 349
    Year: 2013
Title: Fundamental limits on synchronizing clocks over networks
  • Authors: N. M. Freris, S. R. Graham, P. R. Kumar
    Journal: IEEE Transactions on Automatic Control
    Citations: 270
    Year: 2010
Title: Fundamentals of large sensor networks: Connectivity, capacity, clocks, and computation
  • Authors: N. M. Freris, H. Kowshik, P. R. Kumar
    Journal: Proceedings of the IEEE
    Citations: 151
    Year: 2010
Title: A new randomized block-coordinate primal-dual proximal algorithm for distributed optimization
  • Authors: P. Latafat, N. M. Freris, P. Patrinos
    Journal: IEEE Transactions on Automatic Control
    Citations: 89
    Year: 2019
Title: Fundamental limits on synchronization of affine clocks in networks
  • Authors: N. M. Freris, P. R. Kumar
    Conference: 2007 46th IEEE Conference on Decision and Control
    Citations: 79
    Year: 2007
Distortion-aware scalable video streaming to multinetwork clients
  • Authors: N. M. Freris, C. H. Hsu, J. P. Singh, X. Zhu
    Journal: IEEE/ACM Transactions on Networking
    Citations: 69
    Year: 2012
Fast distributed smoothing of relative measurements
  • Authors: N. M. Freris, A. Zouzias
    Conference: 2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
    Citations: 64
    Year: 2012
Multiplayer Stackelberg–Nash game for nonlinear system via value iteration-based integral reinforcement learning
  • Authors: M. Li, J. Qin, N. M. Freris, D. W. C. Ho
    Journal: IEEE Transactions on Neural Networks and Learning Systems
    Citations: 56
    Year: 2020
A synchrophasor data-driven method for forced oscillation localization under resonance conditions
  • Authors: T. Huang, N. M. Freris, P. R. Kumar, L. Xie
    Journal: IEEE Transactions on Power Systems
    Citations: 56
    Year: 2020
A model-based approach to clock synchronization
  • Authors: N. M. Freris, V. S. Borkar, P. R. Kumar
    Conference: Proceedings of the 48th IEEE Conference on Decision and Control (CDC)
    Citations: 53
    Year: 2009

Dr. SENTHIL G. A | Computer Science | Research Excellence Award

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Dr. SENTHIL G. A | Computer Science | Research Excellence Award🏆

Doctor. SENTHIL G. A, Agni College of Technology, India 🎓

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🌟Dr. G.A. Senthil: A Distinguished Career in Engineering and Technology 

🎓Early Academic Pursuits 

Dr. G.A. Senthil’s academic journey commenced with a Diploma in Computer Science and Engineering from the Technical Education Board, Tamil Nadu, where he graduated with a commendable 72% in 1991. He then pursued a Bachelor’s degree in Computer Science and Engineering from SIR. M. Visvesvaraya Institute of Technology, Bangalore University, graduating in 1997. His academic excellence continued with an M.Tech in Information Technology from Sathyabama University, Tamil Nadu, where he graduated with distinction in 2007. Dr. Senthil’s scholarly dedication culminated in a Ph.D. from Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, in 2022, with a thesis focused on enhancing energy-efficient cluster-based routing using hybrid particle swarm optimization for IoT sensor networks.

💼Professional Endeavors 

Dr. Senthil’s career spans over 27 years in various esteemed engineering colleges. His professional journey began at Sir M. Visvesvaraya Institute of Technology, Bangalore, as a Lecturer in Computer Science and Engineering. He subsequently held positions at Annai Mathammal Sheela Engineering College, Aarupadai Veedu Institute of Technology, and Dhaanish Ahmed College of Engineering, where he advanced from Lecturer to Senior Lecturer and eventually to Head of Department. He currently serves as an Associate Professor at AGNI College of Technology, Chennai. Dr. Senthil’s extensive teaching experience includes undergraduate and postgraduate courses, reflecting his deep commitment to education and student development.

🔍Contributions and Research Focus 

Dr. Senthil has made significant contributions to the field of computer science and engineering. His research interests include the Internet of Things (IoT), wireless sensor networks (WSN), and advanced algorithms. He has published 11 journal articles, 50 conference papers, and several book chapters in prestigious publications such as Springer and Wiley. His patent portfolio includes 7 published inventions and 5 grants. Dr. Senthil has also been involved in funded projects, contributing to the advancement of technology and innovation.

🏆Accolades and Recognition 

Throughout his illustrious career, Dr. Senthil has received numerous accolades. He was awarded the Best Researcher Award for the academic year 2023 by the Human Rights Association & ACT. His role as a journal reviewer for Springer, Elsevier, and Hindawi highlights his expertise and recognition in the academic community. Dr. Senthil has also been a session chair and technical program committee member for various conferences, further showcasing his leadership and influence in the field.

🌐Impact and Influence 

Dr. Senthil’s influence extends beyond academia through his active participation in professional societies such as ISTE, CSI, and SCRS. He has mentored numerous students and guided several research projects, fostering a culture of innovation and critical thinking. His contributions to curriculum development, including the publication of three books aligned with Anna University regulations, have significantly impacted engineering education.

🔮Legacy and Future Contributions 

As a dedicated educator and researcher, Dr. G.A. Senthil continues to shape the future of engineering and technology. His ongoing research and commitment to academic excellence ensure a lasting legacy in the field. Dr. Senthil’s future contributions are poised to inspire and guide the next generation of engineers and technologists, cementing his role as a pivotal figure in the advancement of computer science and engineering.

 

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Mrs. Sravani Nalluri | Computer Science and Engineering | Best Researcher Award

Published on by Academic Excellence

Mrs. Sravani Nalluri | Computer Science and Engineering | Best Researcher Award🏆

Mrs. Sravani Nalluri, VIT Vellore, India 🎓

Professional Profile

🌟Sravani Nalluri: A Comprehensive Overview

🎓Early Academic Pursuits

Sravani Nalluri’s academic journey began with a Bachelor’s degree in Electronics and Communication Engineering from Idhaya Engineering College for Women, Anna University, in 2006. She continued her education with a Master’s degree in Computer Science and Engineering from St. Joseph’s College of Engineering, Anna University, Chennai, in 2008. Her quest for knowledge led her to the Vellore Institute of Technology, where she pursued a Ph.D. in Computer Science and Engineering, with her thesis submitted in April 2024. Alongside, she completed a Junior Data Analyst Program from Npower Canada in August 2023, further diversifying her skill set.

💼Professional Endeavors

Sravani’s career has been marked by a 13-year tenure as an Assistant Professor in the Department of Computer Science and Engineering at VNR VJIET, Hyderabad. During her tenure, she excelled in teaching programming languages such as C and Java, and developed a deep understanding of data structures, algorithms, and software development. She has also held roles as a QA Consultant and Training Process Member at Zemoso Technologies, Hyderabad, from May 2022 to August 2022. Her professional memberships include being a life member of The Indian Society for Technical Education (ISTE) and a member of the Computer Society of India, Hyderabad Chapter.

🔍Contributions and Research Focus

Sravani has made significant contributions to computer science education and research. She has developed and taught both undergraduate and graduate courses, guided numerous major and minor projects, and participated in curriculum development. Her expertise extends to machine learning, deep learning, and cloud concepts. She has actively contributed to various technical roles, including being a Hackathon Coordinator and Lab In Charge, and has played a pivotal role in the NAAC and NBA accreditation processes.

🏆Accolades and Recognition

Throughout her career, Sravani has been recognized for her dedication and contributions. Her certifications include Microsoft AZ-900, IBM Data Analyst Professional Certificate, and specialized courses in AI, Big Data Analytics, and Natural Language Processing. These certifications highlight her commitment to continuous learning and staying updated with industry advancements.

🌐Impact and Influence

Sravani’s influence extends beyond academia. Her role as a faculty mentor, involvement in hackathons, and contributions to innovative projects reflect her impact on student development and the academic community. Her commitment to improving educational practices and integrating technology into teaching has had a lasting effect on her students and colleagues.

🔮Legacy and Future Contributions

As she continues her journey, Sravani Nalluri remains dedicated to advancing the field of computer science through her research and teaching. Her future contributions are poised to shape the next generation of computer scientists and engineers. Her ongoing research and commitment to educational excellence ensure a lasting legacy in the field.

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