Milind Cherukuri | Computer Science | Young Researcher Award

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Mr. Milind Cherukuri | Computer Science | Young Researcher Award

Salesforce Business Analyst & Administrator at University of North Texas, United States

Milind Cherukuri is a dynamic early-career researcher and technologist with a strong foundation in artificial intelligence, machine learning, and software engineering. With a Master’s in Computer Science from the University of North Texas, he has applied his expertise across leading organizations such as Caris Life Sciences, Amazon, and Infor. His research spans sentiment analysis, AI safety, LLM prompt engineering, and image segmentation, resulting in five peer-reviewed publications and presentations at major conferences like IEEE AI Summit and EEET 2024. Milind has a proven ability to translate research into real-world impact, particularly in healthcare, where he optimized clinical systems through AI-driven automation and data integration. Recognized as a Senior Member of IEEE in 2025, he actively contributes to the research community through peer review and technical leadership. His innovative mindset, technical depth, and cross-domain contributions position him as a strong candidate for the Young Researcher Award.

Professional Profile

Google Scholar

Education

Milind Cherukuri holds a Master’s degree in Computer Science from the University of North Texas, where he deepened his expertise in artificial intelligence, data science, and advanced software systems. Prior to that, he earned his Bachelor’s degree in Computer Science from SRM University, Chennai, India. His academic journey reflects a consistent focus on technical excellence, with coursework and projects covering machine learning, sentiment analysis, and cloud computing. During his graduate studies, Milind engaged in applied research initiatives and honed his skills in experimental design, statistical analysis, and academic writing. He leveraged these experiences to produce scholarly work and effectively bridge theory with practice. His education provided a strong foundation for multidisciplinary research, particularly in AI-driven applications across healthcare and enterprise environments. The blend of technical depth and research exposure during his formative academic years has directly influenced his ability to contribute meaningfully to both industrial innovation and scientific advancement.

Professional Experience

Milind Cherukuri’s professional journey spans prominent roles at Caris Life Sciences, Amazon, and Infor, reflecting a robust blend of research, software development, and systems integration experience. At Caris Life Sciences, he currently serves as a Salesforce Business Analyst and Administrator, where he leads automation, healthcare data integration, and clinical research optimizations. His work has directly impacted clinical decision-making by aligning technology with operational and regulatory needs. At Amazon, he developed scalable microservices, optimized APIs, and applied AI insights to enhance customer experience and personalization. Prior to that, at Infor in India, Milind supported legacy modernization and contributed to internal research on sentiment analysis and recommendation systems. Across these roles, he demonstrated an ability to innovate at scale while contributing to internal research pipelines and tool development. His hands-on experience across cloud platforms, AI tools, and enterprise software showcases a rare ability to move seamlessly between engineering execution and applied research.

Research Interest

Milind Cherukuri’s research interests lie at the intersection of artificial intelligence, machine learning, sentiment analysis, and safe AI deployment. He is passionate about building explainable, reliable, and application-driven AI systems that serve real-world domains such as healthcare, e-commerce, and cloud ecosystems. His work focuses on areas like multi-dimensional emotion representation, AI safety frameworks for large language models, and optimization techniques for prompt engineering. Milind is particularly interested in how AI can be made more context-aware, ethically responsible, and efficient when integrated into critical infrastructure. His research explores both the theoretical underpinnings of AI algorithms and their translation into user-centric applications. He uses tools such as TensorFlow, scikit-learn, Databricks, and Keras for prototyping and experimentation. Milind’s commitment to conducting reproducible and impactful research is evident through his multiple peer-reviewed publications and active participation in academic peer review and conference presentations.

Award and Honor

Milind Cherukuri has received several accolades that underscore his excellence in both research and professional performance. In 2025, he was elevated to the grade of Senior Member of IEEE, recognizing his significant contributions to engineering and AI research at a relatively early stage in his career. He has authored five peer-reviewed publications across reputable venues and conferences, including IEEE AI Summit and EEET 2024. His work has been cited in discussions on AI safety and ethics, especially regarding GPT-5 development strategies. Within industry roles, Milind earned recognition for developing fault-tolerant systems at Amazon and for improving automation workflows at Caris Life Sciences, boosting operational efficiency by over 30%. He has also contributed as a peer reviewer for research journals, enhancing his engagement with the broader scientific community. These honors reflect a balanced profile of innovation, leadership, and commitment to advancing technology responsibly and effectively.

Conclusion

Milind Cherukuri embodies the qualities of a forward-thinking, multidisciplinary researcher who bridges the worlds of academia and industry with exceptional skill. His educational foundation, professional achievements, and focused research trajectory demonstrate a rare combination of depth and adaptability. From developing scalable software at Amazon to integrating AI solutions in clinical workflows at Caris Life Sciences, he has consistently shown the ability to convert research insights into real-world impact. Milind’s publications, IEEE recognition, and conference engagements highlight his dedication to advancing AI in safe, ethical, and application-driven ways. His involvement in peer review and technical documentation further signals his readiness to contribute to and shape the global research landscape. With a passion for innovation, a track record of scholarly contributions, and strong industry credibility, Milind stands out as a compelling candidate for honors such as the Young Researcher Award, and is poised for continued impact in the field of computer science and artificial intelligence.

Publications Top Notes

  • Title: Comparing Image Segmentation Algorithms
    Author: M. Cherukuri
    Year: 2024
    Citations: 3

  • Title: Cost, Complexity, and Efficacy of Prompt Engineering Techniques for Large Language Models
    Author: M. Cherukuri
    Year: 2025
    Citations: 1

  • Title: WebChecker: A Versatile EVL Plugin for Validating HTML Pages with Bootstrap Frameworks
    Author: M. Cherukuri
    Year: 2025
    Citations: 1

  • Title: Advancing AI Safely: Frameworks and Strategies for the Development of GPT-5 and Beyond
    Author: M. Cherukuri
    Year: 2025
    Citations: 1

  • Title: Exploring Multi-Dimensional Sentiment Analysis: A Study on Emotion Representation Structures and Prediction Models
    Author: M. Cherukuri
    Year: 2024

Bo Yang | Computer Science | Best Researcher Award

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Prof Dr. Bo Yang | Computer Science | Best Researcher Award

Full Professor, Northwestern Polytechnical University, China

📡 Dr. Bo Yang is a Professor at the School of Computer Science, Northwestern Polytechnical University (NPU), China. He is an expert in AI-empowered wireless networks, mobile edge/cloud computing, and big data analysis, with significant experience in academia and industry. His work has contributed to advancements in next-generation wireless systems and computational intelligent surfaces.

Publication Profile

Scopus

Strengths for the Award

  1. Extensive Research in AI-Empowered Networks: Bo Yang’s research focuses on cutting-edge technologies like AI-empowered wireless networks, mobile edge/cloud computing, and intelligent surface designs. These are relevant and impactful fields in today’s technological landscape.
  2. International Experience and Collaborations: Bo Yang has worked across multiple prestigious institutions globally, including Singapore University of Technology and Design (SUTD), Prairie View A&M University (USA), and Northwestern Polytechnical University (China). This international exposure has likely enriched his research perspective.
  3. High-Impact Publications: Bo Yang has authored and co-authored numerous influential publications in high-impact journals, such as IEEE Transactions on Wireless Communications and IEEE Transactions on Industrial Informatics, showcasing his research output and influence in the academic community.
  4. Notable Research Funding: Bo Yang has been involved in significant research projects with substantial funding, such as the $6 million USD project for the U.S. Office of Defense, which demonstrates his ability to secure large grants and work on high-stakes, impactful research.
  5. Awards and Nominations: He has been nominated for prestigious awards like the Excellence in Scholarly Research Award at Prairie View A&M University, highlighting his recognition as a strong researcher.

Areas for Improvement

  1. Broader Industry Impact: While Bo Yang’s research contributions are impressive academically, there is limited evidence of direct industry partnerships or commercialization of his research. Engaging more with industry and applying his innovations in commercial products could further bolster his case for the award.
  2. Leadership in Research Initiatives: While Bo Yang has been part of multiple large-scale research projects, more evidence of him leading major projects or research teams would enhance his leadership profile and strengthen his award candidacy.
  3. Public Engagement and Knowledge Dissemination: Expanding his efforts in science communication, such as more public-facing talks or involvement in workshops and seminars, could improve his visibility and influence beyond the academic community.

Education

🎓 Dr. Yang earned his Ph.D. in Information and Communication Engineering from NPU (2010-2017), where his thesis focused on multi-channel medium access for next-generation WLAN. He also holds an M.Sc. in Communication and Information Systems (2007-2010) with a thesis on video coding and wireless transmission, and a B.Sc. in Communication Engineering (2003-2007), during which he interned at Datang Telecom.

Experience

💼 Dr. Yang is currently a Professor at NPU, Xi’an, China, where he leads cutting-edge research on AI-empowered wireless networks. Previously, he was a Research Fellow at the Singapore University of Technology and Design (SUTD) and a Postdoctoral Fellow at Prairie View A&M University (PVAMU), USA. His research projects have been funded by prestigious organizations, including A*STAR in Singapore and the U.S. Office of the Under Secretary of Defense.

Research Focus

🔬 Dr. Yang’s research focuses on AI-powered wireless networks, mobile edge/cloud computing, computational intelligent surfaces, and big data security. His innovative work addresses challenges in next-generation communication systems, with a particular emphasis on reconfigurable intelligent surfaces and federated spectrum learning for wireless edge networks.

Awards and Honors

🏆 Dr. Yang has been honored with several prestigious awards, including the NNSF for Excellent Young Scientists Fund Program (Overseas) in 2022 and a nomination for the Excellence in Scholarly Research Award at PVAMU in 2020. His groundbreaking research projects have been funded by leading organizations worldwide.

Publication Top Notes

📝 Dr. Yang has authored numerous influential papers in high-impact journals. His recent works include:

“DiffSG: A Generative Solver for Network Optimization with Diffusion Model” (2024) – arXiv:2408.06701

“Reconfigurable Intelligent Computational Surfaces for MEC-Assisted Autonomous Driving Networks: Design Optimization and Analysis” (2024) – arXiv:2407.00933

“Filtering Reconfigurable Intelligent Computational Surface for RF Spectrum Purification” (2024) – arXiv:2406.18055

“AI-Empowered Multiple Access for 6G: A Survey of Spectrum Sensing, Protocol Designs, and Optimizations” (2024) – Proceedings of the IEEE, Cited by 39

“A Multi-View Interactive Approach for Multimodal Sarcasm Detection in Social Internet of Things” (2024) – Applied Sciences, Cited by 18

Conclusion

Bo Yang is a highly qualified candidate for the Best Researcher Award due to his significant contributions to AI-empowered networks, his prolific publication record, and involvement in international research collaborations. To enhance his candidacy further, he could focus on increasing industry engagement, leading more research initiatives, and enhancing public engagement with his work. His strengths in cutting-edge technology, global experience, and scholarly impact make him a strong contender for the award.

Alex Mirugwe | Computer Science | Young Scientist Award

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Mr. Alex Mirugwe | Computer Science | Young Scientist Award

Data Scientist at Makerere University, School of Public Health, Uganda

Alex Mirugwe is a highly skilled Data Scientist with over 4 years of experience, specializing in applying machine learning and AI to healthcare challenges, particularly in HIV, cancer, and tuberculosis diagnostics. He has a proven track record of developing data-driven solutions that improve patient outcomes in resource-constrained settings. His research has been published in several peer-reviewed journals, and he is proficient in a wide range of data science tools and methodologies. Alex also contributes to academia as an Assistant Lecturer and is involved in curriculum development and student mentoring in computer science.

Profile:

Strengths for the Award:

  1. Specialized Expertise in Healthcare Data Science: Alex Mirugwe has developed machine learning models and AI tools to solve critical health challenges, such as HIV patient care and cervical cancer detection. His work is not only technically sound but has made tangible impacts on healthcare delivery in resource-constrained environments.
  2. Research Contributions and Publications: Alex has authored multiple peer-reviewed journal articles on healthcare applications of AI, including sentiment analysis of public health data, tuberculosis detection, and cancer screening. These publications demonstrate his commitment to advancing the application of AI in public health and data science.
  3. Experience in Machine Learning and AI: His technical expertise spans a range of relevant tools and techniques, including deep learning, transfer learning, and predictive modeling, which are crucial for impactful healthcare interventions. His experience in both teaching and research also ensures that his knowledge is applied and shared within the academic community.
  4. Proven Success in Real-World Applications: Alex’s work on reducing HIV patient data duplication, predicting HIV patient outcomes, and improving cervical cancer screening speaks to his practical problem-solving skills in high-stakes environments. The use of AI to improve healthcare decision-making is well-aligned with global trends toward technology-driven health solutions.
  5. Cross-Disciplinary and Global Approach: Alex’s education, spanning institutions in Uganda and South Africa, and his research interests in global health issues, reflect his broad outlook. His involvement with international collaborators highlights his ability to bridge different disciplines and apply his knowledge across borders.

Areas for Improvement:

  1. More Diverse Research Focus: While Alex has concentrated on significant healthcare issues, expanding his research beyond HIV, cancer, and tuberculosis may enhance his portfolio. Including more work in diverse fields, such as environmental health or genomics, would add breadth to his achievements.
  2. Leadership in Research Projects: Alex has demonstrated technical prowess and teaching capabilities, but more emphasis on leadership roles in large-scale research projects or interdisciplinary initiatives could elevate his profile. Leading a significant multi-institutional study or directing larger research teams may help solidify his standing.
  3. Policy and Implementation Impact: Though Alex has made practical contributions, more evidence of his work leading to large-scale policy changes or national-level healthcare implementations could further strengthen his application. This would demonstrate how his AI models or algorithms scale to influence public health strategies at a systemic level.
  4. International Research Collaborations: Although his work is impactful within Uganda, expanding collaborations with more international research institutes or global health organizations could further enhance his visibility and contribution to global health initiatives.

 

Education:

Alex Mirugwe holds an MSc in Data Science from the University of Cape Town, South Africa, completed in 2021, where he conducted research on automated bird detection using machine learning. His academic performance was strong, with a GPA of 74.52%. Prior to this, he earned a BSc in Computer Engineering from Makerere University, Uganda, in 2019, graduating with a CGPA of 4.18/5.0. His undergraduate dissertation focused on developing a low-cost wireless TV audio transceiver, reflecting his early interest in applying engineering principles to real-world problems. His educational background combines technical proficiency in computer science with a strong emphasis on data science and machine learning applications.

Experience:

Alex Mirugwe is a highly skilled data scientist with over four years of experience applying machine learning and AI to healthcare challenges, particularly in diagnosing HIV, cancer, and tuberculosis. He has successfully developed predictive models to improve patient care and outcomes in resource-limited settings, such as creating algorithms for cervical cancer screening and reducing HIV patient data duplication. His work spans both practical implementation and academic research, with multiple publications on AI-driven health interventions. In addition to his research, Alex is an experienced educator, teaching data science and machine learning courses at the university level.

Research Focus:

Alex Mirugwe’s research focuses on leveraging data science and machine learning to address critical healthcare challenges, particularly in resource-constrained settings. His work encompasses developing predictive models for patient care in HIV treatment, enhancing cervical cancer screening accuracy through AI algorithms, and analyzing public sentiment during health crises, such as the Ebola outbreak. Additionally, he explores various applications of AI in public health, including improving tuberculosis detection and reducing data duplication in electronic medical records. Overall, his research aims to harness advanced data analytics to improve patient outcomes and inform public health strategies, making significant contributions to the field of healthcare data science.

Publications Top Notes:

  • Automating Bird Detection Based on Webcam Captured Images Using Deep Learning
    • Authors: A. Mirugwe, J. Nyirenda, E. Dufourq
    • Year: 2022
    • Citations: Not specified in the provided information.
  • Restaurant Tipping Linear Regression Model
    • Author: A. Mirugwe
    • Year: 2020
    • Citations: Not specified in the provided information.
    • Link: SSRNPaper
  • Sentiment Analysis of Social Media Data on Ebola Outbreak Using Deep Learning Classifiers
    • Authors: A. Mirugwe, C. Ashaba, A. Namale, E. Akello, E. Bichetero, E. Kansiime, J. Nyirenda
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Journal: Life, 14(6), 708.
  • Adoption of Artificial Intelligence in the Ugandan Health Sector: A Review of Literature
    • Author: A. Mirugwe
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Link: Available at SSRN 4735326.

Conclusion:

Alex Mirugwe presents an impressive and well-rounded portfolio, with extensive experience in applying machine learning and AI to tackle critical healthcare challenges. His achievements, particularly in HIV care and cancer screening, demonstrate his ability to leverage data science for real-world health outcomes. While he has a strong research and technical background, focusing on leadership, broadening his research scope, and contributing to systemic policy changes could bolster his case further. He is a strong candidate for the Best Researcher Award, especially within the domain of AI-driven healthcare solutions in resource-constrained settings.