Dr. Mohsin Masood – Data Scientist – Best Researcher Award 

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Dr. Mohsin Masood - Data Scientist - Best Researcher Award 

Imperial College London - United Kingdom

Author Profile 

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Mohsin Masood began his academic journey with a strong foundation in computer science, securing a merit-based msc funding grant from the university of east london (2011–2012). his early academic achievements laid the groundwork for advanced training in health data science, culminating in a phd in statistical modelling from the university of strathclyde, funded by a competitive grant (2014–2017). his scholarly curiosity extended internationally through the erasmus exchange research grant at vsb-technical university of ostrava (2015–2018), where he deepened his expertise in predictive modelling and bioinformatics. during this phase, his interest in power electronics and algorithmic optimization in medical diagnostics emerged as an interdisciplinary focus.

💼 Professional endeavors

With over a decade of experience, mohsin has held impactful roles across academia and research institutions. as an assistant professor in computer science at abasyn university (2018–2022), he designed and taught advanced courses in ai, ml, and data science, incorporating real-world applications in epidemiology and digital health. later, as a senior research fellow at the university of leeds (2022–2023), he led data engineering for a large-scale 2.9 million patient cohort, employing advanced machine learning and nlp tools to analyze multimorbidity and Data Scientist cardiovascular risks. currently, he serves as a research associate at imperial college london (2023–present), where he leads predictive modelling projects on population health, integrating datasets like uk biobank, sail databank, and triphic. he also fosters collaborations with institutions such as sheffield university and a* university of singapore.

🧠 Contributions and research focus

Mohsin’s core research focus lies in multimorbidity, disease progression modelling, and epidemiological risk assessment, particularly within cardiovascular and pulmonary health Data Scientist domains. he applies deep learning, survival analysis, and multistate modelling to interpret complex patient trajectories and disease clustering. his work with electronic health records (ehrs) like hospital episode statistics (hes) reflects a commitment to improving precision medicine. integrating technologies from power electronics into patient monitoring systems has been a unique dimension of his research, promoting real-time diagnostics and health alerts. he has also contributed to educational leadership by mentoring bsc and msc students in ai-based health science projects.

🌍 Impact and influence

Mohsin’s influence extends beyond academia through his involvement in cross-institutional research, digital outreach, and public health strategy. at imperial’s national heart and lung institute (nhli), he manages social media communications to boost public engagement with medical data science. his high-impact publications have contributed to the growing intersection of Data Scientist computational modelling and health outcomes, often cited in cardiovascular and cancer research communities. he is recognized for bridging the gap between statistical modelling and power electronics, showing how smart analytics can optimize hardware for healthcare delivery.

📚 Academic cites

His academic influence is reflected in high citation counts across journals focusing on biostatistics, machine learning in medicine, and epidemiology. notable contributions include projects funded by imperial nhli’s pilot project award (2023–2024) and royan pharmaceutical’s breast cancer research grant (2020–2021). his statistical toolkits and predictive algorithms are widely referenced in studies involving survival analysis, deep learning applications in ehrs, and risk prediction modelling.

🧬 Legacy and future contributions

Mohsin’s legacy lies in fostering a data-driven healthcare ecosystem where interdisciplinary tools empower clinicians and researchers alike. he aims to develop scalable, explainable ai systems for public health, enabling real-time decision-making in hospitals and remote settings. leveraging power electronics, he envisions the integration of wearable technologies with ai for early disease detection and patient monitoring. his commitment to mentoring the next generation of health data scientists ensures a lasting academic and societal impact.

Notable Publications 

  • Title: Emotion classification and crowd source sensing; a lexicon based approach
    Authors: R. Kamal, M.A. Shah, C. Maple, M. Masood, A. Wahid, A. Mehmood
    Journal: IEEE Access

  • Title: An improved particle swarm algorithm for multi-objectives based optimization in MPLS/GMPLS networks
    Authors: M. Masood, M.M. Fouad, R. Kamal, I. Glesk, I.U. Khan
    Journal: IEEE Access

  • Title: Energy efficient software defined networking algorithm for wireless sensor networks
    Authors: M. Masood, M.M. Fouad, S. Seyedzadeh, I. Glesk
    Journal: Transportation Research Procedia

  • Title: Proposing bat inspired heuristic algorithm for the optimization of GMPLS networks
    Authors: M. Masood, M.M. Fouad, I. Glesk
    Journal: 2017 25th Telecommunication Forum (TELFOR)

  • Title: Analysis of artificial intelligence-based metaheuristic algorithm for MPLS network optimization
    Authors: M. Masood, M.M. Fouad, I. Glesk
    Journal: 2018 20th International Conference on Transparent Optical Networks (ICTON)

Prof . Balasubbareddy Mallala – Machine Learning – Best Researcher Award 

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Prof . Balasubbareddy Mallala - Machine Learning - Best Researcher Award 

Chaitanya Bharathi Institute of Technology, Hyderabad - India 

Author Profile

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Dr. M. Balasubbareddy embarked on his academic journey with a strong foundation in electrical and electronics engineering, earning a b.e. degree with distinction. further advancing his expertise, he pursued an m.tech. in power systems, achieving first-class honors. his relentless pursuit of knowledge culminated in a ph.d. in electrical and electronics engineering, where he delved into cutting-edge research, laying the groundwork for a prolific career. his academic curiosity extended to post-doctoral studies, further cementing his reputation as a dedicated scholar.

💼 Professional endeavors

As a professor at chaitanya bharathi institute of technology (cbit), dr. balasubbareddy has dedicated over two decades to teaching and mentoring. since joining cbit in 2017, he has taken on diverse roles, including membership in the college academic committee, anti-ragging committee, and intellectual property rights cell. his leadership as a convener of the ethics committee and departmental research committee has significantly shaped institutional policies and academic growth. with a career spanning 22 years in teaching and 16 years in research, he remains a cornerstone of excellence in academia.

🔬 Contributions and research focus

Dr. Balasubbareddy's research focuses on power systems, power electronics, and soft computing techniques. his innovative work bridges theoretical advancements and practical applications, contributing to sustainable and efficient energy solutions. as an active researcher, he has guided numerous projects and students, fostering a culture of inquiry and innovation. his Machine Learning participation in various institutional committees ensures the integration of research-driven strategies into curriculum development and academic practices.

🏅 Accolades and recognition

Dr. Balasubbareddy has received numerous prestigious awards that underscore his excellence in teaching and research. notable accolades include the best researcher of the year award from Machine Learning jnt university, the national award for teaching excellence, and the dr. radhakrishna award for engineering college teachers. his achievements also include international recognition, such as the global eminent scientist award and best open source learner awards. these honors reflect his dedication to academic and research excellence over the years.

🌟 Impact and influence

Through his extensive teaching and mentorship, dr. balasubbareddy has influenced countless students and colleagues, fostering a legacy of innovation and excellence. his involvement in nba Machine Learning accreditation, institute innovation, and patenting committees has significantly enhanced the academic framework of cbit. his dedication to fostering interdisciplinary collaboration and industry partnerships exemplifies his commitment to advancing the field of electrical and electronics engineering.

🏛️ Legacy and future contributions

Dr. Balasubbareddy's enduring legacy is built on his passion for education, research, and innovation. his ongoing efforts to integrate cutting-edge research with practical applications continue to inspire the next generation of engineers and researchers. as a dedicated mentor, academic leader, and researcher, he envisions a future where his contributions to power systems and soft computing techniques pave the way for sustainable technological advancements.

Notable Publications 

  • Title: Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm
    Authors: M. Balasubbareddy, S. Sivanagaraju, C. V. Suresh
    Journal: Engineering Science and Technology, an International Journal
  • Title: Multi-objective optimization in the presence of ramp-rate limits using non-dominated sorting hybrid fruit fly algorithm
    Authors: M. Balasubbareddy
    Journal: Ain Shams Engineering Journal
  • Title: Salp swarm algorithm for solving optimal power flow problem with thyristor-controlled series capacitor
    Authors: B. Mallala, D. Dwivedi
    Journal: Journal of Electronic Science and Technology
  • Title: Generation and utilization of electrical energy
    Authors: S. Sivanagaraju, M. B. Reddy, D. Srilatha
    Journal: Pearson Education India
  • Title: A non-dominated sorting hybrid cuckoo search algorithm for multi-objective optimization in the presence of FACTS devices
    Authors: M. Balasubbareddy, S. Sivanagaraju, C. Venkata Suresh
    Journal: Russian Electrical Engineering

Dr. Yosr Ghozzi – Deep learning – Excellence in Research

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Dr. Yosr Ghozzi - Deep learning - Excellence in Research

University of Sfax - Tunisia

AUTHOR PROFILE

SCOPUS

ORCID

EARLY ACADEMIC PURSUITS 🎓

Yosr Ghozzi embarked on her academic journey with a strong focus on technological innovation and medical applications. She earned her Ph.D. from the National Engineering School of Sfax (ENIS) in 2022, which marked the beginning of her career as a teacher-researcher. Her academic background is rooted in artificial intelligence, deep learning, and medical imaging, laying the foundation for her future contributions to the field.

PROFESSIONAL ENDEAVORS 🏥

Since 2022, Yosr has been a dedicated teacher and researcher at ISIMS/University of Sfax in Tunisia. Her work is characterized by a strong focus on artificial intelligence and its applications in medical diagnostics. Her role as a researcher has allowed her to contribute significantly to both academic and industrial projects, with a notable project being the KAFSS, which involves molecular kits and digital applications for facial prediction and dysmorphia.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Yosr's research is at the intersection of artificial intelligence and medical imaging. She has made significant strides in the use of deep learning Deep learning combined with fuzzy logic to address the challenges of content-based image retrieval (CBIR) systems. Her work in this area is particularly relevant for computer-aided diagnosis, where CBIR systems can aid in detecting abnormalities and classifying medical images based on their content and medical context.

ACCREDITATIONS AND RECOGNITION 🏆

Yosr's contributions to research have not gone unnoticed. In 2022, she was awarded the prestigious title of Best Innovative Researcher at TICAD 8. Her research has also been published in two journals indexed by SCI and Scopus, and she has been involved in the editorial process of six Deep learning conferences, further establishing her as a recognized figure in her field.

IMPACT AND INFLUENCE 🌍

Yosr's research has a significant impact on the medical and technological fields, particularly in the development of advanced diagnostic tools. Her collaboration with international researchers from the University of Essex and the University of Johannesburg highlights her global influence. Her Deep learning work in AI and deep learning contributes to improving the accuracy and efficiency of medical diagnostics, potentially saving lives through early detection and intervention.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Yosr Ghozzi is set to leave a lasting legacy in the fields of artificial intelligence and medical imaging. Her innovative approaches to using deep learning for medical applications position her as a pioneer in her field. As she continues her research, Yosr's contributions will likely inspire future advancements in AI-driven healthcare solutions, ensuring her work's lasting impact on both academia and the medical community.

NOTABLE PUBLICATIONS

Interval Type-2 Beta Fuzzy Near Sets Approach to Content-Based Image Retrieval 2022(13)

Competencies based curricula (Electro-Mechanical Department Case Study) 2019(1)

A beta-fuzzy-near-sets approach to research for visually similar content images 2017(3)

A novel method for resemblance images using near fuzzy set 2016(2)

Modelling and numerical simulation of thick sheet double slitting process using continuum 2014(7)