Lakshmi Devi P | Generative AI and LLM | AI Breakthrough Award

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Mrs. Lakshmi Devi P | Generative AI and LLM | AI Breakthrough Award

Senior Associate – Data Scientist at JP Morgan& Chase, India

Lakshmi Devi P is a seasoned data science professional currently serving as a Senior Associate – Data Scientist at JPMorgan Chase, with additional academic contributions as an Adjunct Faculty member at the Manipal Academy of Higher Education (MAHE). With more than a decade of experience in artificial intelligence, machine learning, and data-driven innovation, she brings an expert lens to the domain of Generative AI and NLP. A published author, active mentor, and patent contributor, her work is grounded in ethical, scalable applications of AI that span enterprise systems and educational initiatives. Her leadership on GenAI solutions exemplifies innovation that drives measurable impact across sectors.

Profile

ORCID

Education

Lakshmi is currently pursuing her Ph.D. in Artificial Intelligence, where her research focuses on designing scalable and ethical AI systems. This doctoral journey builds upon her robust academic and professional background, including foundational degrees in computer science and information technology. Her academic rigor complements her industry-focused innovations, bridging the gap between theoretical advancements and real-world applications. As an Adjunct Faculty member at MAHE, she has also contributed to curriculum development and has trained over 900 learners in a single session, reinforcing her commitment to AI education and knowledge dissemination.

Experience

Over the course of her career, Lakshmi Devi P has built a dynamic portfolio combining technical expertise, leadership, and community engagement. At JPMorgan Chase, she leads multiple enterprise-grade AI initiatives such as Zoom Transcribe GenAI, real-time anomaly detection systems, and semantic search engines. Her prior engagements with Capgemini, RetailOn, and Honeywell involved diverse projects including sentiment analysis, ROI forecasting, and OCR-driven automation. Beyond her corporate role, her teaching position at MAHE and collaborations with academic bodies like CIT and SSIT have enabled her to mentor aspiring data scientists and contribute meaningfully to AI literacy.

Research Interest

Lakshmi’s primary research interests lie at the intersection of Generative AI, Natural Language Processing, and ethical AI frameworks. She is particularly focused on the integration of Large Language Models (LLMs) into software engineering and system architecture. Her patented method for using LLMs to generate updated software architectures is a hallmark of her contribution to AI-driven automation. Additional interests include real-time anomaly detection, AI infrastructure design, vector embeddings, and retrieval-augmented generation systems. Her emphasis on ethical and inclusive AI underlines her belief that technological advancement must align with social responsibility and fairness.

Award

Lakshmi has been nominated for the AI Breakthrough Award in recognition of her innovative work in deploying GenAI solutions within the financial sector, publishing educational content, and mentoring underrepresented groups in AI. Her achievements exemplify groundbreaking contributions across research, enterprise application, and community upliftment. Her involvement in the Force for Good initiative reflects her dedication to leveraging AI for meaningful societal impact.

Publication

Lakshmi Devi P has authored a book titled “Transformers and Beyond: Building the Next Generation of Generative AI Systems” (ISBN: 979-8281458283), offering deep insights into foundation models and multimodal AI. She has also published the following journal articles:

  1. Real Valued Outputs of Cab Bookings using Regression and Ensemble Techniques Comparison Analysis, IJ for Research & Development in Technology, Vol. 13(2), Feb 2020, IF: 6.88.

  2. IOT Based Illegal Trees Cutting Prevention and Monitoring with Web App Using Raspberry Pi, IJ of Innovative Research in Science, Engineering and Technology, Vol. 8(7), Jul 2019, IF: 7.089.

  3. IOT based Waste Management System for Smart City, IAETSD Journal for Advanced Research in Applied Sciences, Vol. 4(7), Dec 2017, IF: 5.2.

  4. Helmet using GSM and GPS Technology for Accident Detection and Reporting System, IJRITCC, Vol. 4(5), May 2016, IF: 5.837.

  5. Real Time Tele Health Monitoring System, IJRITCC, Vol. 4(3), Mar 2016, IF: 5.837.

  6. Matlab Code For Identification Of Graphics Objects In Aircraft Displays, IJRITCC, Vol. 4(3), Mar 2016, IF: 5.837.

  7. SMS based Home Automation using CAN Protocol, IJRITCC, Vol. 4(3), Mar 2016, IF: 5.837.

Each of these publications demonstrates Lakshmi’s commitment to blending practical solutions with academic rigor, often cited for their interdisciplinary applications in IoT, automation, and AI.

Conclusion

Lakshmi Devi P represents the archetype of a modern AI leader—technically adept, ethically grounded, and socially conscious. Her body of work spans patented innovations, impactful AI deployments in high-stakes industries, academic contributions, and grassroots mentorship. By aligning enterprise performance with societal benefits, she embodies the transformative promise of AI. Whether through cutting-edge research, large-scale training, or community initiatives, Lakshmi continues to push boundaries, making her a deserving candidate for the AI Breakthrough Award and a role model in the data science ecosystem.

Fatih Kalemkuş | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Fatih Kalemkuş | Artificial Intelligence | Best Researcher Award

Assistant Professor at Kafkas University, Turkey

Dr. Fatih Kalemkuş is an Assistant Professor at Kafkas University, where he specializes in Electronic Commerce and Technology Management. With a rich academic and professional background, Dr. Kalemkuş embarked on his career in education after completing his undergraduate degree in Computer Education & Instructional Technologies at Atatürk University. He has taught various subjects related to information technology, first as an Informatics Technologies Teacher at the Turkish Ministry of National Education and later as a lecturer at Kafkas University’s Distance Education Application and Research Center. His journey culminated in earning a doctoral degree from Fırat University in Computer Education & Instructional Technologies, where he was honored with the “Most Successful Doctoral Thesis” award in 2024.

Profile

Orcid

Education

Dr. Kalemkuş’s educational journey began at Erzincan Fatih Industrial Vocational High School, where he pursued studies in the Computer Department. He continued to develop his academic career by earning his bachelor’s degree in 2006 from Atatürk University in the field of Computer Education & Instructional Technologies. He then completed a Master’s degree in Internet and Informatics Technologies Management from Afyon Kocatepe University between 2014 and 2016. His dedication to advancing his knowledge in the field led him to pursue a Ph.D. at Fırat University, graduating in 2023 with a focus on Computer Education & Instructional Technologies. His research has been instrumental in advancing educational practices in the digital age, with a specific focus on artificial intelligence and emerging technologies.

Experience

Dr. Kalemkuş has had diverse professional experiences. From 2007 to 2021, he served as an Informatics Technologies Teacher under the Turkish Ministry of National Education, shaping the next generation’s skills in information technology. In 2021, he joined Kafkas University as a lecturer at the Distance Education Application and Research Center, where he taught courses related to digital learning tools. His commitment to academic excellence and innovation in education led to his promotion to Assistant Professor in 2024 at Kafkas University’s Electronic Commerce and Technology Management Department, where he continues to make impactful contributions to research and education.

Research Interests

Dr. Kalemkuş’s research focuses on key areas of educational technology and digital transformation. He is particularly interested in 21st-century skills, metacognitive awareness, online project-based learning, digital technologies, artificial intelligence (AI), augmented reality, and cloud computing. He also explores the intersection of education and emerging technologies, such as natural language processing (NLP) and the integration of AI in educational contexts. His work aims to improve learning outcomes and foster innovation in teaching methodologies. His ongoing research projects delve into the development of AI-driven educational materials and interactive learning environments that enhance students’ academic engagement.

Awards

Dr. Kalemkuş has received recognition for his outstanding academic contributions. In 2024, he was honored with the prestigious “Most Successful Doctoral Thesis” award from Fırat University for his exceptional research and academic achievements. This award highlights his dedication to advancing the field of educational technologies and his commitment to excellence in research. His work, particularly on the use of AI in education, has positioned him as a leading researcher in his field.

Publications

Dr. Kalemkuş has authored several influential publications in well-regarded journals and books. His research has been featured in leading SSCI and ESCI journals, including the European Journal of Education, Interactive Learning Environments, Science & Education, and Journal of Research in Special Educational Needs. His recent publications include:

Kalemkuş, F., & Kalemkuş, J. (2025). “Primary School Students’ Perceptions of Artificial Intelligence: Metaphor and Drawing Analysis”, European Journal of Education, 60(1), 1-23.

Kalemkuş, F., & Bulut-Özek, M. (2024). “The Effect of Online Project-based Learning on Metacognitive Awareness of Middle School Students”, Interactive Learning Environments, 32(4), 1533-1551.

Kalemkuş, F., & Kalemkuş, J. (2024). “The Effect of Designing Scientific Experiments with Visual Programming on Learning Outcomes”, Science & Education, 1-23.

Kalemkuş, F., & Bulut-Özek, M. (2023). “Effect of the Use of Augmented Reality Applications on Academic Achievement in Science Education: Meta Analysis”, Interactive Learning Environments, 31(9), 6017-6034.

Kalemkuş, F. (2024). “Trends in Instructional Technologies Used in Education for People with Special Needs Due to Intellectual Disabilities and Autism”, Journal of Research in Special Educational Needs, 1-25.

Kalemkuş, F., & Çelik, L. (2023). “Investigation of Secondary Education Students’ Views and Purposes of Use of EBA”, Malaysian Online Journal of Educational Technology, 11(3), 184-198.

Kalemkuş, F., & Bulut-Özek, M. (2021). “Research Trends in 21st Century Skills: 2000-2020”, MANAS Sosyal Araştırmalar Dergisi, 10(2), 878-900.

Conclusion

Dr. Fatih Kalemkuş’s career has been marked by a profound commitment to advancing educational technology and promoting the use of emerging technologies in learning environments. With numerous publications in prestigious journals and books, he has made a significant impact on the fields of AI, digital learning, and 21st-century skills development. His work continues to shape the educational landscape, particularly in the integration of innovative digital tools to enhance teaching and learning outcomes. Dr. Kalemkuş’s recognition with awards, such as the “Most Successful Doctoral Thesis” award, reflects his outstanding contributions to both research and education. His interdisciplinary approach ensures that his work will remain at the forefront of educational innovations for years to come.

Cheng-Mao Zhou | Artificial Intelligence | Best Researcher Award

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Dr. Cheng-Mao Zhou | Artificial Intelligence | Best Researcher Award

Researcher | Central People’s Hospital of Zhanjiang | China

Dr. Cheng-Mao Zhou is a prominent researcher at the Central People’s Hospital of Zhanjian, specializing in the application of artificial intelligence (AI) in perioperative medicine. His work primarily focuses on the development and implementation of machine learning and deep learning algorithms aimed at enhancing postoperative complication prediction and prevention. Dr. Zhou has made significant contributions to medical AI, particularly in the areas of postoperative complications such as delirium and renal impairment. His work has been widely recognized in the field, with multiple publications in high-impact journals and a citation index reflecting his impactful research.

Profile

Scopus

Education

Dr. Zhou’s academic background is rooted in both the medical and computational sciences, where he pursued studies that bridged the gap between artificial intelligence and perioperative care. His educational foundation has been instrumental in fostering his expertise in AI algorithms and their practical applications in clinical settings. Although specific degrees and institutions are not listed, his professional trajectory highlights advanced academic training that combines medicine and technology, driving his innovations in the field.

Experience

Dr. Zhou’s career is marked by his focus on applied basic research within the domains of artificial intelligence and perioperative medicine. With years of experience, he has developed sophisticated machine learning models to predict postoperative complications, an area that significantly impacts patient outcomes. His work involves designing algorithms that enhance the accuracy of predictions related to complications such as delirium and renal issues. Dr. Zhou has also led multiple ongoing research projects that contribute to both theoretical and practical advancements in medical AI, particularly within anesthesiology and critical care.

Research Interests

Dr. Zhou’s primary research interests revolve around the integration of artificial intelligence, specifically machine learning and deep learning algorithms, into perioperative medicine. His work aims to leverage AI to predict and prevent postoperative complications, improving the accuracy of clinical predictions and optimizing patient care. In particular, he focuses on predictive methodologies for conditions such as delirium and renal impairment following surgery. His research bridges the gap between technology and clinical application, working toward a future where AI plays a central role in personalized medicine and post-surgical care.

Awards

Dr. Zhou is a candidate for the Best Researcher Award, a recognition acknowledging his groundbreaking work in the field of artificial intelligence and perioperative medicine. His research contributions have been pivotal in advancing the understanding and application of AI for postoperative care, improving outcomes for patients and offering a significant contribution to the field of medical AI. Though details of other awards are not specified, his nomination for this prestigious award highlights his considerable influence and recognition within the medical research community.

Publications

Dr. Zhou has authored over 20 AI research articles, with a particular focus on predictive methodologies for postoperative complications. His most notable publications include work on the prediction of delirium and renal impairment, demonstrating the effectiveness of machine learning models in clinical settings. Below is a selection of his key publications:

“A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm”

    • Authors: Zhou, C.-M., Xue, Q., Li, H., Yang, J.-J., Zhu, Y.
    • Year: 2024
    • Citations: 0

“Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery”

    • Authors: Zhou, C.-M., Li, H., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2024
    • Citations: 3

“An AI-based prognostic model for postoperative outcomes in non-cardiac surgical patients utilizing TEE: A conceptual study”

    • Authors: Zhu, Y., Liang, R., Zhou, C.-M.
    • Year: 2024
    • Citations: 0

“Predicting early postoperative PONV using multiple machine-learning- and deep-learning-algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2023
    • Citations: 6

“Predicting postoperative gastric cancer prognosis based on inflammatory factors and machine learning technology”

    • Authors: Zhou, C.-M., Wang, Y., Yang, J.-J., Zhu, Y.
    • Year: 2023
    • Citations: 10

“A long duration of intraoperative hypotension is associated with postoperative delirium occurrence following thoracic and orthopedic surgery in elderly”

    • Authors: Duan, W., Zhou, C.-M., Yang, J.-J., Ma, D.-Q., Yang, J.-J.
    • Year: 2023
    • Citations: 19

“Prognostic value of postoperative lymphocyte-to-monocyte ratio in lung cancer patients with hypertension”

    • Authors: Yuan, M., Wang, P., Meng, R., Zhou, C., Liu, G.
    • Year: 2023
    • Citations: 0

“Differentiation of Bone Metastasis in Elderly Patients With Lung Adenocarcinoma Using Multiple Machine Learning Algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Zhu, Y.
    • Year: 2023
    • Citations: 5

“Non-linear relationship of gamma-glutamyl transpeptidase to lymphocyte count ratio with the recurrence of hepatocellular carcinoma with staging I–II: a retrospective cohort study”

    • Authors: Li, Z., Liang, L., Duan, W., Zhou, C., Yang, J.-J.
    • Year: 2022
    • Citations: 2

“Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2022
    • Citations: 16

Conclusion:
Dr. Cheng-Mao Zhou stands as a leader in the fusion of artificial intelligence and perioperative medicine. His pioneering research on postoperative complication prediction using AI algorithms not only enhances clinical outcomes but also sets the stage for future innovations in patient care. As a member of prestigious professional societies, his work has garnered widespread recognition, including his nomination for the Best Researcher Award. Dr. Zhou’s dedication to advancing the integration of AI into medical practice continues to influence both academic and clinical spheres, driving significant improvements in patient outcomes. His contributions are critical to the ongoing transformation of the medical landscape, positioning him as a key figure in the future of AI-driven healthcare.