Laxmi Kantham Durgam | Deep Learning | Best Scholar Award

Mr. Laxmi Kantham Durgam | Deep Learning | Best Scholar Award

National Institute of Technology Warangal | India

Publication Profile

Google Scholar

🧑‍🎓 Education

Mr. Laxmi Kantham Durgam is currently pursuing his PhD in Electrical Engineering at National Institute of Technology Warangal, Telangana, India (2021–Present). His research focuses on Speech Recognition, Age and Gender Identification from Speech, and the application of Machine Learning and Deep Learning techniques. He is also a Visiting Researcher at the Technical University of Kosice, Slovakia, as part of the NSP SAIA Fellowship (2024). Mr. Durgam holds an M.Tech in Digital Systems and Computer Electronics from Jawaharlal Nehru Technological University, Hyderabad (2017–2020) and a B.Tech in Electronics and Communication Engineering from the same institution (2011–2015).

📚 Publications

Mr. Durgam has contributed to various publications in the fields of speech processing, deep learning, and edge computing. His notable works include papers on speaker age and gender classification, real-time age estimation from speech, and dress code detection using MobileNetV2 on NVIDIA Jetson Nano. He has been published in journals like Computing and Informatics and Journal of Signal Processing Systems, as well as conferences like ICIT-2023 in Kyoto, Japan.

🔬 Research Experience

Since 2021, Mr. Durgam has been a PhD Research Scholar at NIT Warangal, where his research includes projects on real-time age identification from speech using Edge devices like Jetson Nano and Arduino Nano BLE. He has also worked on real-time projects like vehicle logo classification using Edge Impulse and dress code detection using MobileNetV2. His work is focused on implementing Machine Learning and Deep Learning algorithms for practical, real-time applications.

🏆 Fellowships and Awards

Mr. Durgam was awarded the NSP SAIA Fellowship (2024), an international mobility program funded by the European Union, allowing him to collaborate with the KEMT, Faculty of Electrical Engineering and Informatics at the Technical University of Kosice, Slovakia. He also received the MHRD Fellowship for his PhD from the Government of India. He has passed the NITW PhD Entrance and the GATE exam (2016), and he received financial support as an undergraduate student from the Andhra Pradesh State Government.

📖 Academic Achievements

Mr. Durgam has significantly contributed to the academic environment through his role in conducting hands-on programming sessions in Machine Learning, Deep Learning, and AI applications. He has mentored students in Faculty Development Programs (FDPs), summer and winter internships, and workshops at various institutions. His workshops have reached institutions such as BRIT Vijayanagaram and VBIT Hyderabad, where he focused on advanced deep learning applications on Edge devices.

💻 Technical Skills

Mr. Durgam is highly skilled in programming with languages like Python, C, Embedded C, Matlab, and frameworks such as Keras, TensorFlow, and OpenCV. He has experience working with edge devices like Jetson Nano, Jetson Xavier, and Arduino Nano BLE 33 Sense. His expertise also extends to Machine Learning, Deep Learning, Computer Vision, and Digital Signal Processing.

🧑‍🏫 Teaching and Mentoring

Mr. Durgam has been an active Teaching Assistant and mentor at NIT Warangal, where he has assisted in courses like Artificial Intelligence, Machine Learning, and Digital Signal Processing. He has guided B.Tech students in lab sessions, and his expertise in AI/ML has also been shared through guest lectures and faculty development programs.

🚀 Key Projects

Some of Mr. Durgam’s key projects include age and gender estimation from speech using MFCC features, dress code detection with MobileNetV2 on Edge devices, and real-time object detection using deep learning algorithms. He has successfully developed these applications on devices like Jetson Nano and Arduino Nano BLE for real-time deployment.

🌍 Professional Engagement

Mr. Durgam is an IEEE Student Member and an active participant in IEEE Young Professionals. He has been involved in organizing and coordinating internships, workshops, and training programs related to AI/ML and Deep Learning at NIT Warangal and other institutes. He is passionate about bridging the gap between academia and real-world applications, particularly through Edge Computing and AI deployment.

📚 Top Notes Publications 

Real-Time Dress Code Detection using MobileNetV2 Transfer Learning on NVIDIA Jetson Nano
    • Authors: LK Durgam, RK Jatoth

    • Journal: Proceedings of the 2023 11th International Conference on Information

    • Year: 2023

Real-Time Classification of Vehicle Logos on Arduino Nano BLE using Edge Impulse
    • Authors: D Abhinay, SV Vighnesh, LK Durgam, RK Jatoth

    • Journal: 2023 4th International Conference on Signal Processing and Communication

    • Year: 2023

Age Estimation based on MFCC Speech Features and Machine Learning Algorithms
    • Authors: LK Durgam, RK Jatoth

    • Journal: IEEE International Symposium on Smart Electronic Systems (iSES)

    • Year: 2022

Age Estimation from Speech Using Tuned CNN Model on Edge Devices
    • Authors: LK Durgam, RK Jatoth

    • Journal: Journal of Signal Processing Systems

    • Year: 2024

Age and Gender Estimation from Speech using various Deep Learning and Dimensionality Reduction Techniques
    • Authors: MPJJ Laxmi Kantham Durgam*, Ravi Kumar Jatoth, Daniel Hladek, Stanislav Ondas

    • Journal: Acoustics and Speech Processing at Speech analysis synthesis, Institute of

    • Year: 2024

 

Ouya Fang | Ecological risk| Best Researcher Award

Dr. Ouya Fang | Ecological risk | Best Researcher Award

Dr. Ouya Fang at Institute of Botany, Chinese Academy of Sciences, China

  Profiles👨‍🎓

Early Academic Pursuits 🎓

Dr. Ouya Fang completed her Ph.D. in Physical Geography at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, in 2016. Her academic journey continued with postdoctoral research in Ecology at the same institute from 2016 to 2018, laying a strong foundation in environmental sciences.

Professional Endeavors 💼

Since 2023, Dr. Fang has served as an Associate Professor at the Institute of Botany, Chinese Academy of Sciences, after holding the position of Assistant Researcher from 2018 to 2023. She has also gained international experience as a Visiting Scholar at the Swiss Federal Institute for Forest, Snow, and Landscape Research (2019-2020) and contributes to the scientific community as an Associate Editor for Dendrochronologia and board member for several ecological journals.

Contributions and Research Focus 🔍

Dr. Fang has led significant research projects, including studies on tree ecological resilience and the Tamarix arbor phenomenon in Qinghai. Her work emphasizes forest ecology, dendrochronology, and climate change, advancing knowledge on tree resilience and ecological memory, particularly under climate stress.

Impact and Influence 🌍

With an H-index of 10 and 24 published research papers—19 as first or corresponding author—Dr. Fang’s work has influenced forest resilience assessments and the understanding of historical forest decline due to climate change. Her research findings are recognized for enhancing resilience indicators and developing strategies for tree survival in extreme conditions.

Academic Cites 📚

Dr. Fang’s research has appeared in prestigious journals, including Science, Nature Geoscience, and Global Change Biology, showcasing her impactful contributions to the field. Her editorial roles in notable journals reflect her standing in the academic community.

Technical Skills 🛠️

Dr. Fang possesses advanced technical skills in forest ecology research, dendrochronology, and climate change analysis. Her expertise enables her to conduct in-depth assessments of ecological resilience and historical growth patterns of forest trees.

Teaching Experience 👩‍🏫

As an Associate Professor, Dr. Fang engages in teaching and mentoring students in ecology and environmental sciences, fostering the next generation of researchers. Her academic background enhances her ability to convey complex concepts effectively.

Legacy and Future Contributions 🔮

Dr. Fang’s ongoing research, including a forthcoming book on forest tree health, underscores her commitment to understanding ecological systems and contributing to sustainability. Her work aims to shape future research directions in forest ecology and climate adaptation strategies.

In summary, Dr. Ouya Fang’s academic and professional journey is marked by significant contributions to forest ecology, demonstrating her dedication to advancing knowledge and fostering resilience in natural systems.

 

Top Noted Publications 📖

Tree-growth synchrony index, an effective indicator of historical climatic extremes
    • Authors: Hengfeng Jia, Jiacheng Zheng, Jing Yang, Lixin Lyu, Yuntao Dong, Ouya Fang
    • Journal: Ecological Processes
    • Year: 2024
Reducing continuous synchrony is an inherent property of tree growth in forests
    • Authors: Zhang, Q.-B.; Jia, H.; Zheng, J.; Fang, O.; Yang, J.; Langzhen, J.-Y.; Hebda, R.J.
    • Journal: Research Square
    • Year: 2023
Southeast Asian ecological dependency on Tibetan Plateau streamflow over the last millennium
    • Authors: Chen, F.; Man, W.; Wang, S.; Esper, J.; Meko, D.; Büntgen, U.; Yuan, Y.; Hadad, M.; Hu, M.; Zhao, X. et al.
    • Journal: Nature Geoscience
    • Year: 2023
Linkage between spruce forest decline and cloud cover increase in the Qilian Mountains of the northeastern Tibetan Plateau
    • Authors: Jing Yang, Baowei Zhao, Jiacheng Zheng, Qi Zhang, Yan Li, Fuhai Ma, Ouya Fang
    • Journal: Trees
    • Year: 2023
Tree-ring evidence of ecological stress memory
    • Authors: Yumei Mu, Lixin Lyu, Yan Li, Ouya Fang
    • Journal: Proceedings of the Royal Society B: Biological Sciences
    • Year: 2022
Non-linear modelling reveals a predominant moisture limit on juniper growth across the southern Tibetan Plateau
    • Authors: Hengfeng Jia, Ouya Fang, Lixin Lyu
    • Journal: Annals of Botany
    • Year: 2022