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

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🧑‍🎓 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

 

Hadi Shokati | Machine Learning and AI Applications | Best Researcher Award

Mr. Hadi Shokati | Machine Learning and AI Applications | Best Researcher Award

University of Tuebingen | Germany

PUBLICATION PROFILE

Orcid

INTRODUCTION 🌍

Mr. Hadi Shokati is a dedicated PhD candidate from the Department of Geoscience at the University of Tübingen in Germany, currently conducting research on soil erosion in agricultural landscapes. His studies focus on dynamic changes of land use patterns and structures, encapsulated under his thesis title DYLAMUST (Soil erosion in agricultural landscapes in the context of dynamic changes of land use patterns and structures). His educational journey reflects a solid foundation in water sciences and engineering, with significant expertise in artificial intelligence, hydrology, and programming.

EARLY ACADEMIC PURSUITS 📚

Hadi began his academic career with a Bachelor’s degree in Water Science and Engineering from Mohaghegh Ardabili University, Iran, in 2016. His passion for water engineering led him to pursue a Master’s degree in the same field at Tarbiat Modares University in Iran (2017–2019). His early academic endeavors laid a strong groundwork for his advanced studies, focusing on water management, irrigation, and environmental sciences.

PROFESSIONAL ENDEAVORS 🌐

Throughout his academic career, Mr. Shokati has taken up significant roles as a Teaching Assistant (TA) at the University of Tehran. He was involved in courses such as Fluid Mechanics, Designing Surface Irrigation Systems, Designing Drainage and Irrigation Networks, and Surface Irrigation Hydraulics. These experiences allowed him to apply theoretical knowledge in real-world settings, further solidifying his expertise in water management and environmental engineering.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Hadi’s ongoing research centers on understanding soil erosion in agricultural landscapes. His work aims to investigate the dynamic interactions between land use changes, soil degradation, and the associated environmental impact, providing insights for sustainable land management practices. With the use of modern AI tools, programming languages like Python, and software like Arc GIS and ENVI, his research is at the forefront of geoscience and environmental studies.

IMPACT AND INFLUENCE 🌱

Mr. Shokati’s research is poised to make significant contributions to sustainable agricultural practices, offering new methodologies for tackling soil erosion in areas with changing land use patterns. His multidisciplinary approach, blending environmental science with technology and AI, is a key factor in advancing the field and shaping future solutions to ecological problems.

ACADEMIC CITATIONS AND PUBLICATIONS 📑

Hadi Shokati has been actively involved in academic writing, publishing his work on the intersection of hydrology, soil erosion, and land use changes. His research and findings are expected to have a lasting impact on future publications in the fields of geoscience, environmental engineering, and agriculture.

HONORS & AWARDS 🏆

Throughout his academic career, Mr. Shokati has earned numerous accolades. These awards reflect his commitment to excellence in research and teaching. His most notable honor includes receiving a recognition award for his innovative research at the University of Tübingen.

LEGACY AND FUTURE CONTRIBUTIONS 🌟

As Hadi advances in his doctoral studies, his work is expected to inspire future generations of researchers in environmental science, particularly in the areas of soil conservation, water resource management, and sustainable land use planning. His future contributions will likely redefine how we approach ecological preservation in agricultural contexts.

FINAL NOTE 📜

Mr. Hadi Shokati’s academic journey, marked by his rigorous research and teaching experience, promises to have a lasting influence in the realm of water engineering and environmental science. With a strong foundation in both theoretical knowledge and practical applications, he is well-positioned to continue making valuable contributions to the field of geoscience.

 TOP NOTES PUBLICATIONS 📚

Erosion-SAM: Semantic segmentation of soil erosion by water
    • Authors: Hadi Shokati, Andreas Engelhardt, Kay Seufferheld, Ruhollah Taghizadeh-Mehrjardi, Peter Fiener, Hendrik P.A. Lensch, Thomas Scholten

    • Journal: CATENA

    • Year: 2025

Assessing the Role of Environmental Covariates and Pixel Size in Soil Property Prediction: A Comparative Study of Various Areas in Southwest Iran
    • Authors: Pegah Khosravani, Majid Baghernejad, Ruhollah Taghizadeh-Mehrjardi, Seyed Roohollah Mousavi, Ali Akbar Moosavi, Seyed Rashid Fallah Shamsi, Hadi Shokati, Ndiye M. Kebonye, Thomas Scholten

    • Journal: Land

    • Year: 2024

Assessment of Land Suitability Potential Using Ensemble Approaches of Advanced Multi-Criteria Decision Models and Machine Learning for Wheat Cultivation
    • Authors: Kamal Nabiollahi, Ndiye M. Kebonye, Fereshteh Molani, Mohammad Hossein Tahari-Mehrjardi, Ruhollah Taghizadeh-Mehrjardi, Hadi Shokati, Thomas Scholten

    • Journal: Remote Sensing

    • Year: 2024

Random Forest-Based Soil Moisture Estimation Using Sentinel-2, Landsat-8/9, and UAV-Based Hyperspectral Data
    • Authors: Hadi Shokati, Mahmoud Mashal, Aliakbar Noroozi, Ali Abkar, Saham Mirzaei, Zahra Mohammadi-doqozloo, Ruhollah Taghizadeh, Pegah Khosravani, Kamal Nabiollahi, Thomas Scholten

    • Journal: Remote Sensing

    • Year: 2024