Thatikonda Ragini | Embedded Vision | Best Researcher Award

Mrs. Thatikonda Ragini | Embedded Vision | Best Researcher Award

PhD Researcher at National Institute of Technology Warangal, India

Thatikonda Ragini is a dedicated doctoral researcher at the National Institute of Technology (NIT), Warangal, specializing in artificial intelligence and embedded systems. Under the supervision of Dr. Kodali Prakash, her research aims to develop fast, lightweight, and power-efficient neural architectures suitable for real-world applications, particularly on low-end edge devices. Her interest extends across various domains such as pathology and accessibility, showcasing her drive to make impactful contributions. With six years of teaching experience and three years in R&D, Ragini has a well-rounded academic and professional background. She has published several influential papers in SCIE-indexed journals, demonstrating her expertise in deep learning, machine learning, and computer vision. Her technical acumen and dedication to innovative research make her a promising figure in her field, positioning her as a strong contender for future advancements in AI-driven embedded systems.

Professional Profile

Education

Thatikonda Ragini has a strong academic foundation, starting with her Bachelor of Technology (B.Tech.) in Electronics and Communication Engineering from JNTU Hyderabad in 2010, where she graduated with distinction. She then pursued a Master of Technology (M.Tech.) in VLSI Design, also from JNTU Hyderabad, completing it in 2015 with an impressive distinction score of 82%. Building on her technical expertise, she is currently working toward her Doctor of Philosophy (Ph.D.) at NIT Warangal, focusing on Artificial Intelligence and Embedded Systems. Having submitted her thesis, she is set to complete her Ph.D. in 2024. Her strong educational background reflects a clear trajectory of specialization in cutting-edge fields like machine learning, deep learning, and computer vision, which are central to her ongoing research efforts.

Professional Experience

Ragini’s professional journey spans both academia and research. She has six years of teaching experience, having worked as an Assistant Professor at both Trinity Engineering College (2010-2013) and Jyothishmathi Institute of Technology & Science (2015-2018). During her teaching career, she taught key subjects such as Machine Learning, Deep Learning, Computer Vision, and Internet of Things (IoT), significantly contributing to student learning and development. Alongside teaching, Ragini has three years of R&D experience, where she focused on developing embedded systems and AI-driven technologies. She has also gained valuable experience in writing research proposals for R&D funding agencies, showcasing her ability to lead and contribute to high-impact research projects. Her combined academic and R&D experience makes her a versatile professional in her field.

Research Interests:

Ragini’s research interests lie at the intersection of machine learning, deep learning, and computer vision. Specifically, she focuses on designing lightweight and efficient neural architectures that can be deployed on low-end edge devices with limited power and memory capabilities. Her work aims to optimize these architectures for real-world applications, particularly in domains like pathology and accessibility, which have high societal relevance. Ragini is also interested in embedded vision applications, exploring how computer vision systems can be integrated into embedded systems to enhance performance across diverse fields. Her research contributes to the advancement of AI-driven embedded systems, offering solutions that are both resource-efficient and scalable, making them suitable for real-world deployment on constrained devices.

Research Skills:

Ragini possesses a diverse set of research skills that position her as a highly capable researcher. She is proficient in machine learning, deep learning, and computer vision, with specialized knowledge in designing neural architectures optimized for low-power, memory-efficient applications. Her technical expertise spans across VLSI design, making her adept at integrating software and hardware for embedded systems. Ragini has hands-on experience with programming languages like Python and frameworks such as TensorFlow and PyTorch, enabling her to develop and deploy advanced AI models. Additionally, she is skilled in writing research proposals for R&D funding, contributing to her experience in project management and execution. Her ability to handle complex datasets, conduct experiments, and analyze results reflects her strong analytical and problem-solving skills.

Awards and Honors:

Ragini’s academic and research accomplishments have been recognized through several accolades. She achieved distinction in both her Bachelor’s and Master’s degrees, reflecting her consistent academic excellence. She also completed NPTEL courses in Machine Learning and Deep Learning with Silver Elite certification, demonstrating her commitment to continuous learning and mastery of complex subjects. Her published research in high-impact SCIE journals further attests to her scholarly achievements, with her papers gaining recognition in the artificial intelligence and computer vision communities. Although she has not listed specific research awards, her growing body of work, which includes influential journal publications and conference presentations, positions her as a strong candidate for future research awards and honors.

Conclusion

Thatikonda Ragini has a strong research portfolio with an impressive focus on embedded systems, machine learning, and computer vision. Her publication record in SCIE journals and conference presentations underscore her impactful contributions. While enhancing international collaborations and increasing engagement in professional societies would boost her candidacy further, her current achievements make her a suitable candidate for the Best Researcher Award.

Publication Top Note

  1. S2VSNet: Single stage V-shaped network for image deraining & dehazing
    Authors: Ragini, T., Prakash, K., Cheruku, R.S.
    Journal: Digital Signal Processing: A Review Journal
    Year: 2025
  2. DeTformer: A Novel Efficient Transformer Framework for Image Deraining
    Authors: Ragini, T., Prakash, K., Cheruku, R.
    Journal: Circuits, Systems, and Signal Processing
    Year: 2024
  3. Rain Streak Removal via Spatio-Channel Based Spectral Graph CNN for Image Deraining
    Authors: Ragini, T., Prakash, K.
    Conference: Communications in Computer and Information Science
    Year: 2023
  4. Progressive Multi-scale Deraining Network
    Authors: Ragini, T., Prakash, K.
    Conference: 2022 IEEE International Symposium on Smart Electronic Systems (iSES)
    Year: 2022

 

Asha Sathe | Computer Vision | Best Researcher Award

Mrs. Asha Sathe | Computer Vision | Best Researcher Award

Research Scholar at Sathyabama Institute of Science and Technology, India.

Ms. Asha Prashant Sathe is an experienced academic professional with over 21 years of teaching experience in Computer Engineering. Currently an Assistant Professor at Army Institute of Technology, Pune, she has taught subjects such as Artificial Intelligence, Distributed Systems, and Discrete Mathematics. She is actively pursuing her PhD from Sathyabama University and has authored several research papers in areas like image processing, deep learning, and artificial intelligence. Her notable publications include work on neural networks and image manipulation detection. In addition to her academic contributions, Ms. Sathe holds a patent for Intelligent Ear Pods by Voice Commands and Gestures and has participated in numerous seminars and workshops to enhance her skills. She has also co-investigated a funded project on software architecture, showcasing her engagement in research initiatives. Ms. Sathe’s achievements include the Best Teacher Award and AICTE grants, reflecting her commitment to both teaching and research innovation.

Profile

Education

Ms. Asha Prashant Sathe has a diverse educational background in computer engineering. She completed her Bachelor of Engineering (BE) in Computer Engineering from Pune University in 1999, laying a strong foundation for her career in technology and education. She went on to pursue a Master of Engineering (ME) in Computer Science and Engineering from Swami Ramanand Teerth Marathwada University (SRTMU), Nanded, in 2010, graduating with a score of 7.2%. Her academic journey also includes a Diploma in Computer Technology (DCT) from Mumbai in 1996, where she achieved a commendable 69.18%. Before that, she had a solid start with her Secondary School Certificate (SSC) from the State Board in 1993, securing an impressive 85.42%. Currently, she is pursuing her PhD from Sathyabama University, focusing on advancing her expertise and contributing to the field of computer science. Her educational progression reflects dedication and a continuous pursuit of knowledge.

Professional Experience

Ms. Asha Prashant Sathe is an experienced academic professional with over 21 years of teaching experience in Computer Engineering. She currently serves as an Assistant Professor at the Army Institute of Technology (AIT), Pune, where she has been since 2006. Her extensive teaching career includes previous roles as a lecturer at Amrutvahini College of Engineering (AVCOE), Sangamner, and Pravara Rural Engineering College (PREC), Loni. Throughout her career, she has taught various subjects such as Artificial Intelligence, Distributed Systems, Software Engineering, and Web Technology. Ms. Sathe has also held several administrative and academic coordination roles, including NBA Coordinator, Project Coordinator, and Seminar Coordinator. In addition to her teaching expertise, she has contributed to curriculum development and accreditation processes, enhancing the quality of education in her institution. Her professional experience showcases her dedication to both teaching and the continuous improvement of educational standards in engineering.

Research Interest

Ms. Asha Prashant Sathe’s research interests lie primarily in the fields of Image Processing, Pattern Recognition, Artificial Intelligence (AI), and Deep Learning. She is particularly focused on the development of advanced algorithms and techniques for image manipulation detection and optical character recognition (OCR). Her work involves exploring neural networks, including recurrent neural networks (RNNs), to create systems capable of complex decision-making and pattern recognition. Additionally, Ms. Sathe is passionate about leveraging machine learning models to solve real-world problems in various domains, including gender and age classification based on digital data like blogs. She is also interested in the intersection of deep learning and natural language processing (NLP), focusing on the integration of AI technologies in software development. Her goal is to further enhance AI’s capabilities in automation, improving both user interaction and system performance across different applications.

Research Skills

Ms. Asha Prashant Sathe possesses strong research skills, particularly in the fields of Artificial Intelligence, Image Processing, and Deep Learning. Her work on image manipulation detection and neural networks demonstrates her technical expertise in applying advanced algorithms and machine learning techniques. She has contributed to both journal publications and a patent on intelligent ear pods, showcasing her ability to bridge theoretical research with practical innovation. Her experience extends to pattern recognition and optical character recognition, highlighting her analytical skills in solving complex computational problems. Additionally, Ms. Sathe has been involved in collaborative research projects, such as her role as a co-investigator on a software engineering grant, which reflects her capability in teamwork and securing research funding. Her participation in numerous workshops and training programs, such as Natural Language Processing and Project Management, further emphasizes her commitment to continually developing her research acumen in emerging technologies.

Author Metrics
  • Total Publications: 10 (including journal and conference articles)
  • Patent: 1 (Intelligent ear pods by voice commands and gestures)
  • Notable Journals:
    • JOICS (2021)
    • IJMH (2020)
    • IRJET (2019)
    • IRAJ Research Forum (2014)
    • NCFCA (2009)
  • Notable Conferences:

Conclusion

Ms. Asha Prashant Sathe exhibits a commendable academic and research background with strengths in teaching, publications, innovation, and professional development. However, to compete for a prestigious research-focused award like the Best Researcher Award, areas such as more dedicated research years, completion of her PhD, student supervision, and high-impact publications should be strengthened. While she shows great potential, focusing on these aspects would significantly enhance her candidacy for future research accolades.

Publications Top Notes

Approaching Image Manipulation Detection Using Yolov5, (2021). Approaching Image Manipulation
Detection Using Yolov5. JOICS. volume 11(Issue-4), 428-432. ISBN/ ISSN No : ISSN:1548-7741. URL :
www.joics.org. 

Title: Approaching Image Manipulation Detection Using Yolov5
Author(s): [Author(s) Name]
Journal: Journal of Information and Communication Systems (JOICS)
Volume: 11
Issue: 4
Pages: 428-432
Year: 2021
ISBN/ISSN: ISSN: 1548-7741
URL: www.joics.org

2. My Experience:Science behind Online Teaching – Learning, (2020). My Experience:Science behind                Title: My Experience: Science behind Online Teaching – Learning
Author(s): [Author(s) Name]
Journal: International Journal of Multidisciplinary Humanities (IJMH)
Volume: 5
Issue: 1
Pages: 1-2
Year: 2020
ISBN/ISSN: ISSN 2394-0913
URL: https://www.ijmh.org/download/volume-5-issue-1/

Online Teaching – Learning. IJMH. Volume 5(Issue-1), 1-2. ISBN/ ISSN No : ISSN 2394-0913. URL :
https://www.ijmh.org/download/volume-5-issue-1/.
3. Asha Prashant Sathe, (2019). Neural Story Teller Using RNN and Genrative Algorithms. IRJET. e-ISSN2395-0056(e-ISSN-2395-0056), 33-34. ISBN/ ISSN No : IRJET.                                                                                                                  Title: Neural Story Teller Using RNN and Generative Algorithms
Author(s): Asha Prashant Sathe
Journal: International Research Journal of Engineering and Technology (IRJET)
Volume: [Volume Number]
Issue: [Issue Number]
Pages: 33-34
Year: 2019
ISBN/ISSN: e-ISSN 2395-0056


4. Asha Prashant Sathe, (2014). Gender and Age Classification on the Basis of Blogs. IRAJ Research
Forum. EECSMEPUNE-30034-124(EECSMEPUNE-30034-124), 17-22. ISBN/ ISSN No :
EECSMEPUNE-30034-124.     

Title: Gender and Age Classification on the Basis of Blogs
Author(s): Asha Prashant Sathe
Journal: IRAJ Research Forum
Volume: [Volume Number]
Issue: [Issue Number]
Pages: 17-22
Year: 2014
ISBN/ISSN: EECSMEPUNE-30034-124                                                                                                                                               

  5. Asha Prashant Sathe, (2009). Face Recognition Using Hidden Markov Model. NCFCA 2009. NCFCA2009(NCFCA-2009), 75-77. ISBN/ ISSN No : NCFCA-2009.                                                                                                  Title: Face Recognition Using Hidden Markov Model
Author(s): Asha Prashant Sathe
Conference: National Conference on Face and Character Analysis (NCFCA)
Year: 2009
Pages: 75-77
ISBN/ISSN: NCFCA-2009