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Faculty Dr Ajay Dilip Kumar Marapatla

Dr Ajay Dilip Kumar Marapatla

Assistant Professor

Department of Computer Science and Engineering

Contact Details

ajaydilipkumar.m@srmap.edu.in

Office Location

Homi J Bhabha Block, Level 2, Cubicle No: 5

Education

2024
PhD Pursuing
Pondicherry Central University
2014
MTech
Andhra University, Visakhapatnam, Andhra Pradesh.
2009
BTech
Andhra University, Visakhapatnam, Andhra Pradesh.

Experience

No data available

Research Interest

  • Power, Energy, Efficient resource management, and Energy Harvesting.
  • Investigating the Potential of IoT for Smart Healthcare Solutions.
  • Developing Secure and Scalable IoT-Based Solutions for Smart Cities.
  • Examining the Impact of IoT on Smart Home Security.

Awards

  • 2023- Successfully completed the " Palo Alto Networks Cybersecurity Academy Educator Certificate" certification Course.
  • Secured 2nd Rank in the University Ranking for M. Tech.

Memberships

No data available

Publications

  • Efficient deep learning models for Telugu handwritten text recognition

    Mr Boddu L V Siva Rama Krishna, Dr Ajay Dilip Kumar Marapatla, Buddaraju Revathi., B N V Narasimha Raju., S Suryanarayanaraju

    Source Title: Indonesian Journal of Electrical Engineering and Computer Science, Quartile: Q4, DOI Link

    View abstract ⏷

    Optical character recognition (OCR) technology is indispensable for converting and analyzing text from various sources into a format that is editable and searchable. Telugu handwriting presents notable challenges due to the resemblance of characters, the extensive character set, and the need to segment overlapping characters. To segment the overlapping characters, we assess the width of small characters within a word and segment the overlapping characters accordingly. This method is well suited for the segmentation of overlapping compound characters. To address the recognition of similar characters with less training periods we have used ResNet 18 and SqueezeNet models which have achieved character recognition rates of 95% and 94% respectively
  • Covind-19 Detection Using X-Ray Images by Machine Learning

    Dr Ajay Dilip Kumar Marapatla, Chalapathiraju Kanumuri., T Ravichandra., Kothapalli Phanivarma

    Source Title: African Journal of Biomedical Research, Quartile: Q4, DOI Link

    View abstract ⏷

    For densely populated international locations it's miles difficult to prevent the spread of recent infections which will spread at quicker rates. COVID-19 has created a new world, a new normal, with direct impact on health and leading to economic, social and political consequences. Artificial Intelligence (AI) is a dominant tool having good potential in battling the COVID- 19. There has been a dash to use AI, ever since the outburst of the epidemic. This article provides necessary review, examining the part of AI being played in battle in opposition to COVID-19. The two sub-fields of AI namely, machine learning (ML) and deep learning (DL) which can very well contribute to the battle in opposition to COVID-19, is conferred. This paper helps in concluding that so far AI has been that impactful in opposition to COVID19 as it should be. The usage of AI is weighed down due to lack of good quality data, and too much- unlabelled data. To overcome these restraints, a very balanced relationship between data privacy and public health is required, with precise human-AI interaction. In this paper we discuss on how COVID-19 detection is done by AI methods using X-Ray images and the results were compared with existing methods. This paper also helps to know deep review on COVID-19 suing Deep Learning. We also discussed how COVID-19 can be traced using Deep Learning methods.

Patents

  • A Computer-Implemented System for Predicting Drug-Target Interactions

    Dr Ajay Dilip Kumar Marapatla

    Patent Application No: 202541054965, Date Filed: 06/06/2025, Date Published: 13/06/2025, Status: Published

  • System And Method for Real-Time Beverage Ordering and Delivery

    Dr Ajay Dilip Kumar Marapatla

    Patent Application No: 202541058252, Date Filed: 17/06/2025, Date Published: 03/11/2025, Status: Filed

Projects

Scholars

Interests

  • LOT
  • Network Security
  • Networking

Thought Leaderships

There are no Thought Leaderships associated with this faculty.

Top Achievements

Education
2009
BTech
Andhra University, Visakhapatnam, Andhra Pradesh.
2014
MTech
Andhra University, Visakhapatnam, Andhra Pradesh.
2024
PhD Pursuing
Pondicherry Central University
Experience
No data available
Research Interests
  • Power, Energy, Efficient resource management, and Energy Harvesting.
  • Investigating the Potential of IoT for Smart Healthcare Solutions.
  • Developing Secure and Scalable IoT-Based Solutions for Smart Cities.
  • Examining the Impact of IoT on Smart Home Security.
Awards & Fellowships
  • 2023- Successfully completed the " Palo Alto Networks Cybersecurity Academy Educator Certificate" certification Course.
  • Secured 2nd Rank in the University Ranking for M. Tech.
Memberships
No data available
Publications
  • Efficient deep learning models for Telugu handwritten text recognition

    Mr Boddu L V Siva Rama Krishna, Dr Ajay Dilip Kumar Marapatla, Buddaraju Revathi., B N V Narasimha Raju., S Suryanarayanaraju

    Source Title: Indonesian Journal of Electrical Engineering and Computer Science, Quartile: Q4, DOI Link

    View abstract ⏷

    Optical character recognition (OCR) technology is indispensable for converting and analyzing text from various sources into a format that is editable and searchable. Telugu handwriting presents notable challenges due to the resemblance of characters, the extensive character set, and the need to segment overlapping characters. To segment the overlapping characters, we assess the width of small characters within a word and segment the overlapping characters accordingly. This method is well suited for the segmentation of overlapping compound characters. To address the recognition of similar characters with less training periods we have used ResNet 18 and SqueezeNet models which have achieved character recognition rates of 95% and 94% respectively
  • Covind-19 Detection Using X-Ray Images by Machine Learning

    Dr Ajay Dilip Kumar Marapatla, Chalapathiraju Kanumuri., T Ravichandra., Kothapalli Phanivarma

    Source Title: African Journal of Biomedical Research, Quartile: Q4, DOI Link

    View abstract ⏷

    For densely populated international locations it's miles difficult to prevent the spread of recent infections which will spread at quicker rates. COVID-19 has created a new world, a new normal, with direct impact on health and leading to economic, social and political consequences. Artificial Intelligence (AI) is a dominant tool having good potential in battling the COVID- 19. There has been a dash to use AI, ever since the outburst of the epidemic. This article provides necessary review, examining the part of AI being played in battle in opposition to COVID-19. The two sub-fields of AI namely, machine learning (ML) and deep learning (DL) which can very well contribute to the battle in opposition to COVID-19, is conferred. This paper helps in concluding that so far AI has been that impactful in opposition to COVID19 as it should be. The usage of AI is weighed down due to lack of good quality data, and too much- unlabelled data. To overcome these restraints, a very balanced relationship between data privacy and public health is required, with precise human-AI interaction. In this paper we discuss on how COVID-19 detection is done by AI methods using X-Ray images and the results were compared with existing methods. This paper also helps to know deep review on COVID-19 suing Deep Learning. We also discussed how COVID-19 can be traced using Deep Learning methods.
Contact Details

ajaydilipkumar.m@srmap.edu.in

Scholars
Interests

  • LOT
  • Network Security
  • Networking

Education
2009
BTech
Andhra University, Visakhapatnam, Andhra Pradesh.
2014
MTech
Andhra University, Visakhapatnam, Andhra Pradesh.
2024
PhD Pursuing
Pondicherry Central University
Experience
No data available
Research Interests
  • Power, Energy, Efficient resource management, and Energy Harvesting.
  • Investigating the Potential of IoT for Smart Healthcare Solutions.
  • Developing Secure and Scalable IoT-Based Solutions for Smart Cities.
  • Examining the Impact of IoT on Smart Home Security.
Awards & Fellowships
  • 2023- Successfully completed the " Palo Alto Networks Cybersecurity Academy Educator Certificate" certification Course.
  • Secured 2nd Rank in the University Ranking for M. Tech.
Memberships
No data available
Publications
  • Efficient deep learning models for Telugu handwritten text recognition

    Mr Boddu L V Siva Rama Krishna, Dr Ajay Dilip Kumar Marapatla, Buddaraju Revathi., B N V Narasimha Raju., S Suryanarayanaraju

    Source Title: Indonesian Journal of Electrical Engineering and Computer Science, Quartile: Q4, DOI Link

    View abstract ⏷

    Optical character recognition (OCR) technology is indispensable for converting and analyzing text from various sources into a format that is editable and searchable. Telugu handwriting presents notable challenges due to the resemblance of characters, the extensive character set, and the need to segment overlapping characters. To segment the overlapping characters, we assess the width of small characters within a word and segment the overlapping characters accordingly. This method is well suited for the segmentation of overlapping compound characters. To address the recognition of similar characters with less training periods we have used ResNet 18 and SqueezeNet models which have achieved character recognition rates of 95% and 94% respectively
  • Covind-19 Detection Using X-Ray Images by Machine Learning

    Dr Ajay Dilip Kumar Marapatla, Chalapathiraju Kanumuri., T Ravichandra., Kothapalli Phanivarma

    Source Title: African Journal of Biomedical Research, Quartile: Q4, DOI Link

    View abstract ⏷

    For densely populated international locations it's miles difficult to prevent the spread of recent infections which will spread at quicker rates. COVID-19 has created a new world, a new normal, with direct impact on health and leading to economic, social and political consequences. Artificial Intelligence (AI) is a dominant tool having good potential in battling the COVID- 19. There has been a dash to use AI, ever since the outburst of the epidemic. This article provides necessary review, examining the part of AI being played in battle in opposition to COVID-19. The two sub-fields of AI namely, machine learning (ML) and deep learning (DL) which can very well contribute to the battle in opposition to COVID-19, is conferred. This paper helps in concluding that so far AI has been that impactful in opposition to COVID19 as it should be. The usage of AI is weighed down due to lack of good quality data, and too much- unlabelled data. To overcome these restraints, a very balanced relationship between data privacy and public health is required, with precise human-AI interaction. In this paper we discuss on how COVID-19 detection is done by AI methods using X-Ray images and the results were compared with existing methods. This paper also helps to know deep review on COVID-19 suing Deep Learning. We also discussed how COVID-19 can be traced using Deep Learning methods.
Contact Details

ajaydilipkumar.m@srmap.edu.in

Scholars