Contact Number: +91 9705690202
Academic Experience: 14 Years
Affiliation: B V Raju Institute of Technology
Sl. No | Qualification | Month & Year of Passing | Institution |
1. | Ph.D (Computer Science and Engineering) | Jan 2017 | Jawaharlal Nehru Technological University Kakinada (JNTUK), Kakinada |
2. | M.Tech(Computer Science) | August 2008 | Jawaharlal Nehru Technological University Kakinada (JNTUK), Kakinada |
3 | B.Tech(Computer Science and Engineering) | April 2006 | Jawaharlal Nehru Technological University (JNTU), Hyderabad |
- Professor & Head, CSE( Data Science), BVRIT
- Department Curriculum Coordinator for R20, R18 Regulations at BVRIT
- Institute’s Innovation Council (IIC) Coordinator, BVRIT.
- College level Coordinator for National Innovation and Start-up Policy (NISP).
- NBA & NAAC Coordinator for few Criterions, BVRIT.
- Worked as Training and Placements Coordinator for the Department of Computer Science and Engineering, BVRIT.
- Worked as Head of the Department (CSE) at Malla Reddy Institute of Technology (MRIT), Hyderabad.
Journals | Conferences | Books/Chapters | Citations | |||
National | International | National | International | National | International | |
2 | 16 |
| 12 | 1 | 1 | 23 |
Book/Chapter Name | ISBN | Publisher |
Deep Learning And Its Applications | 978-93-94339-95-8 | AGPH Books (Academic Guru Publishing House) |
Classification of Nucleotides Using Memetic Algorithms and Computational Methods | 978-981-15-6353-9 | Advances in Intelligent Systems and Computing, vol 1199, Springer, 10.1007/978-981-15-6353-9_1 |
Scopus ID | 57219017008 | ORCID ID | 0000-0001-5647-6452 |
Publons ID | ABF-8810-2020 | Google Scholar | O8Lc8ZAAAAAJ |
Science Citation Indexed (SCI):
- Kollapudi, Purnachand at Al. (2022). A New Method for Scene Classification from the Remote Sensing Images. Computers, Materials & Continua. 72. 1339-1355. 10.32604/cmc.2022.025118.
- Purnachand K at. Al “A Novel Faster R-CNN with ODN based Rain Removal Technique”, Hindawi, Mathematical Problems in Engineering, Volume 2022, Article ID 4546135, 11 pages https://doi.org/10.1155/2022/4546135.
- Purnachand K at Al “Block Chain Assisted Bio Metric Verification System using MantaRay Foraging Optimization with Deep Learning Model, Elsevier (Submitted).
- Purnachand K at Al “Secure Energy Aware Optimal Routing using Reinforcement Learning-based Decision-Making with a Hybrid Optimization Algorithm in MANET”, IEEE Access (Submitted).
- Purnachand K at. Al “An Efficient LSTM Model for digital cross language summarization”, Computers, Materials & Continua (CMC), Technical Press. (Submitted).
- Purnachand K at. Al. ’Bio-Inspired Load Balancing Strategy for Cloud-Based Data Centre with Predictive: Machine Learning Approach and Comparative Analogies”. Computers, Materials & Continua (CMC), Technical Press. (Submitted).
COMPENDEX [formerly Ei] (Elsevier):
- Purna Chand and Dr.G.Narsimha, “Integrated Framework for Semantic Text Mining and Ontology Construction using Inference Engine” in International Journal of Data Science (IJDS), Inderscience Journals, 2017 Vol.2 No.2, pp.138 – 154, DOI: 10.1504/IJDS.2017.084766
Web of Science (WOS):
- Purnachand Kollapudi, “An Automated Framework for Detecting Change in the Source Code and Test Case Change Recommendation “in International Journal of Advanced Computer Science and Applications, Vol. 11, No. 8, PP: 270-280.
SCOPUS:
- K. Purnachand at. Al. “Analysis of Effective Medical Record Storage Formats and Demonstration of Time Efficient Secure Storage Framework” in European Journal of Molecular & Clinical Medicine, December 2020 Volume 7, Issue 6, Pages 2744-2763.
- PurnachandKollapudi, “Provision of Security Using Substitution Ciphers” JOURNAL OF CRITICAL REVIEWS ISSN- 2394-5125 VOL 7, ISSUE 04, 2020.
- Purna Chand “A Comparative Study of Famous Image Compression Methods Based on Bits per Pixel: A Survey” in Journal of Critical Reviews, Web of Science, VOL 7, ISSUE 18, 2020, ISSN- 2394-5125.
- Purna Chand “Sentiment Extraction and Analysis using Machine Learning Tools-Survey” in IOP Conf. Series: Materials Science and Engineering 594 (2019) 012022 IOP Publishing, DOI:10.1088/1757-899X/594/1/012022.
UGC:
- K.Purna Chand, “A Survey on the Collaborative Tool-MoKi”, Pp252-256, in International Journal of Scientific Research and Review (IJSRR). ISSN-2279 0543.
- K.Purna Chand, “Spatial Data Analysis using Map-Reduce Techniques, in International Journal of Scientific Research and Review (IJSRR), Pp257-262, ISSN-2279 0543.
- K.Purna Chand, “A Novel Approach for Data Storage in Heterogeneous Cloud Environments” in “International Journal of Latest Trends in Engineering and Technology (IJLTET)”, Pp133-140, ISSN-2319 3778.
- K.Purna Chand, “Requirements Evocation and Analysis using ETL in Cloud Environments” in “International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT)”, Pp1597-1603,ISSN : 2456-3307
- K.Purna Chand “Predictive Healthcare Informatics using Deep Learning- A Big Data Approach” in International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), Pp1604-1608, ISSN: 2456-3307
- K Purna Chand and Jekkala Chandra Sekhar, “An Empirical Study: Data Integration tools in Big Data Environment” Journal of Innovation in Computer Science and Engineering(JICSE), Volume 7 Issue 2, ISSN: 2278-0947.
- Dr. K. Purnachand at. Al. “Crop Prediction Based on Soil Types using Machine Learning”, ICASCCI-21 on 23rd–24th July ‘2021 Conference Proceeding indexing in SCOPUS and WOS with Publication Partner American Institute of Physics (AIP).
- K. Purnachand at. Al. “Predictive Maintenance of Machines and Industrial Equipment”, International Conference on Communication Systems and Network Technology CSNT-2021, pp. 318-324, IEEE Explore DOI: 10.1109/CSNT51715.2021.9509696.
- K. Purnachand and Syamala Rao P “Stock Price Prediction using Machine Learning”, International Conference on Communication Systems and Network Technology (CSNT-2021), IEEE Explore
- K.Purnachand and B.Yashwanth Akhil, “Cardiovascular Disease Severity Prediction using Machine Learning Approaches” in International Conference on Computational & Experimental Methods for Advancing Engineering Systems (ICCEAESA-2019).
- Purna Chand and Dr.G.Narsimha, “Security Issues with Possible Solutions in Cloud Computing” In International Conference on Innovations in Computing & Communication 2015 (ICICC-2015), pp 329-334, ISBN:978-93-82163-59-6
- Purna Chand and Dr.G.Narsimha, “Secure Data Management in Cloud” in National Conference on Research Trends in Computer Science and Technology (NCRTCST-2015),pp 19-22,ISBN:978-81-923249-2-0.
- Purna Chand and Dr.G.Narsimha, “Semantic Annotations for Efficient Information Retrieval” In International Conference on Research Advancements in Engineering Science and Information Technology (ICRAESIT-2015), pp. 63-66, ISBN: 978-93-85100-56-7.
- Purna Chand, “A Short Survey on IoT Security Issues”. in “International Conference on Research Advancements in Engineering Science and Information Technology (ICRAESIT-2015)”, pp142-145, ISBN: 978-93-85100-56-7
- Purna Chand and Dr.G.Narsimha, “An Integrated Approach to Improve the Text Categorization Using Semantic Measures” is accepted by International Conference on Computational Intelligence in Data Mining (ICCIDM-2014), December 2014 and Published in Smart Innovation, Systems and Technologies 32, Springer India 2015. DOI: 10.1007/978-81-322-2208-8_5.
- Purna Chand and Dr.G.Narsimha , “Framework for Automatic Construction of Taxonomies (FACT)” in International Conference on Innovations in Computing & Communication 2015 (ICICC-2015), February 2015.ISBN: 978-93-82163-59-6.
- Purna Chand and Dr.G.Narsimha, “An Integrated Approach to Improve the Text Categorization Using Semantic Measures” is accepted by International Conference on Computational Intelligence in Data Mining (ICCIDM-2014), December 2014 and Published in Smart Innovation, Systems and Technologies 32, Springer India 2015. DOI: 10.1007/978-81-322-2208-8_5.
- Purna Chand and Dr.G.Narsimha ,“An Integrated Framework for Generating Domain Ontologies Using Semantic Measures and Modelling Tools” in International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO-2015), 25th Jan 2015.Published in IEEE Explore Digital Library, ISBN: 978-1-4799-7678-2/15, DOI:10.1109/EESCO.2015.7253780.
Applied: IoT for Bio-Based Integrated Pest Management under Integrated Farming System” applied to Department of Science and Technology (DST) UnderScience and Heritage Research Initiative (SHRI) Scheme on 31st August, 2021.
Completed: “Identification and Demonstration of Cost-Effective Technologies to maximize habitat energy self –sufficiency” sanctioned by Department of Science and Technology (DST) with the file no: TMD/CERI/BEE/2016/096(G).
Title: Plant Disease Detection Using Deep Learning Techniques
Abstract: In agriculture, the early detection of diseases is important for an efficient crop yield. Healthy or unhealthy, the bacterial spot, late blight, sesame leaf spot, seedling blight, and yellow curved leaf diseases affect the quality of the crop. To avoid errors due to manual detection of diseases, deep learning methods are used for image processing. Using a deep convolution neural network that has been trained and fine tuned to adequately match a database of a plant leaves that was compiled independently for various plant illnesses, the technique paper presented here may represent a novel method for identifying plant diseases. So, we propose using deep learning techniques that are involved in the detection of diseases in their very early stages, using defined techniques to classify image databases. Finally, a classification technique is used to specify the type of plant leaf disease. The predicted technique successfully diagnoses the illness and accurately categorizes the plants leaf illness when compared to CNN models.
Title: Diagnosis of Chronic Kidney Disease Using Machine Learning and Deep Learning Algorithms
Abstract: To overcome the difficulties facing in the existing, we propose a system to use to data to perform analysis using four different classifications algorithms and deep learning on CT scans to detect Chronic kidney disease and also compare their result to determine the best algorithm to use for Chronic kidney disease. First Step pre-processing, we dealt with missing values by replacing them with mean values and Standardize features using Standard Scalar. Second Step is training the model using the different machine learning algorithms. Next is Testing We test the models using different metric such as (F1 score, accuracy, Recall, Precision, etc). In deep learning we pre-process the images by turning them into numpy arrays and using deep learning techniques on them
Title: An Efficient Ensemble Classifier to Predict the Risk Levels Of Cardio Vascular and Ckd Problems from Type-3 Diabetes
Abstract: After a century of medical progress, people nowadays live longer with diabetes than ever before. However, current preventative approaches, compounded in part by increased life-expectancy, are failing to reduce the prevalence of diabetes. Cardiovascular and CKD sequel account for many of the four million deaths annually attributable to diabetes. Evidence indicates that certain glucose-lowering medications can improve those problems outcomes in some people with type 3 diabetes, which, together with better understanding of using multiple therapies concurrently, offers opportunities for beneficial personalization of medication regimens. The proposed research work are going to predict the chances of the damage occurred in cardio and CKD based on the patient diabetes symptoms and performing the performance analysis for proposed ensemble classifier to other machine learning models.
Title: Crop Prediction Based on Soil Types using Machine Learning and Deep Learning Techniques
Abstract: This research focus on various soil types to understand which crops grow better in certain soil types. Machine and Deep learning techniques can be helpful in this case. Machine learning is still an emerging and challenging research field in agricultural data analysis. In this project, a model was proposed that can predict soil series with and type and according to prediction it can suggest suitable crops.
Title: A Novel Framework to Detect the Brain Disorder for Tumours using Machine Learning on MR Images
Abstract: The rapid growth in the medical image analysis domain is encouraging the researchers to look forward for the improvement in disease detection. Numerous research attempts are being made to enhance the detection of diseases based on the manual data accumulation from the magnetic resonance (MR) images and processing the data further to generate subsequent analysable reports for prediction and detection of syndromes related to human brain. Nevertheless, the approaches are prone to errors as the first level analysis is made manually and then the gathered data is analysed again, finally resulting into a questionable outcome. Thus, the demand from the modern research is to make the analysis and detection of brain tumour automatic, which is accurate and timely. Henceforth, this work proposes a novel framework to analyse and detect brain tumours from MR Images and subsequently deploy a predictive sub framework to detect the probable diseases may cause to the subject (Patient).
Title: Predictive Maintenance for Machines and Industrial Equipments
Abstract: We often come across requirements in product development that need to analyze, interpret predict or transform data coming from various sources in the business. Most of the manufacturing industries will use high cost equipments foe their products manufacturing purposes. The impact of a failure cannot be afforded and will suspend the production. To avoid this huge loss, the machine is subjected to preventive maintenance, which involves periodic inspection and repair, often scheduled based on time-in-service. The challenge of proper scheduling grows with the complexity of machines: in a system with many components working together and influencing each other’s lifetime. The aim of predictive maintenance is to build models that quantify the risk of failure for a machine in any moment in time and use this information to improve scheduling of maintenance.
The success of predictive maintenance models depend on three main components: having the right data available, framing the problem appropriately and evaluating the predictions properly. This project will give insights on how to choose the modeling technique that best fits to analyze machine daily usage, life span and predicts the certain breakpoints to be noticed.
- Life Member of Indian Society for Technical Education (ISTE) – LM-123938
- Life Member of International Association of Engineers (IAENG)- Member No: 65382
- Member of IEEE and ACM Digital Library
FDP's/ Workshops:
S. No | Title | Patent Application No | Date of Filed | Date of Published | Date of Granted | Status | Country |
1 | Weighted Coupling Support (WCS): A Metric to Predict the Fault Proneness of Object-Oriented Application | 201941042760 A | 22.10.2019 | 29.11.2019 | – | Published | India |
2 | Search based Binary Classification for Web Attacks Detection | 201941042764 A | 22.10.2019 | 29.11.2019 | – | Published | India |
3 | Automated Real-Time Driving Behavioural Modelling Analysis And Reporting In Denser Traffic Using Data Mining | 2020101738 | 10.08.2020 | 02.09.2020 | 02.09.2020 | Granted | Australia |
4 | Display connecting device for identification of data malfunction | 332996-001 | 09-09-2020 | 20-10-2021 | – | Published | India |
5 | A Framework with Augmented Reality Using AI for improving Teaching Pedagogy in Educational Institutions | 202014011570 | 18 Mar 2021 | 26 Mar 2021 | – | Published | India |
- Best Faculty for implementing Innovative Teaching Practices by VEDIC- 2020.
- Ratified as an Associate Professor by JNTUH on February, 2018.
- Ratified as an Assistant Professor by JNTUH on June, 2012.
- Qualified Faculty Eligibility Test (FET) -2010.
- Qualified GATE-2006.
- Organizing Committee member for AICTE Sponsored one week Online Short Term Training Programme on IoT based Green Energy systems from 14th to 19th September, 2020 organized by Department of CSE, BVRIT.
- Coordinator for One Week Online Faculty Development Program on “Machine Learning with Python (Hands-on)” from 15th-20th June, 2020 organized by Department of CSE, BVRIT.
- Organizing Committee member for International Conference on Computational & Experimental Methods for Advancing Engineering Systems Applications (ICCEAESA – 2019) on 23rd August, 2019 organized by BVRIT.
- Organizing Committee member for National Level Faculty Development Program Indian Cyber Congress (INCYCON – 2019), 26th& 27thApril, 2019 organized by BVRIT.
- Coordinator for One Week Workshop on “Internet of Things (Hands-on)” from 17th to 22nd July, 2017 in association with IIT Varanasi (BHU) organized by Department of CSE, BVRIT.
- Organizing Committee member for International Conference on Research Advancements in Computer Science and Communication- 2016 (ICRACSC-2016), Organized by the Departments of CSE & IT, on 29th & 30th December 2016.
- Coordinator for International Conference on Innovations in Computing and Communication (ICICC 2015) from 12th to 13th February, 2015 organized by Department of CSE, BVRIT.
- Organizing Committee member for Two Day Faculty Development Program on “Data Mining – Tools & Research Issues” during 16th -17th May, 2014 organized by Department of CSE, BVRIT.
- Attended Online Short Term Training Programme on “Cyber Security & Block-Chain Technologies” organized by Department of Computer Science Engineering, GNITC from 26th to 31st October, 2020.
- Attended Online Short Term Training Programme on “IoT based Green Energy Systems.” organized by Department of Computer Science Engineering, BVRIT from 14th to 19th September, 2020.
- Participated in a Faculty Development Program on AI & Deep Learning held from 17thto 28thAugust, 2020 by TASK in association with 360DigiTMG, India.
- Participated in One Week Online Faculty Development Program on “Machine Learning with Python (Hands-on)” from 15th to 20thJune, 2020at BVRIT, Narsapur.
- Participated 5 Days online “Hands on FDP: Data Science Using Python” from 18th to 22nd May, 2020 at Jeppiaar Institute of Technology, Sriperumbudur.
- Participated in a 5-Day-National Level Online Faculty Development Program on “ARTIFICIALINTELLIGENCE” from 22nd to 26th May, 2020 organized by Department of CSE & IT, BVRITH inassociation with NYCI &Brainovision Solutions India Pvt.
- Attended three-day workshop on “Inspire – Impact – Introspect (III), Level-2″ from 28-01-2020 to 30-01-2020 at VEDIC, Aziz Nagar.
- Attended two weeks National Level FDP on “Cyber Security, Crypt Analisys and Security for Physical Infrastructure” under DST-ICPS Division from 09th to 20th December, 2019 organized by Department of CSE, Gurunanak Institutions Technical Campus (GNITC), Hyderabad.
- Attended the ‘Associate Analytics -Train – the – Trainer Program along with TVET” during 18th to 24th November 2019 at VEDIC, Hyderabad.
- Attended 3-days workshop on “Inspire – Impact – Introspect (III)” from 22nd to 24th October, 2019 at VEDIC, Aziz Nagar.”
- Attended 3-days workshop on “Machine Learning with Python” from 25th to 27th September,2019 at BVRIT, Narsapur.
- Attended one-week FDP on “Internet of Things” conducted by E&ICT academy in association with NIT Warangal from 26th to 31st August, 2019 at BVRIT, Narsapur.
- Attended one-week FDP on “Introduction to Python Programming” in association with Microsoft-MTA from 17th-24th April,2019 organized by Department of IT, BVRIT.
- Attended a 3-Day workshop on “Artificial Intelligence and Deep Learning”, In association with Bennett University during 24th – 26th November 2018 at BVRIT, Narsapur.
- Successfully completed, AICTE – ISTE sponsored “Refresher Course on Programming, Data Structures and Algorithms implementation using Python” from 16th July 2018 to 21st July 2018 at BVRIT, Narsapur.
- Attended Faculty Development Program on “CLOUD COMPUTING” organized by Department CSE, BVRIT, Narsapur association with E&ICT-NIT Warangal from 29th March to 03rd April 2018.
- Attended the ‘Data Analytics-Train – the – Trainer Program” during 20 – 24 Mar’ 2018 at VEDIC. The program was organised by Sri Vishnu Educational Society (SVES), Punjagutta, Hyderabad in collaboration with IT-ITeS Sector Skills Council NASSCOM.
- Attended a One Week FDP on “Teaching Methodologies” on 28th November to 3rd December, 2016 at CMRCET, Hyderabad.
- Attended a 2-day Workshop on “Microsoft Windows Azure” on 4th & 5th March 2016 at BVRIT, Hyderabad.
- Participated in a Guest Lecture on “Green Optical Access and Metro Integration: from lab to Pan-Europen testing”, conducted on 7th January, 2016 at BVRIT, Narsapur.
- Attended One Week National Level Workshop on “Big Data Analytics” from 14th-20th December, 2015 at JNTUH College of Engineering, Jagitial.
- Attended a 3-Day workshop on “IBM- Blue Mix Enablement Session” from 06th – 08th May, 2015 at BVRIT, Narsapur.
- Attend a 21 days training program on “Windows Technologies” from 5th April, 2015 to 26th April, 2015 at BVRIT, Hyderabad.
- Attended a 2-day Workshop on “Data Science using R-Programming” on 25th & 26th March 2015 at BVRIT, Narsapur.
- Attended a One Week short term training program on “Emerging Trends in Speech Signal Processing” from 15th -19th January, 2015 at IIT, Pune.
- Attended a One Week FDP on “Research Trends in Computer Science and Engineering” from 5th to 11th January, 2015 at Vardhaman College of Engineering, Hyderabad.
- Attended a National Conference on “Recent Research Advancements in Information Technology (NCRRAIT-2014)” on 25th & 26th September 2014 Conducted by Department of IT, BVRIT.
- Attended FDP on “Data Mining Tools and Research Issues” from 16th -17th May, 2014 conducted by Department of CSE, BVRIT.
- Attended audit course on “Research Methodologies” from 01-05-2014 to 15-05-2014 conducted by R & D Cell, JNTU, Kakinada.
- Attended a FDP on “Network Security & Cryptography” from 02-06-2013 to 08-06-2013 organized by Department of CSE, BVRIT
Microsoft Technology Associate:
- Introduction to Programming Using Python – Certified in 2019.
- Database Fundamentals – Certified in 2019.
Microsoft Educator:
- Certified Microsoft Innovative Educator
- MIE Trainer: Trainer academy
- Introduction to Cloud for Leaders
- Deploying Cloud-ready Classroom PCs
- Crafting a collaborative learning environment with Class Teams
- Digital Citizenship
- Engaging 21st Century Learners: Leveraging Squigl to Improve Student Engagement
- Computational Thinking and its importance in education
- Collaborate faster using Microsoft Teams for higher education staff
NPTEL (National Programme on Technology Enhanced Learning by MHRD, India)
- Design and Analysis of Algorithms
- Data Science for Engineers
Online Courses
- Completed Diploma in “Machine Learning with R studio” by Alison Online Courses.
- “Machine Learning A-Z™: Hands-On Python & R in Data Science” by UDEMY.
- “Maths for Data Science by Data Trained” by UDEMY.
Coursera Certifications:
- IBM Data Science Professional Certificate
- Python for Everybody Specialization
NASSCOM & Simplilearn Courses:
- “Foundational Artificial Intelligence” an Industry recommended & validated course aligned to SSC NASSCOM Foundation AI curriculum.
- “Big Data Foundation” course by Digital Vidya.
- “Foundations on IOT” course by JIGSAW Academy.
- Introduction to Data Analytics course by Simplilearn
- Introduction to AI course by Simplilearn
- Introduction to IoT course by Simplilearn
Name: Dr. K. Purnachand
Father Name: Sri. K. Siva Prasada Rao, Telugu Pandit (Retd.)
Marital Status: Married
Permanent Address: PLOT NO-1155, FLAT NO- 201, AYODHYA APARTMENT
PRAGATI NAGAR, BACHUPALLE, HYDERABAD-500090
TELANGANA STATE
