Professional( Teaching/Research) Experience:

1.   Assistant Professor, NIT AP (November 2019 to till date)
2.  Ad-hoc faculty, NITAP(July 2017 to November 2019)
3. Three years of research experience (July 2014 to June 2017)
4. AssistantProfessor, SNIST Hyderabad (Dec 2012-June 2014).

Course Taught:

1. Basic Electrical Engineering

2. Circuit Theory-I

3. Circuit Theory-II

4.  Network Analysis

5. Power Systems-II

6. Digital Signal Processing 

7. Soft Computing Techniques

Research Publications

Refereed Journals:

1. Kiran Teeparthi and D.M. Vinod Kumar, “Security constrained optimal power flow with wind and thermal power generators using fuzzy adaptive artificial physics optimization algorithm”, Neural Computing and Applications, Springer, Vol: 29, Pg. nos:855–871 (2018). (DOI: 10.1007/s00521-016-2476)  (SCIE, Q1-Impact factor: 6.0)
2. Kiran Teeparthi and D.M. Vinod Kumar, “Multi-Objective Hybrid PSO-APO Algorithm based Security Constrained Optimal Power Flow with Wind and Thermal Generators”, Engineering Science and Technology, an International Journal, Elsevier, Vol: 20, Pg. nos:411–426 (2017). (DOI: 10.1016/j.jestch.2017.03.002) (SCIE, Q1-Impact factor: 5.7)
3. Kiran Teeparthi and D.M. Vinod Kumar, “Dynamic security assessment and enhancement using a new hybrid PSO-APO algorithm”, Engineering, Technology & Applied Science Research, Vol: 7, Pg. nos:2124–2131 (2017). (DOI: 10.48084/etasr.1477) (ESCI)
4. Kiran Teeparthi and D.M. Vinod Kumar, “Power System Security Assessment and Enhancement: A Bibliographical Survey”, Institution of Engineers (India): Series B, Springer, Vol: 101, Pg. nos:163–176 (2020). (DOI: 10.1007/s40031-020-00440-1) (SCOPUS)
5. Kiran Teeparthi and D.M. Vinod Kumar, “An Improved Artificial Physics Optimization Algorithm Approach for Static Power System Security Analysis”, Institution of Engineers (India): Series B, Springer, Vol: 101, Pg. nos: 347–359 (2020). (DOI: 10.1007/s40031-020-00457-6) (SCOPUS)
6. Sreenadh Batchu and Kiran Teeparthi, "A Preventive Transient Stability Control Strategy Through Individual Machine Equal Area Criterion Framework," in IEEE Access, vol. 9, pp. 167776-167794, 2021. (DOI: 10.1109/ACCESS.2021.3136593) (SCIE, Q1-Impact factor: 3.367) (Supervisor, Corresponding Author)
7. Vishalteja Kosana, Santhosh M, Kiran Teeparthi, " A novel hybrid deep learning framework for wind speed forecasting using autoencoder based convolutional long short-term memory neural network”, International Transactions on Electrical Energy Systems, Wiley, Vol: 31, 2021. (DOI: https://doi.org/10.1002/2050-7038.13072) (SCIE, Q2-Impact factor: 2.639) (Supervisor)
8. Vishalteja Kosana, Kiran Teeparthi, Santhosh Madasthu, Santosh Kumar, "A novel reinforced online model selection using Q-learning technique for wind speed prediction", Sustainable Energy Technologies and Assessments, Elsevier, Volume 49, 2022.  (DOI:https://doi.org/10.1016/j.seta.2021.101780). (SCIE, Q1-Impact factor: 8.0) (Supervisor)
9. Vishalteja Kosana, Kiran Teeparthi, Santhosh Madasthu, "Hybrid wind speed prediction framework using data pre-processing strategy based autoencoder network", Electric Power Systems Research,  Elsevier, Volume 206, 2022. (DOI: https://doi.org/10.1016/j.epsr.2022.107821) (SCIE, Q1-Impact factor: 3.9) (Supervisor, Corresponding Author)
10. Kosana V., Kiran Teeparthi,  & Madasthu S, "Hybrid convolutional Bi-LSTM autoencoder framework for short-term wind speed prediction", Neural Computing and Applications, Springer, 2022. (DOI: https://doi.org/10.1007/s00521-022-07125-4) (SCIE, Q1-Impact factor: 6.0) (Supervisor, Corresponding Author)
11. Vishalteja Kosana, Santhosh Madasthu,  Kiran Teeparthi, Santosh Kumar, "A novel dynamic selection approach using on-policy SARSA algorithm for accurate wind speed prediction," Electric Power Systems Research,  Elsevier, Vol. 212, 2022.  (DOI:https://doi.org/10.1016/j.epsr.2022.108174). (SCIE, Q1-Impact factor: 3.9) (Supervisor, Corresponding Author)
12. Sreenadh Batchu and Kiran Teeparthi, "Transient Stability Enhancement Through Individual Machine Equal Area Criterion Framework Using an Optimal Power Flow" in IEEE Access, vol. 10, pp. 149433 - 49444, 2022. (DOI: 10.1109/ACCESS.2022.3173422) (SCIE, Q1-Impact factor: 3.367) (Supervisor, Corresponding Author)
13. Sreenadh Batchu and Kiran Teeparthi, "A new method for operating point free power system transient stability situational awareness based on single machine equivalent approach" Engineering Reports, Wiley, 2022. (DOI: https://doi.org/10.1002/eng2.12519) (ESCI) (Supervisor)
14. Vishalteja Kosana, Kiran Teeparthi, and Santhosh Madasthu, "A novel and hybrid framework based on generative adversarial network and temporal convolutional approach for wind speed prediction", Sustainable Energy Technologies and Assessments, Elsevier, Volume 53, 2022.  (DOI:https://doi.org/10.1016/j.seta.2022.102467). (SCIE, Q1-Impact factor: 8.0) (Supervisor, Corresponding Author)
15. Y.Raghuvamsi, Kiran Teeparthi, and Vishalteja Kosana, "A novel deep learning architecture for distribution system topology identification with missing PMU measurements", Results in Engineering,  Elsevier, Vol. 15 ,2022.  (DOI:https://doi.org/10.1016/j.rineng.2022.100543). (ESCI, Q1) (Supervisor, Corresponding Author)
16. Bala Saibabu Bommidi, V Kosana, Kiran Teeparthi, and S Madasthu, "Hybrid attention-based temporal convolutional bidirectional LSTM approach for wind speed interval prediction", Environmental Science and Pollution Research,  Springer, 2023.  (DOI:https://doi.org/10.1007/s11356-022-24641-x). (SCIE, Q1-Impact factor: 5.190) (Supervisor, Corresponding Author)
17. Bala Saibabu Bommidi, Kiran Teeparthi, and Vishalteja Kosana, "Hybrid wind speed forecasting using ICEEMDAN and transformer model with novel loss function", Energy,  Elsevier, Vol. 265, 2023.  (DOI:https://doi.org/10.1016/j.energy.2022.126383). (SCIE, Q1-Impact factor: 9.0) (Supervisor, Corresponding Author)
18. Y Raghuvamsi and Kiran Teeparthi, "Detection and reconstruction of measurements against false data injection and DoS attacks in distribution system state estimation: A deep learning approach", Measurement,  Elsevier, Vol. 210, 2023.  (DOI:https://doi.org/10.1016/j.measurement.2023.112565). (SCIE, Q1-Impact factor: 5.6) (Supervisor, Corresponding Author)
19. Y. Raghuvamsi, Dr. Kiran Teeparthi, Vishalteja kosana, “Denoising Autoencoder based Topology Identification in Distribution Systems with Missing Measurements,” International Journal of Electrical Power & Energy Systems, Elsevier, vol.154, pp. 109464, 2023, doi:10.1016/j.ijepes.2023.109464 - SCIE, Q1, IF: 5.2. (Supervisor, Corresponding Author)
20. Y. Raghuvamsi, Kiran Teeparthi, “A Review on Distribution System State Estimation Uncertainty Issues using Deep Learning Approaches,” Renewable and Sustainable Energy Reviews, Elsevier, vol. 187, pp. 113752, 2023, doi:10.1016/j.rser.2023.113752- SCIE, Q1, IF: 15.9. (Supervisor, Corresponding Author)
21. Srihari Parri, Kiran Teeparthi, Vishalteja Kosana, “A hybrid VMD based contextual feature representation approach for wind speed forecasting”, Renewable Energy, Volume 219, 2023, Elsevier, doi: 10.1016/j.renene.2023.119391- SCIE, Q1, IF: 8.7. (Supervisor, Corresponding Author)
22. Y. Raghuvamsi, Dr. Kiran Teeparthi, “Distribution System State Estimation with TransformerBi-LSTM based Imputation Model for Missing Measurements,” Neural Computing and Applications, Springer,2023, doi: 10.1007/s00521-023-09097-5- SCIE, Q1, IF: 6.0. (Supervisor, Corresponding Author)
23. Bala Saibabu Bommidi and Kiran Teeparthi, “A novel method for predicting wind speed using data decomposition-based reformer model”, Earth Sci Inform, Springer, 17, 227–249 (2024). https://doi.org/10.1007/s12145-023-01123-3 -SCIE, Q2, IF: 2.8 (Supervisor, Corresponding Author)
24. Srihari Parri and Kiran Teeparthi, “VMD-SCINet: A hybrid model for improved wind speed forecasting”, Earth Sci Inform, Springer, 17, 329–350 (2024). https://doi.org/10.1007/s12145-023-01169-3-SCIE, Q2, IF: 2.8 (Supervisor, Corresponding Author)
25. Bala Saibabu Bommidi and Kiran Teeparthi, ''A hybrid wind speed prediction model using improved CEEMDAN and Autoformer model with auto-correlation mechanism'‘, Sustainable Energy Technologies and Assessments, Elsevier, Volume 64, https://doi.org/10.1016/j.seta.2024.103687-SCIE, Q1, IF: 8.0 (Supervisor, Corresponding Author).
26. Y Raghuvamsi and Kiran Teeparthi, "Distribution system state estimation with Transformer-Bi-LSTM-based imputation model for missing measurements”, Neural Computing and Applications, Springer, 36, 1295–1312 (2024). https://doi.org/10.1007/s00521-023-09097-5-SCIE, Q1, IF: 6.0. (Supervisor, Corresponding Author)
27. Srihari Parri, Kiran Teeparthi, Vishalteja Kosana, ''A hybrid methodology using VMD and disentangled features for wind speed forecasting'', Energy, Elsevier, Volume 288, 2024, https://doi.org/10.1016/j.energy.2023.129824-SCIE, Q1, IF: 9.0. (Supervisor, Corresponding Author)
28. Srihari Parri and Kiran Teeparthi, “SVMD-TF-QS: An efficient and novel hybrid methodology for the wind speed prediction”, Expert Systems with Applications, Elsevier,  Volume 249, 2024, https://doi.org/10.1016/j.eswa.2024.123516-SCIE, Q1, IF: 8.5. (Supervisor, Corresponding Author)

National/ International Conferences:

1.  Kiran Teeparthi and D.M. Vinod Kumar, “Grey wolf optimization algorithm based dynamic security constrained optimal power flow”, IEEE19thNational Power System Conference (NPSC-2016), IIT Bhubaneswar,19-21Dec-2016, pp.1-6.
2. Kiran Teeparthi and D.M. Vinod Kumar, “Dynamic security enhancement using an improved artificial physics optimization method”, National Systems Conference (NSC-2016), NITWarangal, 4-6Nov2016, pp. 1-6.
3. Vishal K and Kiran Teeparthi, “Efficient Epileptic seizure prediction based on IoT and machine learning methods”, International conf. on Distributed Computing and Internet tech. (11^th student research symposium 2021),KIITBhubaneswar,7-10 January 2021. (Supervisor)
4. Sreenadh Batchu, Raghuvamsi Yarlagadda, and Kiran Teeparthi, "An intelligent system design and analysis for transient stability assessment using four sample input feature vector approach", IEEE International Conference on Intelligent Systems, Smart and Green Technologies (ICISSGT), 2021, IEEE Vizag Bay Section. (Supervisor)

5.  Vishalteja Kosana, Santhosh M, Kiran Teeparthi, A hybrid wind speed forecasting model using complete ensemble empirical decomposition with adaptive noise and convolutional support vector machine”, 9th IEEE International Conference on Power Systems (ICPS), 2021, IIT Kharagpur. (Supervisor)

6. Y.Raghuvamsi, Vishalteja Kosana, Kiran Teeparthi, “Power System State Estimation and Forecasting using CNN based Hybrid Deep Learning Models”, IEEE International Conference on Technology, Research, and Innovation for BEtterment of Society (TRIBES – 2021), IIIT Naya Raipur. (Supervisor)

7. MJV Sai Ratna Kumar, Kiran Teeparthi, Sreenadh Batchu, "A Search Space Reduction Algorithm Applied for Transient Stability Constrained Optimal Power Flow”, IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), 2022. (Supervisor)
8. Nimushakavi Syam Manohar, Kiran Teeparthi, Sreenadh Batchu, "Improved Grasshopper Optimization Framework for Optimal Power flow Considering Multi Objective Functions”, IEEE 3rd Global Conference for Advancement in Technology (GCAT), 2022. (Supervisor)
9. Y.Raghuvamsi, Sreenadh Batchu, Kiran Teeparthi, “Physics-guided Deep Learning for Branch Current Distribution System State Estimation”, IEEE 22nd National Power System Conference (NPSC-2022), IIT Delhi,17-19 Dec-2022, pp.1-6. (Supervisor)
10.  Sreenadh Batchu, Y.Raghuvamsi, Kiran Teeparthi, “A Comparative Study on Equal Area Criterion Based Methods for Transient Stability Assessment in Power Systems”, IEEE 22nd National Power System Conference (NPSC-2022), IIT Delhi, 17-19 Dec-2022, pp.1-6. (Supervisor) (Supervisor)
11. Bala Saibabu Bommidi, V Kosana, Kiran Teeparthi, Santhosh Madasthu,  “A hybrid approach to ultra short-term wind speed prediction using CEEMDAN and Informer”, IEEE 22nd National Power System Conference (NPSC-2022), IIT Delhi, 17-19 Dec-2022, pp.1-6. (Supervisor)
12. Srihari Parri, V Kosana, Kiran Teeparthi,  “A hybrid GAN based autoencoder approach with attention mechanism for wind speed prediction”, IEEE 22nd National Power System Conference (NPSC- 2022), IIT Delhi, 17-19 Dec-2022, pp.1-6. (Supervisor)
13. S. Maddineni, S. Janapati, V. Kosana and Kiran Teeparthi, "A hybrid deep transformer model for epileptic seizure prediction," International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC), Bhubaneswar, India, 2022, pp. 1-6, doi: 10.1109/ASSIC55218.2022.10088398.
14. Bommidi, B.S., Kosana, V., Kiran Teeparthi, Madasthu, S. (2023). A Novel Wind Speed Forecasting Framework Using Data Preprocessing Based Adversarial Approach. In: Doolla, S., Rather, Z.H., Ramadesigan, V. (eds) Advances in Clean Energy and Sustainability. ICAER 2022. Green Energy and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-99-2279-6_49. (Supervisor)
15. Y.Raghuvamsi, Kiran Teeparthi, and Sreenadh Batchu “Missing Data Imputation Using Transformer Model for Distribution System State Estimation,” 23rd International Conference on Control, Automation and Systems (ICCAS), Korea, 2023. (Supervisor)

16. Sreenadh Batchu, Kiran Teeparthi, “An Empirical Study on Missing Data Imputation Techniques for Transient Stability Assessment Using Four Sample Frequency Features Data set,” IEEE 3rd International Conference on Emerging Techniques in Computational Intelligence (ICETCI), Hyderabad, India, 2023. (Supervisor)

17. Sreenadh Batchu, Kiran Teeparthi, “Transient Stability Assessment and Enhancement in the Realm of Power System Dynamic Security Analysis: A Review and Scope of Methods,” IEEE 4th Global Conference for Advancement in Technology (GCAT),  Banglore, India, 2023. (Supervisor)

18. A. Y. Mudiminchi, Kiran Teeparthi,, A. Mastanaiah and S. Kolipaka, "An Intelligent Deep Reinforcement Learning Control for DC-DC Power Buck Converter Feeding a Constant Power Load,"  IEEE 3rd International Conference on Sustainable Energy and Future Electric Transportation (SEFET), Bhubaneswar, India, 2023, pp. 1-4, doi: 10.1109/SeFeT57834.2023.10245391. (Supervisor)
19. S. Kolipaka, Kiran Teeparthi, and A. Yadav Mudiminchi, "Robust Type-2 Fuzzy Controller for DC-DC Power Converter Feeding Constant Power Load," 3rd International Conference on Intelligent Technologies (CONIT), Hubli, India, 2023, pp. 1-5, doi: 10.1109/CONIT59222.2023.10205867. (Supervisor)

Ph.D. Supervision (Ongoing): 05

Workshop/Faculty Development Programme organized:

1. Organized Five Days Online FDP on Emerging Trends in Artificial Intelligence Methods to Power Systems, Signal Processing, and Control, by Dept. of Electrical Engineering, NIT Andhra Pradesh during 02 – 06, November 2020.
2. Organized Five Days Online FDP under AICTE Training and Learning (ATAL) Academy on Data-Driven Strategies in Smart Power System and Control -2021, by Dept. of Electrical Engineering, NIT Andhra Pradesh during 22 – 26, November 2021.

Additional Responsibilities:

1. Associate Dean, Alumni Affairs
2. Associate Dean, Student Welfare(Physical Education & Sports Activities)
3. Faculty In-charge Sports & Games
4. Coordinator, Career Development & Placements (PG)
5. Warden NIT Hostels

A Search Space Reduction Algorithm Applied for Transient Stability Constrained Optimal Power Flow