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Information Systems and Analytics

Pradeep Kumar Dadabada

Assistant Professor Ph.D, IDRBT,University of Hyderabad

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Email :pradeepdadabada@iimshillong.ac.in

Office Ph.: +91 364 2308027

Research Interests/ Areas

Data Science, Financial Analytics, Sustainability, Optimization, Time series Prediction

Teaching Interest / Areas

Information Systems & Analytics

  • Ph.D. (CS), Institute for Development and Research in Banking Technology (IDRBT), Hyderabad, Telangana /University of Hyderabad, Hyderabad, Telangana,2018
  • M.Tech (CSE), RVR&JC College of Engineering, Guntur, Andhra Pradesh /Acharya Nagarjuna University, Guntur, Andhra Pradesh,2008
  • M.C.A, College of Science, GITAM, Visakha Patnam , Andhra Pradesh/Andhra Univesrity, Andhra Pradesh,2005
  • Sr. Data Scientist, Innominds Software SEZ Pvt. Ltd, Hyderabad during April 2018 – May 2019.
  • Senior ML Scientist, Phenom People Pvt. Ltd., Hyderabad during October 2017 – November 2017
  • Research Scientist- Data Science, FinMee Technologies (Ntwist) Pvt. Ltd., Hyderabad during February 2017 – June 2017
  • Research Fellow, Institute for Development and Research in Banking Technology, Hyderabad during January 2012 – January 2017
  • Lecturer, R.V.R.& J.C. College of Engineering (autonomous), Chowdavaram, Guntur during August 2008 – January 2012

Research Interests

  • Data/Business Analytics, Time Series Forecasting, Machine Learning, Evolutionary Computation, Deep Learning, Natural Language Processing, Computer Vision.

Ph.D. Thesis title

  • Financial Time Series Prediction using Soft Computing Hybrids


  • Dadabada Pradeep Kumar, A Review of impact of COVID-19 on Environment from Lens of Sustainable Development Goals, International Journal of Innovation and Sustainable Development. DOI: 10.1504/IJISD.2021.10043427 (Scopus)
  • Dadabada Pradeep Kumar, Impact of COVID-19 on Society from Lens of Sustainable Development Goals, Empirical Economics Letters, 20(9): (September 2021) ISSN 1681 8997, pp. 1659-1677. (ABDC-C)
  • Dadabada Pradeep Kumar, A Review of Impact of COVID-19 on Economic Sustainability: An Exploratory Data Analysis and 3R Approach, Empirical Economics Letters, 20(8): (August 2021), ISSN 1681 8997, pp. 1457-1467. (ABDC-C)
  • Kumar D.P. (2021) Particle Swarm Optimization: The Foundation. In: Mercangöz B.A. (eds) Applying Particle Swarm Optimization. International Series in Operations Research & Management Science, vol 306. Springer, Cham. https://doi.org/10.1007/978-3-030-70281-6_6 (Book Chapter)
  • Pradeepkumar, D. and Ravi, V. (2020) ‘Financial time series prediction: an approach using motif information and neural networks’, Int. J. Data Science, Vol. 5, No. 1, pp.79–109.
  • Dadabada Pradeepkumar, Vadlamani Ravi, Soft computing hybrids for FOREX rate prediction: A comprehensive review, Computers & Operations Research, Volume 99, 2018, Pages 262-284, ISSN 0305-0548, https://doi.org/10.1016/j.cor.2018.05.020 (ABDC-A)
  • Vadlamani Ravi, Dadabada Pradeepkumar, Kalyanmoy Deb, Financial time series prediction using hybrids of chaos theory, multi-layer perceptron and multi-objective evolutionary algorithms, Swarm and Evolutionary Computation, Volume 36, 2017, Pages 136-149, ISSN 2210-6502, https://doi.org/10.1016/j.swevo.2017.05.003
  • Dadabada Pradeepkumar, Vadlamani Ravi, Forecasting financial time series volatility using Particle Swarm Optimization trained Quantile Regression Neural Network, Applied Soft Computing, Volume 58, 2017, Pages 35-52, ISSN 1568-4946, https://doi.org/10.1016/j.asoc.2017.04.014 (ABDC-C)
  • Pradeepkumar D., Ravi V. (2017) FOREX Rate Prediction: A Hybrid Approach Using Chaos Theory and Multivariate Adaptive Regression Splines. In: Satapathy S., Bhateja V., Udgata S., Pattnaik P. (eds) Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications. Advances in Intelligent Systems and Computing, vol 515. Springer, Singapore. https://doi.org/10.1007/978-981-10-3153-3_22  (Conference Publication)
  • Pradeepkumar D., Bhunwal M., Ravi V. (2015) A Novel Hybrid Algorithm for Discovering Motifs from Financial Time Series. In: Panigrahi B., Suganthan P., Das S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science, vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_18 (Conference Publication)
  • Pradeepkumar D., Ravi V. (2014) FOREX Rate Prediction Using Chaos, Neural Network and Particle Swarm Optimization. In: Tan Y., Shi Y., Coello C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_42 (Conference Publication)
  • Pradeepkumar and V. Ravi, “FOREX Rate prediction using Chaos and Quantile Regression Random Forest,” 2016 3rd International Conference on Recent Advances in Information Technology (RAIT), 2016, pp. 517-522, doi: 10.1109/RAIT.2016.7507954 . (Conference Publication)
  • “Paper Development Workshop” on 23-May-2022 co-hosted by AIS India Chapter and IIM Kashipur
  • “5-Days online workshop on Comprehensive time series forecasting” during 6-10 June, 2022
  • “5-Days online weekend workshop on Comprehensive time series forecasting-Batch 2” during 27-28 August and 3-4, 10 September,2022
  • Trained nearly 50+ aspiring data scientists at institutes such as Imarticus Learning and Silicon Guru, Hyderabad.
  • Trained various bank managers and various levels of bank employees in customized programs in CRM & Analytics at IDRBT, Hyderabad.
  • Recognized as one of “The Top 10 most prominent data analytics and data science academicians 2019” by Analytics Magazine India
  • MHRD Fellowship for conducting research at IDRBT from January 2012- January 2017
  • UGC-NET (Lectureship) in December 2012
  • Best Active participant in MATLAB Workshop conducted by NITW in Aug 2013
  • AICTE fellowship for pursuing M.Tech (CSE) from August 2006- May 2008