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Dr. Deepudev Shahadevan

Assistant Professor, Faculty of Mathematics and Data Science

Telephone: +971 4 6050154

Email: deepu.dev@eau.ac.ae

Dr. Deepudev is currently an Assistant Professor in the Faculty of Mathematics & Data Science and Institute of Applied Research & Technology, Emirates Aviation University. Prior to his appointment as an Assistant Professor, Dr. Deepudev worked for the Airports Authority of India for 12 years in various roles. During his tenure, he held several positions as Manager (ATM-specialist) in a Research and Development centre, Licensed Air Traffic Controller in various international airports, Instructor in Air Traffic Management, Airport Safety Officer, Airside Operation Management and made significant contributions to research and development activities in the aviation field as a data scientist. He served as advisor member in ICAO Air Traffic Management Requirements and Performance Panel (ATMRPP). Prior to joining AAI, Dr. Deepudev served the Indian Space Research Organisation (ISRO). He was a team member on the first moon mission by ISRO.

Dr. Deepudev earned a PhD in the area of Machine Learning and Air Traffic Flow Management from the National Institute of Technology (NIT) Tiruchirappalli, India, and a Master of Technology (M.Tech) in Signal Processing at the College of Engineering Trivandrum(CET), India. His doctoral thesis is on "Performance Improvement of Air Traffic Flow Management and 4D-Trajectory Prediction Using Machine Learning". He has published many international journals in the aviation and machine learning domains. His research interests are application research in the aviation domain, Data Science, Machine Learning, Artificial Intelligence, Next generation 4D Trajectory Based Operation, Airport and Airspace Capacity Enhancement, Airline Scheduling, Airport Operations, Unmanned Aircraft System (UAS) Traffic Management (UTM), Data Mining , Data Analytics and Natural Language Processing.

  1. PhD, National Institute of Technology Tiruchirappalli (NIT-T), India, 2021.
  2. Master of Technology (M.Tech), University of Kerala, India , 2012.
  3. Bachelor of Technology (B.Tech), University of Kerala, India , 2006.
  • Artificial Intelligence
  • Machine Learning
  • Software Engineering-Computer Science
  • Air Traffic Management
  • Application research in the aviation domain
  • Machine Learning
  • Artificial Intelligence
  • Next generation 4D Trajectory Based Operation
  • Air Transport Management
  • Airport and Airspace Capacity Enhancement
  • Airline Scheduling
  • Airport Operations
  • Unmanned Aircraft System (UAS) Traffic Management (UTM)
  • Data Mining
  • Natural Language Processing
  1. Sahadevan, D.; Al Ali, H (2023). Enhancing Trajectory-Based Operations for UAVs through Hexagonal Grid Indexing: A Step towards 4D Integration of UTM and ATM. International Journal of Aviation, Aeronautics, and Aerospace, 10(2) link
  2. Sahadevan, D.; Al Ali, H.; Notman, D.; Mukandavire, Z. Optimising Airport Ground Resource Allocation for Multiple Aircraft Using Machine Learning-Based Arrival Time Prediction. Aerospace 2023, 10, 509. Link
  3. Sahadevan D, Al Ali H, and Mukandavire Z, Airports Ground Operation Resource Optimisation Based on Arrival Time Prediction using Machine Learning, In: Proceedings of the 4th International Aviation Management Conference (Eds. H. Al Ali and Z. Mukandavire), IAMC-2022, Emirates Aviation University, Dubai, UAE, 21 – 22 November 2022, pp. 261-271, 2022. Link
  4. Deepudev Sahadevan, Palanisamy Ponnusamy, Varun P. Gopi and Manjunath K. Nelli. "Ground-based 4d trajectory prediction using bi-directional LSTM networks.", (2022), Applied Intelligence, Springer: 1-18. doi: https://doi.org/10.1007/s10489-022-03309-6
  5. Deepudev Sahadevan, Palanisamy Ponnusamy, Varun P. Gopi, Shivkumar Guruswami, and Adithya K. Krishna. "A machine learning-based approach to predict random variation in the landing time of scheduled flights.", (2021), International Journal of Sustainable Aviation 7, no. 4: 293-318. doi:https://doi.org/10.1504/IJSA.2021.119689
  6. Deepudev Sahadevan, Palanisamy Ponnusamy Dr, Manjunath K. Nelli Mr, and Varun P. Gopi Dr. "Predictability improvement of Scheduled Flights Departure Time Variation using Supervised Machine Learning.", (2021), International Journal of Aviation, Aeronautics, and Aerospace 8, no. 2: 9.doi: https://doi.org/10.15394/ijaaa.2021.1586
  7. Deepudev Sahadevan, Palanisamy P Dr, Varun P. Gopi Dr, Manjunath K. Nelli Mr, and K. Mr. "Prediction of gate in time of scheduled flights and schedule conformance using machine learning-based algorithms." (2020), International Journal of Aviation, Aeronautics, and Aerospace 7, no. 4: 9. doi:https://doi.org/10.15394/ijaaa.2020.1521
  8. Deepudev, S., P. Palanisamy, Varun P. Gopi, and Manjunath K. Nelli. "A machine learning based approach for prediction of actual landing time of scheduled flights." In Proceedings of International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, pp. 755-766. Springer, Singapore, 2021. DOI:https://doi.org/10.1007/978-981-15-7234-0_72
  9. Deepudev, S., Palanisamy, P., Gopi, V.P., Nelli, M.K., & Asokkumar, K." Performance Improvement of Air Traffic Flow Management Ground Delay Program using Machine-learning and Mixed Integer Linear Programming based Algorithm".,Deepudev, S., Palanisamy, P., Gopi, V.P., Nelli, M.K., & Asokkumar, K. (2020). Performance Improvement of Air Traffic Flow Management Ground Delay Program using Machine-learning and Mixed Integer Linear Programming based Algorithm.", International Journal on Emerging Technologies,11(2),1071-1081.
  10.   Adaptive Registration with Decentralized Kalman Filter Fusion Algorithm for Radar-ADS-B Data Fusion in Air Traffic Surveillance, (2018), Global J Technol Optim 9: 236.