I am a principal AI scientist at Shell and a part-time professor of computer science at Delft University of Technology (TU Delft) with a track record of innovation and stakeholder management in both industry and academia. Over the years, I have made fundamental contributions to Shell's affinity and adoption of AI based solutions, leading the development of some of its largest deep learning and computer vision based products for asset maintenance, safety, surveillance, and renewable energy forecasting and optimization. I am passionate about further advancing the frontiers of research on deep learning and computer vision as well as their applications in our day-to-day lives. I obtained my PhD in statistical learning and distributed optimization (Cum Laude) under supervision of Prof. Geert Leus from the Delft University of Technology (TU Delft) in 2014. During my PhD, I visited CSIP at Georgia Tech (supervised by Prof. Xiaoli Ma), and STADIUS at KU Leuven (supervised by Prof. Marc Moonen and Prof. Toon van Waterschoot).  For more details about my research interests and expertise, read on! 

Research Interest:

Deep Learning and Computer Vision 

• Generative AI

• Self-Supervised Learning

• Few-Shot Land Meta Learning

• Federated Learning (FL) & Distributed Optimization

• Graph Neural Networks (GNNs)

Honors & Awards:

• Joined European Laboratory for Learning and Intelligent Systems (ELLIS), Feb 2024. 

• My project Spatio-Temporal Deep Learning for Solar Forecasting (STELLAR) won the Shell.ai Award, Oct. 2023.

• Our paper is amongst the finalists for the Best Paper Award at WACV 2023 (~top 1%) [Announcement]

• My Project Biofuel Visual Remote Sensing (BioVERS) won the Shell.ai Award, Sep. 2022. 

• My Project Autonomous Integrity Recognition (AIR) won the Shell.ai Award, Nov. 2021 [Public Announcement]. 

• Won the Best Paper Award at the ICLR DPML 2021, May 2021.  

• Elevated to IEEE Senior Member grade, June 2020. 

• Won Digitalization and Computational Sciences Award for my project on “Autonomous Integrity Recognition”, Shell, August 2019.

• Won Vice President Subsurface Technologies Award for my project on “Machine Learning for Seismicity Prediction”, Shell, July 2019.

• Won Shell.ai Award, top AI recognition, for my project on “Continuous Subsurface Tomography with Wireless IoT”,  Shell, March 2019.

• Received Cum Laude (university-wide top 1%) for PhD dissertation, on “Sparsity-Aware Wireless Networks”, TU Delft, December 2014.

• Won European Erasmus Grant for visiting STADIUS, KU Leuven, November 2012. 

News:

• I've joined European Laboratory for Learning and Intelligent Systems (ELLIS), Feb 2024!

• I'm reviewing for ECCV 2024. 

• Our paper "BECLR: Batch Enhanced Contrastive Unsupervised Few-Shot Learning" is accepted at ICLR 2024 (Spotlight - top 5%).  

• I'm serving as Area Chair (AC) for NeurIPS workshop on "R0-FoMo: Robustness of Few-shot and Zero-shot Learning in Foundation Models", 2024.  

• I'm reviewing for ICLR 2024.

• I'm reviewing for Transactions on Machine Learning Research (TMLR), starting Oct. 2023 and going forward.  

• [ICCV Workshop Accepted!] I'll be co-organizing  4th Edition of Visual Inductive Priors (VIPriors) at ICCV, in Oct. 2023. 

• I'll be co-organizing Netherlands Conference on Computer Vision (NCCV), in Sep. 2023.

• I have an exciting PhD position on Self-Supervised Deep Learning and Computer Vision (deadline: March 24th 2023).

• I'm reviewing for ICCV 2023. 

• New preprint available: "Transductive Decoupled Variational Inference for Few-Shot Classification". [arxiv][code]

• Two papers accepted to appear in WACV 2023. See publications page!

• Our paper "Self-Supervised Class-Cognizant Few-Shot Classification", is accepted in IEEE ICIP, 2022. [arxiv][code]

• Our paper "Federated Learning with Taskonomy for Non-IID Data" has appeared in IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), March, 2022. [paper][supplementary] 

• Our US/EU patent has been finally awarded, Oct 2021!

• I'm reviewing for AAAI 2021, AISTATS 2022 and CVPR 2022. 

• Our paper "Lookahead Adversarial Learning for Near Real-Time Semantic Segmentation" is accepted to appear in Computer Vision and Image Understanding (CVIU), Elsevier, August 2021 [Paper].

• Our paper "Federated Learning with Taskonomy" has won the Best Paper Award at the ICLR DPML 2021! [award certificate]

• Our paper entitled “Tilted Cross-Entropy (TCE): Promoting Fairness in Semantic Segmentation” is accepted at CVPRW 2021 [arxiv].

• Our paper "Federated Learning with Taskonomy" is accepted at ICLR DPML 2021 (Contributed Talk) [paper] [slides].

• I'll be co-instructing (with Dr. Justin Dauwels) Machine Learning, A Bayesian Perspective, TU Delft, Q3 2020-21 (excerpt of Student Feedback).

• I'm reviewing for ICCV 2021. 

• I'm reviewing for AAAI 2021 and AISTATS 2021. 

• I am elevated to IEEE Senior Member grade, June 2020! 

• Our paper entitled “Continuous Subsurface Tomography over the Cellular Internet of Things”, accepted to appear in IEEE Sensors Journal, 2020 [preprint].