I am a Senior Research Fellow in the Department of Computer Science and WEISS at UCL . Before I was a Postdoctoral Research Associate at Imperial Computer Vision and Learning Lab in Imperial College London.

I obtained a PhD from Normandie Universite, Caen, France in December 2016. My PhD was done under the supervision of Prof. Frederic Jurie. Prior to this, I was a Masters student at the department of computer science and the department of computational linguistics at Saarland University, Germany. My Master's thesis was carried out under the supervision of Prof. Ivan Titov.

Short CV:

• July 2021 - Now, Senior Research Fellow, University College London, UK

• July 2021 - Now, Visiting Researcher, Imperial College London, UK

• Dec. 2017 - July 2021, Research Associate, Imperial College London, UK

• Aug. 2016 - Dec. 2017, Data Scientist, Telenor Group, Norway

• May 2013 - Aug. 2016, PhD Student, Normandie Universite, France

Research Interests:

• Machine Learning

• Computer Vision

• Natural Language Processing

Professional Activities :

• General Co-chair Second Nepal Winter School in AI, 2019

• Program Chair First Nepal Winter School in AI, 2018

• Reviewer: IJCV (2016, 2018) , T-PAMI (2020)

CVPR (2016, 2017, 2018, 2019, 2020, 2021, 2022) , NeurIPS (2020, 2021), ICML (2021, 2022)

ICCV (2017, 2019, 2021) , ECCV (2016, 2018, 2020), ICLR (2021)

AAAI (2020, 2021), BMVC (2018, 2019, 2020, 2021) , ACCV (2018, 2020)

MVA (2016), CVIU (2019), ICPR (2020), WACV (2021, 2022)

Teaching:

• Speaker at Second Nepal Winter School in AI, Dec, 2019, Pokhara, Nepal

• Teaching Assistant, Selected Topics in Computer Vision at EEE Department, Imperial College London, 2019

• Speaker at First Nepal Winter School in AI, Dec, 2018, Kathmandu, Nepal

• Teaching Assistant, Machine Learning for Computer Vision at EEE Department, Imperial College London, 2018

Awards:

• Google Cloud Research Innovator, 2022

• Outstanding Reviewer Award, BMVC, 2021

• Winner (2K USD) FetReg Endoscopic Vision Challenge at MICCAI 2021

• 5K + 5K USD Google Cloud Platform Research Credits

• DAAD Postdoc Net-AI-Fellow, 2020 (top 22 out of 192)

• Outstanding Reviewer Award, BMVC, 2019

• Best Student Paper Award of Image, Video and Multidimensional Signal Processing, ICASSP, 2016

• Best Paper Award Runner up, ACM ICVGIP, 2016

Pre-prints:

• Caramalau, R. Bhattarai, B. and Kim, T-K Visual Transformer for Task-Aware Active Learning [Arxiv] [Code]

• Sapkota, S. Bhattarai, B. Input Invex Neural Network [Arxiv] [Code]

Publications:

• Sapkota, S. Bhattarai, B. Noisy Heuristics NAS: A Network Morphism based Neural Architecture Search using Heuristics, ICML Workshops 2022

• Sun, J. Bhattarai, B. Chen Z. and Kim, T-K SeCGAN: Parallel Conditional Generative Adversarial Networks for Face Editing via Semantic Consistency, AI for Content Creation CVPR June 2022 [pdf],

• Sapkota, S. , Khanal, B., Bhattarai*, B., Khanal, B., Kim, T-K Label Geometry Aware Discriminator for Conditional Generative Networks ICPR 2022 (Oral) [Arxiv]

• Caramalau, R. Bhattarai, B. and Kim, T-K Sequential Graph Convolutional Network for Active Learning CVPR 2021 [Arxiv] [Code]

• Lee, J., Bhattarai, B. and Kim, T-K Face Parsing from RGB and Depth Using Cross-Domain Mutual Learning AMFG CVPR 2021 [Pdf] [Code]

• Caramalau, R. Bhattarai, B. and Kim, T-K Active Learning for Bayesian 3D Hand Pose Estimation WACV 2021 [Pdf] [Code]

• Bodur R., Bhattarai, B., Kim, T-K 3D Dense Geometry-Guided Facial Expression Synthesis by Adversarial Learning WACV 2021 [Pdf][Code]

• Bhattarai, B. and Kim, T-K Inducing Optimal Attributes Representations for Conditional GANs ECCV, Aug., 2020 [pdf]

• Sun, J. Bhattarai, B. and Kim, T-K MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network ACCV Nov. 2020 [pdf], [Code]

• Ali, S., Bhattarai, B. , Kim, T-K, Rittscher, J. Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images, MLMI-MICCAI Oct . 2020 [Arxiv]

• Bhattarai, B*., Bodur R.*, Kim, T-K AugLabel: Exploiting Word Representations to Augment Labels for Face Attribute Classification, ICASSP, May, 2020 [pdf]

• Bhattarai, B., Baek, S., Bodur, R., Kim, T-K Sampling Strategies for GAN Synthetic Data, ICASSP, May, 2020, [pdf]

• Gecer, B. Bhattarai, B. Kittler, J. Kim, TK Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model In European conference on Computer Vision (ECCV), Sept. 2018, Munich Germany [pdf] [Project page]

• Bhattarai, B. Sharma, G. and Jurie, F. CP-mtML: Coupled Projection multi-task Metric Learning for Large Scale Face Retrieval CVPR, July 2016, Las Vegas, USA [pdf]

• Bhattarai, B. Sharma, G. and Jurie, F. Deep fusion of visual signatures for client-server facial analysis (Best Paper Award runner up) ACM ICVGIP, Dec. 2016, Guwahati India [pdf]

• Bhattarai, B. Sharma, G. Lechervy, A. and Jurie, F. A Joint Learning Approach for Cross Domain Age Estimation (Best Student Paper Award of Image, Video and Multidimensional Signal Processing) ICASSP, April 2016, Shanghai, China [pdf]

• Bhattarai, B. Sharma, G. Jurie, F. and Perez, P. Some faces are more equal than others: Hierarchical organization for accurate and efficient large-scale identity-based face retrieval LBP ECCV, 2014, Zurich, Switzerland [pdf]

• Bhattarai, B. Mignon, A. Jurie, F. and Furon, T. Puzzling Face Verification Algorithms for Privacy Protection IEEE WIFS, Dec 2014, Atlanta, USA [pdf]

• Klementiev, A. Titov, I. and Bhattarai, B. Inducing Crosslingual Distributed Representations of Words, In International Conference on Computational Linguistics (COLING), Dec. 2012, Mumbai, India [pdf]

• Klementiev, A. Titov, I. and Bhattarai, B. Crosslingual Distributed Representations of Words, Deep Learning NIPS, 2012, Tahoe Lake, USA [pdf]

• Bhattarai, B. Development of face analysis approximation methods by machine learning , PhD Thesis, Dec. 2016 (Normandie University, France) [pdf]

• Bhattarai, B. Inducing cross-lingual word representations, Masters Thesis, Jan. 2013 (Saarland University, Germany) [pdf]