Arnab Kumar Mondal

I have received my Bachelor of Engineering in Electronics and Telecommunication from Jadavpur University, India in 2013. Right after my graduation, I joined Centre for Development of Telematics (C-DOT), Delhi, and served as a research engineer there until July 2018. In C-DOT I had the opportunity to participate in cutting-edge projects such as the Dense Wavelength Division Multiplexing (DWDM) and Packet Optical Transport Platform (P-OTP). I joined IIT Delhi as a Ph.D. scholar in July, 2018 under the guidance of Prof. Prathosh AP and Prof. Parag Singla. My research interests lie primarily within the field of deep generative models and applied deep learning. My Ph.D. was supported by the Prime Minister's Research Fellows (PMRF) Scheme by Govt. of India. Currently, I am working as a senior researcher in the graph AI team of Fujitsu Research India Private Limited.

Experience

Education

Publications

SSDMM-VAE: variational multi-modal disentangled representation learning

Applied Intelligence, 2023

Self-supervised Representation learning Based OSA Detection Method using Single Channel ECG Signals

IEEE Transactions on Instrumentation and Measurement, 2023

Clustering Single-cell RNA Sequence Data using Information Maximized and Noise-Invariant Representations

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023

Deep latent space clustering for detection of stealthy false data injection attacks against ac state estimation in power systems

IEEE Transactions on Smart Grid, 2023

ImAiR: Airwriting recognition framework using image representation of IMU signals

IEEE Sensors Letters, 2022

COVID-19 prognosis using limited chest X-ray images

Applied Soft Computing, 2022

SCLAiR: Supervised Contrastive Learning for User and Device Independent Airwriting Recognition

IEEE Sensors Letters, 2021

xViTCOS: Explainable Vision Transformer Based COVID-19 Screening Using Radiography

IEEE Journal of Translational Engineering in Health and Medicine, 2021

scRAE: Deterministic Regularized Autoencoders with Flexible Priors for Clustering Single-cell Gene Expression Data

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021

RespVAD: Voice Activity Detection via Video-Extracted Respiration Patterns

IEEE Sensors Letters, 2020

Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach

EMNLP (Main Conference), 2023

Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-Encoders

AISTATS, 2023

Few-shot Cross-domain Image Generation via Inference-time Latent-code Learning

ICLR, 2023

FlexAE: Flexibly Learning Latent Priors for Wasserstein Auto-Encoders

UAI, 2021

MaskAAE: Latent space optimization for Adversarial Auto-Encoders

UAI, 2020

C-MI-GAN: Estimation of Conditional Mutual Information using MinMax formulation

UAI, 2020

Research Interests

Representation Learning, Generative Models, Deep Learning.

Honors & Awards

• Prime Minister's Research Fellows (PMRF)

  COMPETITIVE SCHOLARSHIP FOR ACADEMIC AND RESEARCH EXCELLENCE

  2020-2023 IIT, Delhi

• Prof. Jnansaran Chatterjee Memorial Gold Medal

  AWARD FOR SECURING THE HIGHEST AGGREGATE MARKS IN THE PAPERS “ELECTROMAGNETIC THEORY” AND “ANTENNAS & PROPAGATION”

  2013 Jadavpur University, Kolkata

• Amul Vidya Bhushan Award

  AWARD for outstanding performance in Higher Secondary Examination

  2009 Ramakrishna Mission Vidyapith, Purulia