Aishik Konwer


						Aishik Konwer 5th year PhD candidate Department of Computer Science, Stony Brook University Email: akonwer@cs.stonybrook.edu, Mobile: +1-6317471244 Resume • Google Scholar • Github • Linkedin

I am a Research Assistant at Imagine lab under the supervision of Prof. Prateek Prasanna.

Before joining SBU, I did my Bachelor in Technology (Btech) from the Institute of Engineering & Management, Kolkata (India) majoring in Electronics and Communication Engineering. During my undergraduate, I particularly worked on research problems such as Scene Text Detection and Recognition, Handwriting Recognition, Writer Identification, and Script Identification.

Research Interest: My current research interests lie in deep learning and computer vision in general, including multimodal learning, deep generative models, and medical imaging.

My thesis focuses on designing algorithms that learn efficiently from imperfect 2D/3D/multi-stained medical imaging datasets. Some of my works include enhancing multimodal foundational models (VLMs) with efficient prompts, applying generative approaches such as GANs and conditional diffusion models, fine-tuning LLMs, and customizing meta-learning/few-shot algorithms for clinical tasks. These tasks span medical image segmentation, caption generation, and future timepoint prediction in limited data settings.

I am currently on the job market for Research Scientist roles.

Recent News

^NEW 06/2024: 1 paper accepted to MICCAI

^NEW 08/2023: 1 paper accepted to MICCAI workshop

^NEW 07/2023: 1 paper accepted to ICCV

^NEW 07/2022: 1 abstract accepted to RSNA

^NEW 03/2022: 1 paper accepted to CVPR

10/2021: 1 paper accepted to SPIE Medical Imaging

03/2021: 1 paper accepted to MIDL

10/2019: 1 paper accepted to ICASSP

04/2018: 3 papers accepted to ICPR

08/2018: 1 paper accepted to Pattern Recognition

05/2017: 1 paper accepted to ACPR

Education


						Stony Brook University, USA PhD in Computer Science & Engineering Aug 2019 - June 2024


						Institute of Engineering & Management, India Btech in Electronics and Communication Engineering Aug 2013 - June 2017

Research Experiences


						Indian Statistical Institute, Kolkata, India Under Prof. Umapada Pal Sept 2016 - Sept 2017 [Certificate]


						Indian Institute of Technology Roorkee, India Under Prof. Partha Pratim Roy Sept 2017 - March 2018 [Certificate]

Industry


						GE Healthcare, USA AI Scientist Intern May 2024 - August 2024


						SRI International, USA Deep Learning Research Intern May 2023 - August 2023


						Roche, USA Advanced ML Research Intern May 2022 - August 2022


						Cognizant, India Datawarehouse developer Dec 2017 - July 2019

Selected Research

	MetaStain: Stain-generalizable Meta-learning for Cell Segmentation and Classification with Limited Exemplars Aishik Konwer, Prateek Prasanna International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.
	Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation Aishik Konwer, Xiaoling Hu, Joseph Bae, Xuan Xu, Chao Chen, Prateek Prasanna IEEE International Conference on Computer Vision (ICCV), 2023. [paper]
	Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna IEEE Conference on Computer Vision and Pattern Recognition Conference (CVPR), 2022. [paper]
	Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Prateek Prasanna International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [paper]
	Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Amit Gupta, Chao Chen, Joel Saltz, Prateek Prasanna Medical Imaging with Deep Learning (MIDL), 2021. [paper]
	Facial Micro-Expression Spotting and Recognition using Time Contrasted Feature with Visual Memory Sauradip Nag , Ayan Kumar Bhunia , Aishik Konwer, Partha Pratim Roy International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019. [paper], [arXiv]
	Script identification in natural scene image and video frames using an attention based Convolutional-LSTM network Ankan Kumar Bhunia, Aishik Konwer, Abir Bhowmick, Ayan Kumar Bhunia, Partha Pratim Roy Pattern Recognition, 2019. [I.F. 3.962] [paper], [arXiv], [GitHub]
	Word Level Font-to-Font Image Translation using Convolutional Recurrent Generative Adversarial Networks Ankan Kumar Bhunia, Ayan Kumar Bhunia, Prithaj Banerjee, Aishik Konwer, Abir Bhowmick, Partha Pratim Roy, Umapada Pal *International Conference on Pattern Recognition (ICPR), 2018* [paper], [arXiv]
	Staff line Removal using Generative Adversarial Networks Aishik Konwer , Ayan Kumar Bhunia, Abir Bhowmick, Ankan Kumar Bhunia, Prithaj Banerjee, Partha Pratim Roy, Umapada Pal International Conference on Pattern Recognition (ICPR), 2018 (Oral) [paper], [arXiv]
	Handwriting Trajectory Recovery using End-to-End Deep Encoder-Decoder Network Ayan Kumar Bhunia, Abir Bhowmick, Ankan Kumar Bhunia, Aishik Konwer, Prithaj Banerjee, Partha Pratim Roy, Umapada Pal International Conference on Pattern Recognition (ICPR), 2018 [paper], [arXiv]
	A New GVF Arrow Pattern for Character Segmentation from Double Line License Plate Images Palaiahnakote Shivakumara, Aishik Konwer, Abir Bhowmick, Vijeta Khare, Umapada Pal, Tong Lu 4th Asian Conference on Pattern Recognition (ACPR),, 2017. [paper]