Tanmoy Dam, Ph.D.
Email: tanmoydam@yahoo.com/ Google Scholar / LinkedIn
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About me:
I completed my Ph.D. in Electrical Engineering in August 2022 at the University of New South Wales (UNSW), Australia, mentored by Senior Lecturer Sreenatha Anavatti and Prof. Hussein Abbass. My doctoral dissertation focused on developing Generative Models for dealing with classification and clustering problems in situations where learning is both imbalanced and ongoing (Continual). I received my M.S. (by research) in Electrical Engineering from the Indian Institute of Technology Kharagpur(IIT-KGP), where my thesis was based on developing fuzzy clustering algorithms for TS rule-based dynamical system identification.
I am currently working as a postdoctoral fellow at Emory University with Prof. Anant Madabhushi.I am applying novel quantitative AI imaging analysis, broadly focusing on computer vision, image processing, and multi-modal fusions (such as Radiomics, Pathomics, and text) for disease diagnosis and prognosis. Prior to this, I have worked as a Research Fellow at the Saab-NTU Joint Lab, Nanyang Technological University (NTU), Singapore where we have developed novel Multimodal fused based 3D object detections to tackle futueristics autonomous airports project. In addition, I engaged in multiple projects in digital tower technology, focusing on the development of real-time object detection solutions (few-shot domain adaptation) and the generation of precise runway exit predictions through the analysis of historical time series data, accounting for concept and data drift. I have previous experience as a tech lead at KPIT (R&D) in Pune, India, working on various autonomous vehicle projects (autopilot software). Prior to my employment at KPIT, I held positions as a junior and senior research fellow, contributing to virtual lab initiatives hosted at IIT-KGP.
I completed my Ph.D. in Electrical Engineering in August 2022 at the University of New South Wales (UNSW), Australia, mentored by Senior Lecturer Sreenatha Anavatti and Prof. Hussein Abbass. My doctoral dissertation focused on developing Generative Models for dealing with classification and clustering problems in situations where learning is both imbalanced and ongoing (Continual). I received my M.S. (by research) in Electrical Engineering from the Indian Institute of Technology Kharagpur(IIT-KGP), where my thesis was based on developing fuzzy clustering algorithms for TS rule-based dynamical system identification.
I am currently working as a postdoctoral fellow at Emory University with Prof. Anant Madabhushi.I am applying novel quantitative AI imaging analysis, broadly focusing on computer vision, image processing, and multi-modal fusions (such as Radiomics, Pathomics, and text) for disease diagnosis and prognosis. Prior to this, I have worked as a Research Fellow at the Saab-NTU Joint Lab, Nanyang Technological University (NTU), Singapore where we have developed novel Multimodal fused based 3D object detections to tackle futueristics autonomous airports project. In addition, I engaged in multiple projects in digital tower technology, focusing on the development of real-time object detection solutions (few-shot domain adaptation) and the generation of precise runway exit predictions through the analysis of historical time series data, accounting for concept and data drift. I have previous experience as a tech lead at KPIT (R&D) in Pune, India, working on various autonomous vehicle projects (autopilot software). Prior to my employment at KPIT, I held positions as a junior and senior research fellow, contributing to virtual lab initiatives hosted at IIT-KGP.
News
[September, 25]. One Journal paper accepted in PLOS Digital Health.
[August, 25]. One Journal paper accepted in Expert Systems with Application, Congrats Rasel!
[Jan -present, 25]. 3 Journals paper accepted in Lancet, Jama Network and European Journal of Cancer.
[Jan -present, 25]. Two Conference paper accepted in ICTIS 25, Congrats Rasel.
[May 25]. Chaired the autonomous vehicle session at ICRA 2025.
[Feb 25]. One conference accepted in SPIE.
[Jan -present, 25]. Sanjay’s paper accepted to ICRA 2025! This marks his second consecutive year securing a travel grant.
[Aug-Dec, 24] Three papers accepted to health conferences, including ISIB, InCOR-NTD, and the American Urological Association Annual Meeting.
[July 24] One Conference paper accepted at CIKM 24. Congrats, Sanjay!
[June 24] One Journal paper accepted at Renewable and Sustainable Energy Reviews.
[May 24] One Journal paper accepted at Artificial Intelligence Review. Congrats Gao!
[March 24] Congratulations to Sanjay for receiving the IEEE RAS student travel grant to present at IEEE ICRA 24 !
[January 24] One conference paper accepted at IEEE ICRA 24 . Congrats, Sanjay!
[January 24] One Jouranl paper accepted at TAI .
[November 23] I joined as a TPC reviewer at IEEE WCCI 24.
[October 23] One conference paper accepted at IEEE WACV-24 . Congrats, Gao!
[August 23] One Journal paper accepted at Expert System with Applications . Congrats, Rasel!
[April 23] One Journal paper accepted at IEEE Trans. on GRSL . Congrats, Gao!
[April 23] One conference paper accepted at IJCNN-23. Congrats, Rasel!
[October 22] Joined Saab-NTU Joint lab as a Research (Postdoctoral) Fellow.
[August 22] Awardee Ph.D.
[June 22] Ph.D. Thesis Submitted
[Jun 22] Two papers accepted at ICIP-22
[Jun 22] One paper accepted at ECML PKDD-22
[October 21] Received IEEE CIS Participation Grant Award for attending IEEE SSCI-21
[October 21] One paper accepted at IEEE SSCI 21
[September 21] Received SIGIR Student Travel Grant Award for attending CIKM-21
[August 21] One paper accepted at CIKM 21
Research
Research
For the last decade, my research and development efforts have focused on machine learning, data mining, and image processing. My current research aims to develop robust transformer models from few-shot samples under offline and continual learning settings. In addition to this, I am enthusiastic about topics like class imbalance, few-shot learning, generative models, and their practical applications.
Since 2013, I have supervised more than ten students working as research interns on projects that led to publications, technical reports, and dissertations. These interns came from a variety of prestigious academic institutions in India, Singapore, and Australia. In addition, I've participated in KPIT recruiting teams for both professionals and interns.Current Students:
Mr. Gao Yu Lee, (Pursuing in PhD), NTU Singapore
Mr. Md. Rasel Sarkar, (Pursuing in PhD), UNSW Canberra, Australia
Mr. Sanjay Bhargav, (Pursuing in Dual Degree), IIT Kharagpur, India
Research Topics
Research Topics
Computer Vision
Few-shot/zero-shot Learning (Offline and Continual learning settings)
Robust and Explainable AI
Generative Models
Multi-modal Learning
Time series Forecasting.
Applications: Air Traffic and Unmanned Aircraft System Traffic Management (ATM/UTM), Autonomous Vehicles (2D and 3D object Detections), Medical Image Diagnosis, Robotics, Energy etc.
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