Tirtharaj Dash | interests

Research

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Deep Learning

Neural Networks has had a long and rich history, and the reincarnated viewpoint has shifted towards “Deep Neural Networks” and “Deep Learning”. Deep learning and its ever-evolving implementations have been achieving remarkable successes in subareas of science and technology. I am inclined towards conceptual and implementational aspects of deep learning for problems arising in biology, chemistry, computer vision, robotics and games. This includes: deep learning for structured- and unstructured-data, transfer learning, model compression, adversarial learning, deep reinforcement learning.

Neuro-Symbolic AI

Neural networks can learn from non-symbolic or structured data, and they are found to be robust to noise. However, they suffer from two important issues: their learning is severely affected if data is scarce; they are not interpretable. Whereas, symbolic machine learning models are very data efficient and interpretable. Neuro-symbolic models exploit the advantages of neural networks and symbolic models. My research focus in this area is a combination of deep neural networks and Inductive Logic Programming (ILP). Follow some of my works here: NeSy.

Graph Representation Learning

Graph neural networks or GNNs have shown tremendous potential in learning from relational data or graph-structured data. I am interested in conceptual and implementational development of graph-convolution and graph-pooling procedures. Further, I am very motivated to involve myself in the evolving areas of “Geometric Deep Learning”. If you are new to the world of GNNs, you may want to go through these introductory slides on GNNs.

Machine Learning

I work on concept and implementations of Machine Learning models and systems. I primarily focus on various optimisation strategies for learning ML models, including structure optimisation and Bayesian learning. In the past, I have also looked at Probabilistic Graphical Models (PGMs), albeit in the context of Deep Learning.

Computational Biology

My area of interest has recently being broadened owing to my Post-PhD experience in AI for Healthcare and AI for Life Sciencec, in general. I look at various interesting problems in Genomics, Single-Cell and Spatial Transcriptomics. I always have a keen interest on solving problems in Drug Discovery. Overall, my interests include applying ML and DL in problems arising in the area of: internet-of-things (IoT), computer networks and finance (time-series analysis).

Upcoming Conference Deadlines

Collaboration

I am looking forward to new problems and research discussions. I am happy to collaborate, if there is any shared interest. In future, there will be a website for my lab: iMachLab.

Teaching

I love teaching any course that is in line with my present research interests: Deep Learning, Machine Learning, Artificial Intelligence. In the past, I have always enjoyed teaching programming (mostly in C or C++) to first-year undergrad students. A course on data structure and algorithms has always been my crush in my short teaching life. I have taught database systems (including labs on MySQL) and would like to teach again if I have to, but with a flavour of relational learning.

Academic and Research Services

I contribute to research indirectly, by reviewing for journals and conferences. Some of my activities are listed here.

Journal Editor

PLOS One (since Jan 2023)

Journal Reviewer

(Frequent ones are marked ‘*’, where I have reviewed at least 4 different full papers. I have now stopped reviewing for some of these journals due to: (a) quality of submissions, (b) too busy doing other things, (c) tired of incentive-less reviewing.)

IEEE Transactions on Industrial Electronics (TIE)*
IEEE Transactions on Cybernetics (CYB-IEEE)*
Neural Processing Letters (NEPL)*
IEEE Systems Journal (IEEE-SJ)
IEEE Transactions on Network Science and Engineering (TNSE)
IEEE Consumer Electronics Magazine (CEMAG)
IEEE Access
Scientific Data (Nature)
Information Fusion (INFFUS)*
Cognitive Systems Research (COGSYS)*
Applied Soft Computing (ASOC)
Frontiers in Neuroscience (Front. Neurosci.)
Soft Computing (SOCO)
Computers & Security (COSE)
Computer Methods and Programs in Biomedicine (CMPB)
Paladyn Journal of Behavioral Robotics (PJBR)
Robotica
Ain Shams Engineering Journal (ASEJ)
Proceedings of the National Academy of Sciences India (NASA)
International Journal Intelligent Robotics and Applications (JIRA)
International Journal of Image and Data Fusion (TIDF)
International Journal of Communication Systems (IJCS)
Data Technologies and Applications (DTA)
CAAI Transactions on Intelligence Technology (CIT)
Journal of Experimental & Theoretical Artificial Intelligence (TETA)

Conference Activities

Member of program committee, IJCAI: 2022–2024
Member of program committee, AI for Social Good Track, IJCAI: 2023–2024
Member of program committee, DASFAA: 2022
Member of program committee, AAAI-CLeaR: 2022
Member of technical committee, IJCNN: 2019–2023
Member of program committee, ICANN: 2019–2021
Member of program committee, ILP: 2019
Member of organizing committee, ICCI: 2017 (IIT Kanpur)

What else, if it matters to you?

I was born and raised in a remote village of Western Odisha, an Indian state rich in culture, vegetables and farming. My father (who is a Master in Arts and Bhagavad Gita) and extended paternal family are involved mostly in farming and small businesses. We speak a dilect of Odia language, known as Kosali (a folk language). My district is known for Odia folk music and the famous Sambalpuri Saree. I enjoy riding motorbikes (mostly fast-yet-careful racing). I play cricket; I am a batsman and a wicketkeeper. That view of the game from behind the stumps is extraordinary. I have occasionally played football; I am a goalkeeper. I love swimming in the sea (The Arabian sea is my neighbour) and known rivers. Trekking is something that always excites me. Watching movies on weekends has always been there since my undergrad studies (sometimes, I do binge-watch). In addition to all these fun stuff, I am also interested in philosophy, spirituality, farming, and poverty prevention.

Websites, I regularly visit: