Tr$^2$AIL: Trust and Transparency in AI through Logic
$^2$AIL research group is led by Prof. Somak Aditya. The long-term goal of the lab is to achieve transparent Human-aware AI systems through Logic and Reasoning. We want the AI systems to be able to reason-in-the-wild
and do so transparently for the end-users with whom it is expected to interact. Technically, we will work on the fundamental challenges faced by current neural and probabilistic logical systems in achieving such properties. I am fortunate to be working with a group of passionate student reserachers
and my wonderful collaborators
. Our group acknowledges the kind and generous support by Microsoft
(through sponsored internship), Toloka AI
, SERB DST and IIT Kharagpur (see Grants
I am looking for motivated Ph.D students who are interested in pursuing their thesis in the exciting juncture of classical and statistical AI (often dubbed as neuro-symbolic methods). For prospective students, please see answers to FAQs below (to be updated).
We are grateful to be supported by the following generous organizations:
SERB DST SRG (2021-23)
SERB DST Startup Research Grant (2021-23) ~ INR 26 Lacs
| Topic: "Learning from Rules and Data for Image Analytics"
IIT Kharagpur FSRG (2022-24)
IIT Kharagpur Faculty Startup Research Grant (2022-24) ~ INR 25 Lacs
Topic: The Role of Feedback in Vision-Language enabled Embodied Agents towards Applications in Desire Management
Joint PI: Prof. Pawan Goyal
Microsoft Accelerate Foundation Models Grant (May-Dec 2023)
Microsoft: "Accelerate Foundation Models Academic Research" (2023) ~ USD 10000 | Topic: "Perils and Prevention of Prompt Injection Attacks for Large Language Models"
Joint PI: Prof. Animesh Mukherjee
Toloka AI Grant (2022)
Annotation Grant (2022) ~ USD 300
| Topic: "Infusing Language Model with Affordances"
FAQs for Propsective Students
What are the projects that you will be working on?
Here are some broad questions that we are interested in:
See the project page and publication to see how solving such technical challenges may affect a range of applications -- from NLP, Vision, to automated mathematical reasoning.
- How do we reason transparently? What does it mean to reason transparently?
- How do we reason with noisy and incomplete knowledge sources? Can we utilize semi-structured (or more natural) forms of knowledge representation?
- How do we elicit missing knowledge?
- How can human-in-the-loop help?
Is my expertise right for your lab?
I am happy to welcome students with diverse expertise, ideas and background. But, based on my experience, following expertise seem absolutely essential. First, coding expertise (python mostly) and scripting knowledge (shell script, R is a plus). Being able to figure out your way through installation issues, knowledge about Git, shell scripting, and basic idea about GPUs are important. If you are an IIT-KGP student, make sure you have obtained A or above in PDS theory and Lab. Share a link to your Git repositories. Participation in popular open-source projects is a plus.
Secondly, even if you are not familiar with ML, in-depth understanding of Algorithms, Probability and statistics is important. Knowledge of Logic, ML, DL, traditional NLP (parsing, POS tagging, chunking etc.), linguistics, or traditional image processing is a huge plus.
How do I contact you?
If you are an IIT KGP student, please send an inquiry to my email. Kindly mention which program you are enrolled in. If you are not a KGP student, kindly visit the IIT Kharagpur website to see how to enroll in the Ph.D or Masters program.
I plan to take 1 or 2 external students who shows proven depth in at least one of the axes (linguistics/ML/DL/CV) through Publications/Courses/olympiads as interns (for one or two semesters). Feel free to email me if that interests you, and you fit the profile.