About me
A dedicated enthusiast in the world of Machine Learning and Artificial Intelligence. My journey into technology began early, fueling a profound passion for innovation and positive global impact. Currently, I am pursuing a Master's in Advanced Computing (Research Fellow at I-X HUB, Brain & Signal Analysis Lab) at the prestigious Imperial College London . I am also working as a Research Fellow at Brain And Signal Research & Analysis (BASIRA) Laboratory in I-X. Completed my Bachelor's in Computer Engineering with a minor in Conversational A.I. at Thapar University.
Beyond academia, I've contributed to significant research projects, worked at JP Morgan Chase & Co., and published research papers internationally at both conferences and journals. Driven by a commitment to innovation and a love for adventure, I hold a Gold Medal from the Himalayan Mountaineering Institute and have championed Table Tennis regionally. I am excited to further my impact on the world of technology.
What i'm doing
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Founder
Building the next big thing!
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Research Fellowship
MSc researcher at BASIRA Lab, I-X, focusing on 'Self-Explainable reasoning-centric GNNs' under Dr. Islem Rekik
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Pattern Discovery
Working on knowledge synthesis and pattern discovery using GNNs and self-explainable reasoning.
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Trekking
Love to travel around the world and meet people from different walks of life. Have been to numerous trekking camps.
Achievements & Honours
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Awarded CPP Individual Project Prize for excellence in Computing Science (Distinguished)
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Received Corporate Partnership Programme (CPP) Funding of $1200
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Gold Medalist at HMI (Himalayan Mountaineering Institute)
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Student of the Year Award by USA UnivQuest
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Finalist in Code for Good’22 National Hackathon by JP Morgan Chase & Co.
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National Debate Winner (APD) & Model United Nation (Special & Verbal Mention)
GitHub Campus Expert (60 selected from 10,000 applications) and also Postman Campus Expert (API Certified)
experience
Work Experience
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BASIRA Lab, I-X, Imperial College London
Research Fellow
Feb 2025 – Sep 2025- - Conducted research at the Brain And Signal Analysis (BASIRA) Lab under Dr. Islem Rekik, focused on building an interpretable GNN foundational model using symbolic reasoning, gradient introspection and self-explainability.
- - Built an AI Agentic System with multi-retrieval RAG from KG and conducting customized Generative Evals.
- - Accepted two papers: FireGNN (NeurIPS 2025 Workshop, Poster) and X-Node (MICCAI 2025, Oral, A1 Conference).
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JP Morgan Chase & Co
Software Engineer
Jan 2024 – July 2024- - Worked in CCB (Consumer & Community Banking; @Chase Bank) LOB under Global Technology.
- - Modified AEM (Adobe Experience Manager), GraphQL, PQ based components for Chase Products.
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JP Morgan Chase & Co
Software Engineer Intern
June 2023 – Aug 2023- - Worked in the Electronic Compliance Department (FRDC) under the Global Technology
- - Developed DL-based algorithms, which were 80% accurate for automating surveillance systems over emails, voice recording and other modes of communication between employees and traders.
- - Worked on several DL techniques such as BERT, Transformers (Word2vec2ctc), Transcription Engines (Omni AI) and Prod accounts while working on the real time project
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IIT KANPUR
Research Intern
June 2022 – June 2023- - Worked on a research project in Multimodal-Emotion-Recognition, under Prof. Ashutosh Modi.
- - Worked with NLP Models (for different languages), Deep Learning Models & Annotation.
- - Published blog of Label-Studio-Annotator-Control, by developing additional annotator specific features.(Blog Link)
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THAPAR UNIVERSITY
Undergraduate Student Research Intern
Aug 2022 – Feb 2023- - Worked on a research paper in A Feature Extraction and Time Warping based Neural Expansion Architecture for Cloud Resource Usage Forecasting under Prof. Jatin Bedi.(Submitted to Cluster Computing SCI Journal; IF: 4.4)
- - Worked with Cloud Clustering dataset (2019-a traces), to find the optimum cloud usage time via Deep Learning Models & Clustering algorithms in connection with Time Series (Soft-DTW).
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SCALER ACADEMY(INTERVIEWBIT)
Technical Content Writer Intern
Aug 2022 – Feb 2023- - Wrote Technical Blogs on topics based on programming languages and have published 6 blogs.(Link)
- - Worked and reviewed articles based on Python, C++, SQL and gave SEO suggestions.
Education
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Imperial College London
2024 — 2025MSc Advanced Computing (Research Fellow at I-X HUB, Brain & Signal Analysis Lab). [Awarded Distinguised Status]
- - Term 1: Reinforcement Learning, Computational Neurodynamics, Computer Vision, Blockchain [Received Distinction]
- - Term 2: Deep-Graph Based Learning, NLP, Deep Learning, Software Engineering for ML Systems [Received Distinction]
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Thapar Institute of Engineering & Technology
2020 — 2024B.E. in Computer Engineering with a minor in Conversational A.I. I served as the General Secretary of the OWASP Student Chapter. I led a team of over 200 students in various technical domains and organized international MLH Hackathons.
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Higher Secondary
2020- ISC Board – 96% (PCMB)
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Secondary
2018- ICSE Board – 95%
Publications
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X-Node: Self-Explanation is All We Need
GRAIL, MICCAI 2025 Conference (Oral), South Korea
Proposed a self-explainable graph neural network framework (X-Node) enabling robust, reasoning-centric interpretability for medical image analysis. (Under Dr. Islem Rekik, BASIRA Lab)
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FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules
NeurIPS 2025 Workshop (Poster), San Diego, USA
Introduced a neuro-symbolic GNN framework (FireGNN) integrating fuzzy logic with trainable rules for transparent, trustworthy, and interpretable medical imaging tasks. (Under Dr. Islem Rekik, BASIRA Lab)
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Benchmarking the Effectiveness of Classification Algorithm & SVM Kernel for Dry Beans
AIDA IEEE BigData 2023 Conference (arXiv pre-print) [Accepted]
This study evaluates SVM classification algorithms (linear, polynomial, RBF) and other methods. RBF SVM achieves the highest accuracy (93.34%), precision (92.61%), recall (92.35%), and F1 Score (91.40%). (Under Dr. Harpreet Singh with Tel Aviv University, Israel)
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Enhancing Performance of Deep Learning Model with Novel Data Augmentation approach
14th ICCCNT International Conference (IEEE Xplore), IIT Delhi
The paper discusses data augmentation in deep learning, focusing on CNNs. It introduces a novel technique involving rescaling, rotating, flipping, and converting to grayscale, which outperforms existing methods with a 93.33% accuracy, a 3.33% improvement. (Under Prof. P.S Rana)
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Predictive Maintenance of Armoured Vehicles using Machine Learning Approaches
ICCSMLAI International Conference 2023
The paper suggests a predictive maintenance system for armoured vehicles using ensemble machine learning, achieving impressive results: 98.93% accuracy, 99.80% precision, and 99.03% recall. (Under Prof. P.S Rana)
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A Multi-Layered Approach to Brain Tumor Classification Using VDC-12
ICCST International Conference (Springer CCIS) [Accepted]
This paper introduces a CNN model for multiclass brain tumor detection in medical images, outperforming other techniques with a 97.60% classification accuracy. (Under Prof. P.S Rana)
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A Feature Extraction and Time Warping based Neural Expansion Architecture for Cloud Resource Usage Forecasting
Cluster Computing Springer Journal, SCIE Index, IF: 4.4
Enhancing cloud resource estimation efficiency through a hybrid machine learning approach, outperforming traditional methods, validated with real-world Google cluster data, for superior accuracy and performance.
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