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update intro and pub
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‎index.qmd

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---
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title: "Govind Waghmare"
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subtitle: |
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Machine Learning Researcher working on graphs and NLP.
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Machine Learning Researcher.
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image: assets/profile.jpg
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toc: false
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about:
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I currently work at Mastercard as a Senior Data Scientist. My research interests include temporal graphs and NLP for transactional data.
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Welcome to my personal website 👋!
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I currently work at Mastercard as a Senior Data Scientist. I manage transactional data, which encompasses tabular and temporal dimensions. It involves intricate temporal data modeling utilizing time-series analysis, temporal point processes, and temporal graph neural networks. Additionally, I am actively engaged in prototyping the integration of Large Language Model (LLM)--based embeddings, harnessing their capabilities to optimize performance across transactional data scenarios. My daily responsibilities encompass the end-to-end process of designing, developing, and deploying machine learning and deep learning models at scale, ensuring robust and efficient solutions.
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## Education

‎publications.qmd

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My [Google Scholar](https://scholar.google.com/citations?user=QtutNncAAAAJ) 📝 profile.
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---
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<!--
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* **[Learning Temporal Representations of Bipartite Financial Graphs](https://dl.acm.org/doi/abs/10.1145/3604237.3626911)
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<br/> Pritam Kumar Nath, Govind Waghmare, Nikhil Tumbde, Nitish Kumar, Siddhartha Asthana **
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<br/> *International Conference on AI in Finance (ICAIF), 2023*
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* **[TBoost: Gradient Boosting Temporal Graph Neural Networks](https://openreview.net/pdf?id=API0yII2Ua)
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<br/> Pritam Nath, Govind Waghmare, Nancy Agrawal, Nitish Kumar, Siddhartha Asthana**
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<br/> *Temporal Graph Learning Workshop @ NeurIPS, 2023*
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---
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* **[Modeling Inter-Dependence Between Time and Mark in Multivariate Temporal Point Processes](https://arxiv.org/abs/2210.15294)
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<br/> Govind Waghmare, Ankur Debnath, Siddhartha Asthana, Aakarsh Malhotra**
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<br/> *Conference on Information & Knowledge Management (CIKM), 2022*
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---
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* **[Adversarial Generation of Temporal Data: A Critique on Fidelity of Synthetic Data](https://link.springer.com/chapter/10.1007/978-3-030-93736-2_24)
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<br/> Ankur Debnath, Nitish Gupta, Govind Waghmare, Hardik Wadhwa, Siddhartha Asthana, Ankur Arora**
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<br/> *Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2021*
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---
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* **[Exploring generative data augmentation in multivariate time series forecasting: opportunities and challenges](https://kdd-milets.github.io/milets2021/papers/MiLeTS2021_paper_7.pdf)
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<br/> Ankur Debnath, Govind Waghmare, Hardik Wadhwa, Siddhartha Asthana, Ankur Arora**
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<br/> *KDD Workshop on Mining and Learning from Time Series (MileTS), 2021*
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* **[Unsupervised cross-modal alignment for multi-person 3d pose estimation](https://arxiv.org/pdf/2008.01388.pdf)
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<br/> Jogendra Nath Kundu, Ambareesh Revanur, Govind Vitthal Waghmare, Rahul Mysore Venkatesh, R Venkatesh Babu**
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<br/> *European Conference on Computer Vision (ECCV), 2020*
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- [Project page](https://sites.google.com/view/multiperson3D)
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---
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* **[Badminton shuttlecock detection and prediction of trajectory using multiple 2 dimensional scanners](https://ieeexplore.ieee.org/abstract/document/7413746/)
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<br/> Govind Waghmare, Sneha Borkar, Vishal Saley, Hemant Chinchore, Shivraj Wabale**
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<br/> *IEEE First International Conference on Control, Measurement and Instrumentation (CMI), 2016*
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<br/> *IEEE First International Conference on Control, Measurement and Instrumentation (CMI), 2016*
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-->
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```{=html}
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<table>
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<tbody>
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<tr class="border_bottom">
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<td><img src='/assets/misc/abs_dyn_bip.jpg' width="275"></td>
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<td>
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<strong>
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<a href="https://dl.acm.org/doi/abs/10.1145/3604237.3626911">Learning Temporal Representations of Bipartite Financial Graphs</a>
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</strong>
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<br> Pritam Kumar Nath, <strong>Govind Waghmare</strong>, Nikhil Tumbde, Nitish Kumar, Siddhartha Asthana
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<br> <em>International Conference on AI in Finance (ICAIF), 2023</em>
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</td>
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<!-- <hr> -->
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</tr>
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<tr class="border_bottom">
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<td><img src='/assets/misc/abs_tboost.jpg' width="275"></td>
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<td>
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<strong>
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<a href="https://openreview.net/pdf?id=API0yII2Ua">TBoost: Gradient Boosting Temporal Graph Neural Networks</a>
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</strong>
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<br> Pritam Nath, <strong>Govind Waghmare</strong>, Nancy Agrawal, Nitish Kumar, Siddhartha Asthana
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<br> <em>Temporal Graph Learning Workshop @ NeurIPS, 2023</em>
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</td>
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</tr>
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<tr class="border_bottom">
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<td><img src='/assets/misc/abs_tpp_cikm_2022.jpg' width="275"></td>
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<td>
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<strong>
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<a href="https://arxiv.org/abs/2210.15294">Modeling Inter-Dependence Between Time and Mark in Multivariate Temporal Point Processes</a>
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</strong>
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<br> <strong>Govind Waghmare</strong>, Ankur Debnath, Siddhartha Asthana, Aakarsh Malhotra
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<br> <em>Conference on Information & Knowledge Management (CIKM), 2022</em>
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</td>
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</tr>
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<tr class="border_bottom">
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<td><img src='/assets/misc/adv_synth_ts.jpg' width="275"></td>
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<td>
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<strong>
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<a href="https://link.springer.com/chapter/10.1007/978-3-030-93736-2_24">Adversarial Generation of Temporal Data: A Critique on Fidelity of Synthetic Data</a>
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</strong>
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<br> Ankur Debnath, Nitish Gupta, <strong>Govind Waghmare</strong>, Hardik Wadhwa, Siddhartha Asthana, Ankur Arora
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<br> <em>Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2021</em>
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</td>
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</tr>
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<tr class="border_bottom">
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<td><img src='/assets/misc/arch_timegan_lstnet.jpg' width="275"></td>
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<td>
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<strong>
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<a href="https://kdd-milets.github.io/milets2021/papers/MiLeTS2021_paper_7.pdf">Exploring generative data augmentation in multivariate time series forecasting: opportunities and challenges</a>
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</strong>
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<br> Ankur Debnath, <strong>Govind Waghmare</strong>, Hardik Wadhwa, Siddhartha Asthana, Ankur Arora
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<br> <em>KDD Workshop on Mining and Learning from Time Series (MileTS), 2021</em>
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</td>
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</tr>
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<tr class="border_bottom">
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<td><img src='/assets/misc/mp_eccv_2020.jpg' width="275"></td>
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<td>
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<strong>
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<a href="https://arxiv.org/pdf/2008.01388.pdf">Unsupervised cross-modal alignment for multi-person 3d pose estimation</a>
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</strong>
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<br> Jogendra Nath Kundu, Ambareesh Revanur, <strong>Govind Waghmare</strong>, Rahul Mysore Venkatesh, R Venkatesh Babu
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<br> <em>European Conference on Computer Vision (ECCV), 2020</em>
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</td>
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</tr>
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<tr class="border_bottom">
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<td><img src='/assets/misc/badminton_cmi2016.jpg' width="275"></td>
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<td>
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<strong>
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<a href="https://ieeexplore.ieee.org/abstract/document/7413746/">Badminton shuttlecock detection and prediction of trajectory using multiple 2 dimensional scanners</a>
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</strong>
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<br> <strong>Govind Waghmare</strong>, Sneha Borkar, Vishal Saley, Hemant Chinchore, Shivraj Wabale
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<br> <em>IEEE First International Conference on Control, Measurement and Instrumentation (CMI), 2016</em>
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</td>
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</tr>
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</tbody>
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</table>
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```
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‎styles.css

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/* css styles */
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tr.border_bottom td {
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border-bottom: 1px solid rgb(220, 214, 214);
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}

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