"उद्यमेन हि सिध्यन्ति कार्याणि न मनोरथैः! न हि सुप्तस्य सिंहस्य प्रविशन्ति मुखे मृगाः!"

About

नमस्कार! I am अच्युत मणि त्रिपाठी (Achyut Mani Tripathi) , originally from Bilaspur, Chhattisgarh, India. I am an Assistant Professor (सहायक प्राध्यापक) in the Computer Science & Engineering Department ( संगणक विज्ञान एवं अभियांत्रिकी विभाग) at the Indian Institute of Technology Dharwad (IIT-Dh) (भारतीय प्रौद्योगिकी संस्थान धारवाड़) in Karnataka, India.

Academics:

  • Ph.D. Department of Computer Science & Engineering, IIT Guwahati, Assam, India.
  • BE Chhattisgarh Swami Vivekanand Technical University (CSVTU), Bhilai, Chhattisgarh.
  • Office A1-129, Academic Block-1, IIT Dharwad
  • Email t.achyut@iitdh.ac.in
  • Landline 1084

Research Interests

Deep Learning

Image,Video and Audio Classification

Deep Model Compression

Knowledge Distillation, Dataset Distillation

Adversarial Machine Learning

Adversarial Attacks, Backdoor Attacks

Multi-Modal Learning

AVSC, AVSE, AVEL, AVQA, AQA, VQA

Machine Unlearning

Class and Instance Specific Machine Unlearning

Applied ML for 5G/6G Networks

RIS Applications, Anomaly Detection

New Highlights and Announcements

  1. ( Paper Accepted: WACV 2025)→ When Visual State Space Model Meets Backdoor Attack (Congratulations Sankalp & Ashish )
  2. ( Paper Accepted: WACV 2025)→Bandit Based Attention Mechanism in Vision Transformer (Congratulations Prabhu & Raghu)
  3. I am looking for motivated B.Tech students with exceptional coding skills and a solid foundation in mathematics to join my team in deep learning. If you have a CGPA of 8.5 or higher and are eager to contribute to BTP/R&D projects in this field, please email me your detailed CV. One should only contact me for BTP/R&D if they are confident in their coding skills; let's save and respect each other's time. Currently, I am not seeking students for MTP, Ph.D., short-term internships, online internships, or mini-projects.

Publications

Patents

  1. "A System and Method for Activity Identification and Problem Prediction During Oil and Gas Well Drilling". [From Ph.D. Thesis]

Refereed Journal Articles

  1. " Enhancing Audio Representation Learning Using State Space Model", Neurocomputing, Elsevier, 2024 [H-index=136, Impact Factor=6.0]
  2. " Adaptive Knowledge Fusion Ratio-Based Knowledge Distillation", Pattern Recognition, Elsevier, 2024 [H-index=118, Impact Factor=7.5]
  3. "Anchor-Based Void Detouring Routing Protocol In Three Dimensional IoT networks", Computer Networks, Elsevier, 2023 [H-index=93, Impact Factor=4.4]
  4. " Divide and Distill: New Outlooks On Knowledge Distillation for Environmental Sound Classification, IEEE/ACM Transactions on Audio, Speech, and Language Processing, (IEEE TASLP), Vol.31, Page.1100-1113, 2023, [H-index=74, Impact Factor=5.4]
  5. "When Sub-Band Feature Meets Attention Mechanism While Knowledge Distillation for Sound Classification," Applied Acoustics, Elsevier, Vol.195, Page.108813, 2022, [H-index=65, Impact Factor=3.614]
  6. "Data Augmentation Guided Knowledge Distillation for Environmental Sound Classification", Neurocomputing, Elsevier, Vol.489, Page 59-77, 2022 [H-index=136, Impact Factor=6.0]
  7. "(Adv-ESC): Adversarial Attack Datasets for An Environmental Sound Classification", Applied Acoustics, Elsevier, 108437, Vol.185, 2021, [H-index=65, Impact Factor=3.614]
  8. "Environment Sound Classification Using An Attention-Based Residual Neural Network," Neurocomputing, Elsevier, Vol.460, Page 409-423, [H-index=136, Impact Factor=6.0]
  9. "Self-Supervised Learning for Environmental Sound Classification," Applied Acoustics, Elsevier, 108183, Vol.182, 2021. [H-index=65, Impact Factor=3.614]
  10. "Oil Well Drilling Activities Recognition Using a Hierarchical Classifier", Journal of Petroleum Science & Engineering, 107883, Vol.196, 2021. [H-index=95, Impact Factor=5.168]

Refereed Conference

  1. "When Visual State Space Model Meets Backdoor Attack ", IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 28 Feb-4 March, 2025, Tucson, Arizona . [Core Rank=A*] [Accepted]
  2. "Bandit Based Attention Mechanism in Vision Transformer", IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 28 Feb-4 March, 2025, Tucson, Arizona . [Core Rank=A*] [Accepted]
  3. "TM-PATHVQA: 90000+ Textless Multilingual Questions for Medical Visual Question Answering ", Conference of the International Speech Communication Association (INTERSPEECH), Sept 1-5, 2024, Kos Island, Greece. [Core Rank=A*]
  4. "Towards Multi-Lingual Audio Question Answering", Conference of the International Speech Communication Association (INTERSPEECH), Aug 20-24, 2023, Dublin, Ireland. [Core Rank=A*]
  5. "Sub-band Contrastive Learning-based Knowledge Distillation for Sound Classification," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), June 4-10, Rhodes Island, Greece, 2023 [Core Rank=A*]
  6. "Temporal Self-Attention-Based Residual Network for An Environmental Sound Classification," Conference of the International Speech Communication Association (INTERSPEECH), Sept 18-22, 2022, Incheon, Korea. [Core Rank=A*]
  7. "Revamped Knowledge Distillation for Environmental Sound Classification," IEEE International Joint Conference on Neural Networks (IJCNN), July 18-23, 2022, Padua, Italy.[Core Rank=A]
  8. "Reverse Adversarial Attack To Enhance Environmental Sound Classification," IEEE International Joint Conference on Neural Networks (IJCNN),July 18-23, 2022, Padua, Italy. [Core Rank=A]
  9. "Defensive Bit Planes: Defense Against Adversarial Attacks," IEEE International Joint Conference on Neural Networks (IJCNN),July 18-23, 2022, Padua, Italy. [Core Rank=A]
  10. Investigation of Performance of Visual Attention Mechanisms for Environmental Sound Classification: A Comparative Study", IEEE International Joint Conference on Neural Networks (IJCNN),July 18-23, 2022, Padua, Italy.[Core Rank=A]
  11. "Adv-IFD: Adversarial Attack Datasets for An Intelligent Fault Diagnosis", IEEE International Joint Conference on Neural Networks (IJCNN),July 18-23, 2022, Padua, Italy. [Core Rank=A]
  12. "Enhancing Multivariate Time Series Classification Using Long Short Term Memory and Evidence Feed Forward HMM, IEEE International Joint Conference on Neural Networks (IJCNN), July 19-24, 2020, Glasgow, UK, [Core Rank=A]
  13. "Multivariate Time Series Classification With An Attention-Based Multivariate Convolutional Neural Network", IEEE International Joint Conference on Neural Networks (IJCNN), July 19-24, 2020, Glasgow, UK, [Core Rank=A]
  14. "Acoustic Event Detection Using Oriented Fuzzy Local Binary Pattern and Ensemble of Convolutional Neural Network", IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July 19-24, 2020, Glasgow, UK, [Core Rank=A]
  15. "Contextual Anomaly Detection in Time Series Using Dynamic Bayesian Network", Asian Conference on Intelligent Information and Database Systems, Phuket, Thailand, March 26-29, 2020,[Core Rank=B]
  16. "Anomaly Detection in Multivariate Time Series Using Fuzzy AdaBoost and Dynamic Naive Bayesian Classifier", in Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (SMC), Bari, Oct 6-9, 2019, Italy., [Core Rank=B]
  17. "Incremental Cauchy Non-Negative Matrix Factorization and Fuzzy Rule-based Classifier for Acoustic Source Separation", in Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), June 23-27, 2019, New Orleans, USA, [Core Rank=A]
  18. "Acoustic Event Classification Using Cauchy Non-Negative Matrix Factorization and Fuzzy Rule-Based Classifier", in Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July 9-12, 2017, Naples, Italy, pp.1-6, [Core Rank=A]
  19. "Anomaly Detection in Data Streams Based on Graph Coloring Density Coefficients", in Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI), Dec 6-9, 2016, Athens, Greece, pp.1-7, [Core Rank=C]
  20. "Acoustic Event Classification Using Ensemble of One-Class Classifiers for Monitoring Application", in Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI), Dec 7-10, 2015, Cape Town, South Africa, pp.1681-1686, [Core Rank=C]
  21. "Acoustic Sensor Based Activity Recognition Using Ensemble of One-Class Classifiers", in Proceedings of IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) , Dec 1-3, 2015, Duoai, France, pp.1-7, [Core Rank=C]
  22. "Ultrasonic Sensor-based Human Detector Using One-Class Classifiers", in Proceedings of IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), Dec 1-3 ,2015, Duoai, France, pp.1-6., [Core Rank=C]

Teaching

  1. Compilers (CS 323) (Jan-May 2025)
  2. Compilers Lab (CS 316) (Jan-May 2025)
  3. Database Management & Information Systems (Theory) (CS 303) (Aug 2024- Nov 2024)
  4. Database Management & Information Systems (Lab) (CS 313) (Aug 2024- Nov 2024)
  5. Compilers (CS 323) (Jan-May 2024)
  6. Compilers Lab (CS 316) (Jan-May 2024)

Students

BTP

  1. Sankalp Nagaonkar (B.Tech-IV Year) (EECS) (2024) [Topic= Backdoor Attacks and Knowledge Distillation]
  2. Om Suhash Deshmukh (B.Tech-IV Year) (CSE) (2024) [Topic= Architectural Backdoor Attacks]
  3. Vivek Pillai (B.Tech-IV Year) (CSE) (2024) [Topic=Memory-Efficient Deep Models for Audio Classification]
  4. Ayush Singhi (B.Tech-IV Year) (EECS) (2024) [Topic= High-Performance Deep Models for Audio Classification]
  5. Agrim Jain (B.Tech-IV Year) (CSE) (2024) (Co-op Internship) [Topic= Efficient Page Ranking Algorithms for MakeMyTrip.com]

Research & Development

  1. Sankalp Nagaonkar (B.Tech-III Year) (EECS) (2024) [Topic= Adaptive Knowledge Fusion Ratio-Based Knowledge Distillation]
  2. Tanisq Trivedi (B.Tech-III Year) (CSE) (2024) [Topic= Adversarial Audio Classification: An Empirical Study]
  3. Samriddha Chattopadhyay (B.Tech-IV Year) (EECS) (2024) [Topic= Heterogeneous Continual Learning Using Knowledge Distillation]
  4. Sadok Chakma (B.Tech-IV Year) (EECS) (2024) [Topic= Adversarial Heterogeneous Continual Learning]

Projects

1. Automatic Diarization of Multiple Speakers in Audio Recordings Using AI/ML Algorithms for Mandarin Language (Funding Agency: DRDO Young Scientist Laboratory (DYSL-CT)) (Principal investigator)

Achievements

  1. Recipient of IEEE Registration Grant For IEEE International Joint Conference on Neural Networks (IJCNN), July 19-24, 2020, New Glasgow, UK
  2. Recipient of IEEE CIS Travel Grant To Attend IEEE International Joint Conference on Neural Networks (IJCNN), July 19-24, 2020, New Glasgow, UK
  3. Recipient of IEEE Registration Grant For IEEE International Conference on Fuzzy Systems (FUZZ- IEEE), July 19-24, 2020, New Glasgow, UK
  4. Recipient of IEEE CIS Travel Grant To Attend IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July 19-24, 2020, New Glasgow, UK
  5. Recipient of IEEE CIS Travel Grant To Attend IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), June 23-27, 2019, New Orleans, USA
  6. Recipient of Travel Grant to Attend Microsoft AI-Research Summit (2018), IIIT-Hyderabad
  7. Recipient of Prestigious PAN-IIT ONGC Scholarship for Ph.D. (2016-2021)
  8. Recipient of MHRD Research Scholarship (2014-2019)