"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

Continual Learning

Continual Distillation, Incemental Learning

New Highlights and Announcements

  1. ( Paper Accepted: IEEE TAI 2025)→ MalaNet: A Small World Inspired Neural Network for Automated Malaria Diagnosis (Congratulations to All Co-Authors)
  2. Students who wish to pursue an R&D/BTP project in the next semester are encouraged to begin their research work at the start of the summer vacation, ensuring that their hard work leads to a productive and fruitful research outcome without delay and is completed by the end of the next semester.
  3. I am seeking highly motivated B.Tech students with exceptional coding skills and a strong foundation in mathematics to join my research group. If you have a CGPA of 9.0 or higher and are eager to contribute to BTP/R&D projects in this area, please send me your detailed CV. Just so you know, BTP will not be offered until a student has completed R&D work under my supervision. BTP will be considered if the student’s performance in R&D meets expectations. I am particularly interested in students who are committed to pursuing higher studies and are willing to invest significant time in publishing research articles in top venues. Additionally, 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. I am not interested in offering any Short-Term Internships, Online Internships, or Mini-Projects for the next few years.

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. " MalaNet: A Small World Inspired Neural Network for Automated Malaria Diagnosis," IEEE Transactions on Artificial Intelligence (IEEE-TAI), 2025 (Accepted)
  2. "Anchor-Based Void Detouring Routing Protocol In Three Dimensional IoT networks," Computer Networks, Elsevier, 2023 [H-index=93, Impact Factor=4.4]
  3. " 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]
  4. "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]
  5. "Data Augmentation Guided Knowledge Distillation for Environmental Sound Classification", Neurocomputing, Elsevier, Vol.489, Page 59-77, 2022 [H-index=136, Impact Factor=6.0]
  6. "(Adv-ESC): Adversarial Attack Datasets for An Environmental Sound Classification", Applied Acoustics, Elsevier, 108437, Vol.185, 2021, [H-index=65, Impact Factor=3.614]
  7. "Environment Sound Classification Using An Attention-Based Residual Neural Network," Neurocomputing, Elsevier, Vol.460, Page 409-423, [H-index=136, Impact Factor=6.0]
  8. "Self-Supervised Learning for Environmental Sound Classification," Applied Acoustics, Elsevier, 108183, Vol.182, 2021. [H-index=65, Impact Factor=3.614]
  9. "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. "Semi-Supervised Knowledge Distillation Framework Towards Lightweight Large Language Model for Spoken Language Translation", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 6-11, Hyderabad, India, 2025 [Core Rank=A*]
  2. "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*]
  3. "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*]
  4. "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*]
  5. "Towards Multi-Lingual Audio Question Answering," Conference of the International Speech Communication Association (INTERSPEECH), Aug 20-24, 2023, Dublin, Ireland. [Core Rank=A*]
  6. "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*]
  7. "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*]
  8. "Revamped Knowledge Distillation for Environmental Sound Classification," IEEE International Joint Conference on Neural Networks (IJCNN), July 18-23, 2022, Padua, Italy.[Core Rank=A]
  9. "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]
  10. "Defensive Bit Planes: Defense Against Adversarial Attacks," IEEE International Joint Conference on Neural Networks (IJCNN),July 18-23, 2022, Padua, Italy. [Core Rank=A]
  11. 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]
  12. "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]
  13. "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]
  14. "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]
  15. "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]
  16. "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]
  17. "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]
  18. "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]
  19. "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]
  20. "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]
  21. "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]
  22. "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]
  23. "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

I have only two BTP and two R&D positions available in my group. Kindly avoid applying if the positions are already filled, as I will not be able to offer a position in that case.

BTP

  1. Om Suhas Deshmukh (B.Tech-IV Year) (CSE) (2025) [Topic= Architectural Backdoor Attacks, Continual Learning and Deep Reinforcement Learning] [Ongoing]

Research & Development

  1. Prachet Vikas Rane (B.Tech-II Year) (CSE) (2027) [Topic= Continual Learning] [Ongoing]
  2. Pranav Kumar Pandey (B.Tech-III Year) (CSE) (2026) [Topic= Machine Unlearning] [Ongoing]
  3. Sankalp Nagaonkar (B.Tech-III Year) (EECS) (2025) [Topic= Adaptive Knowledge Fusion Ratio-Based Knowledge Distillation and Backdoor Attacks] [Completed]
  4. Tanisq Trivedi (B.Tech-III Year) (CSE) (2025) [Topic= Adversarial Audio Classification: An Empirical Study] [Completed]

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)

2. AI-Enhanced Non-Invasive Wearable Patch for Early Heart Attack Prediction via Real-Time Cardiac Troponin-I Monitoring Using a Pseudoknot-Engineered Aptamer(Funding Agency: ANRF) (Co-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)