Dr. Tanya Liyaqat

About

Dr. Tanya Liyaqat is a dedicated professional deeply committed to both teaching and research, particularly in the fields of artificial intelligence and machine learning. She holds a B. Tech in Computer Science and Information Technology from MJP Rohilkhand University, Bareilly, and an M. Tech in Computer Engineering from Jamia Millia Islamia University, Delhi. She completed her Ph.D. at Jamia Millia Islamia University, her research focuses on the application of machine learning in drug discovery. With over six plus years of research experience, Tanya has made significant contributions to her field, evident through her multiple research publications and presentations at international conferences. Her academic journey is complemented by certifications including GATE and NET qualifications, a JRF award, and several professional certifications in data science and machine learning fundamentals. Tanya's areas of expertise and interest encompass Artificial Intelligence (AI), Natural Language Processing (NLP), and Bioinformatics, reflecting her passion for leveraging advanced technologies to drive innovation in scientific research and education.

Experience

• 1+ Years experience as Assistant Professor

Qualification

• B. Tech (CS/IT)
• M. Tech (Computer Engineering)
• Ph.D. (Computer Engineering) (pursuing)

Award & Recognition

• Successfully qualified the Graduate Aptitude Test in Engineering (GATE) in 2017 and 2019.
• Attained the National Eligibility Test (NET) certification for Teaching in 2017.
• Awarded the NET-Junior Research Fellowship (JRF) in 2018.

Research

Total Research -

• T Liyaqat, et al. (2024). Advancements in Molecular Property Prediction: A Survey of Single and Multimodal Approaches. Manuscript Published in Archives of Computational Methods in Engineering, Springer Nature Publishing (SCIE Indexed, IP: 12.1, Q1).
• T Liyaqat, et al. (2024). Stacked ensemble-based mutagenicity prediction model using multiple modalities with graph attention network. Manuscript published in Medical & Biological Engineering & Computing, Springer Nature Publishing (SCIE Indexed, IP: 2.6, Q1).
• T Liyaqat, et al. (2023). A machine learning strategy with clustering under sampling of majority instances for predicting drug target interactions. Manuscript published in Molecular Informatics, 42, 5, 2200102, Wiley Online Library (SCIE Indexed, IP: 2.8, Q2)
• T Liyaqat, et al. (2023). TeM-DTBA: time-efficient drug target binding affinity prediction using multiple modalities with Lasso feature selection. Manuscript Published in Journal of Computer-Aided Molecular Design, 37, 12, 573-584, Springer International Publishing (SCIE Indexed, IP: 3.0, Q2).
• T Liyaqat, et al. (2022). A Methodology for the Prediction of Drug Target Interaction Using CDK Descriptors. In 29th International Conference on Neural Information Processing, ICONIP 2022. Communications in Computer and Information Science, vol 1794. Springer, Singapore (Scopus Indexed).
• T Liyaqat, et al. (2022). A brief review on artificial intelligence based drug target interaction prediction. In 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), 2022. Communications in Computer and Information Science, 544-549. IEEE, India (Scopus Indexed).
• T Liyaqat, et al. (2025). AI-Driven Prediction of Drug-Target Interactions and Binding Affinity for Drug Discovery in Healthcare. Chapter Accepted for Publication in the Scopus-indexed volume of the book entitled Artificial Intelligence and Data Science in Healthcare Applications published by CRC Press/Taylor & Francis Group (Scopus Indexed).
• Ms. Tanya Liyaqat et al. (2024). Artificial Intelligence Based Device for the Detection of Cardiac Diseases. The Patent Office, Government of India Patent No. 432522-001. Registration Date: 02/10/2024.

Certifications

• Earned a Professional Certificate in Data Analysis from Coursera.
• Completed the 'Deep Learning Fundamentals' certification from Cognitive Class.
• Received an NPTEL ‘ELITE certificate for achieving a score of 71% in the course 'Bioinformatics: Algorithms and Applications' in 2024.
• Participated in the Faculty Development Program (Online) titled " Next-Generation Computing: Trends and Challenges in Research” organized by Department of CSA, SSCSE, Sharda University held from 25th March to 29th March 2025.
• Served as the reviewer during the 5th International Conference on Advances and Applications of Artificial Intelligence and Machine Learning (ICAAAIML-2025) held on 18th -19th July, 2025, organized by Sharda School of Computing Science & Engineering, Sharda University, Greater Noida, Uttar Pradesh, India.
• Participated in an online Program on “Medical Image Processing” jointly organized by the Electronics and ICT Academies at IIT Roorkee, MNIT Jaipur, NIT Patna, PDPM IIITDM Jabalpur and NIT Warangal.
• Participated in the online Faculty Development Programme on "PYTHON PROGRAMMING LANGUAGE" organized by the Department of Computer Engineering, Jamia Millia Islamia, New Delhi in association with Spoken Tutorial, IIT- Bombay.
• Participated in a workshop on “Technological Advancements in Digital Healthcare” conducted by the digital healthcare unit at the Department of Electrical Engineering, Jamia Millia Islamia in collaboration with Jamia Hamdard under the scheme STUTI, DST.
• Participated in “Workshop-cum-Training Programme on Advanced Artificial Intelligence Techniques” at the Department of Computer Science, Jamia Millia Islamia, New Delhi.
• Participated in IEEE International Symposium on “Internet of Things: Smart Innovation & Usages (IOT-SIU-2016)” at the Faculty of Engineering and Technology, MJP Rohilkhand University, Bareilly.

Area of Interest

• Machine Learning, Deep Learning, Natural Language Processing, Bioinformatics, Health informatics, Drug Discovery, Health informatics