Priyanka Chandra

Skilled multitasker with superior work ethic and good teamwork, problem-solving and organizational skills. Willing to take on any task to help team. Reliable and dedicated team player with hardworking and resourceful approach. Hardworking Student offering part-time work experience and extensive knowledge of core subject matter. Meticulous and detail-oriented with excellent observational, organizational and communication skills.

• Artificial Neural Networks
• Computational Fluid dynamics

Physics Informed Neural Networks for bioconvective nanofluid flows

• 2024-08-01, Awarded for 2 review contribution in the journal "Engineering application of artificial Intelligence" [Elsevier, SCI-Q1-Impact factor- 8.0]
• 2024-02-01, Presented a Contributory talk on "An Accelerated finite element method to study the gyrotactic-nanofluid flows" in the conference hosted by "School of Mathematics, IISER Thiruvananthapuram".
• 2023-06-01, Attended Teacher Enrichment Workshop (TEW) at VIT, Vellore hosted by National Centre of Mathematics (TIFR and IIT Bombay).
• 2023-05-01, Participated in 5 days FDP on Optimization Techniques for AI/ML/DS Models organized by "Indian Institute of Information Technology (IIT), Kottayam, Kerla".
• 2019-12-01, Attended workshop program organised by NATIONAL ACADEMY OF SCIENCE, ALLAHABAD (NASI).

• Design of a unified physics-informed neural network using interior point algorithm to study the bioconvection nanofluid flow via stretching surface, Engineering Applications of Artificial Intelligence, Elsevier, SCI-Q1, 8.0, 2024-01-01
• A hybrid RSA-IPA optimizer for designing an artificial neural network to study the Jeffery-Hamel blood flow with copper nanoparticles: Application to stenotic tapering artery, Results in Engineering, Elsevier, SCI-Q2, 5.0, 2023-01-01
• A hybrid machine learning algorithm for studying magnetized nanofluid flow containing gyrotactic microorganisms via a vertically inclined stretching surface, International Journal for Numerical Methods in Biomedical Engineering, Wiley, SCI-Q2, 2.4, 2023-01-01
• Finite-element-based machine-learning algorithm for studying gyrotactic-nanofluid flow via stretching surface, International Journal for Numerical Methods in Fluids, Wiley, SCI-Q3, 1.7, 2023-01-01
• Impact of gyrotactic microorganisms in nanofluid via porous media along an inclined stretching plate: Finite element analysis, Numerical Heat Transfer Part B: Fundamentals, Taylor & Francis, SCI-Q3, 1.8, 2023-01-01