Mansi Tarani

Undergraduate Researcher

About Mansi

Three years of exposure to pure/applied physics along with experimental analysis in cognitive sciences has led me to develop a keen interest in interdisciplinary research

Research Interests Include: Quantum physics, Quantum computing, Applied Physics, Cognitive Science, Computer Science

I am a highly motivated individual actively involved in the field of physics, quantum computing and cognitive science. I have been in hands-on training in these fields for last three years through which I developed interest and gained knowledge in various paradigms of the research field.

My curiosity to learn and explore new things has driven me to indulge in interdisciplinary research through various projects. In the past three years of undergraduation, I have exposed myself to inter-related topics of research including cognitive science, physics, mathematics, quantum mechanics, and quantum computing. My dissertation research project implements concepts of classical physics and mathematics in determining brain activation level while performing different cognitive tasks.

My technical skills include such as designing and conducting experiments using brain imaging devices mainly, electroencephalography (EEG) for data collection, along with physics lab skills such as working with various digital circuits such as ICs, multiplexers, flip flops, and other classical physics and optics experimentation. My programming skills include knowledge of C++, python, SQL, HTML and MATLAB.

Hands-on training and experimentation with various hardware and software helped me to think creatively, work in various ways to find solutions, and work efficiently. Involving myself into various group projects in hackathons and challenges have helped me learn team skills and develop the quality of leadership and conducting group activities.

I have actively participated in the following summer schools – Introduction to the quantum computing course by Qubit-by-qubit organization on ‘Foundational understanding of quantum computing’. Along with this, I joined Qiskit Global summer school 2020 by IBM, and completed a capstone project on variational quantum classifiers (VQC), then I joined Qiskit Global summer school 2021 on Quantum machine learning by IBM to learn at next level. Before undergraduation, I was selected for a science camp under INSPIRE Internship program by the Department of Science and Technology (DST), a government of India body. My achievements at hackathons include a mention at leaderboard in Qiskit challenge India by IBM and HackerEarth.

I have presented research papers at UGC-SAP 2022 organized by Dayalbagh Educational Institute Committee and also at various conferences including National Systems Conference 2021 organized by Systems Society of India, resulting in a conference publication. I have been awarded with Undergraduate Research Award (UGRA) 2021 by Alumnus society of Dayalbagh Educational Institute, Agra, India for my proposal in interdisciplinary research.

I want to be a part of this role so that I may bring value to my talents and pursue a successful career in quantum physics and quantum computing. If I were chosen, I would take use of this opportunity to learn new things and advance in my profession, to take quantum computing to the next level, and to build the industrial skills required for innovation for the good of humanity.


  • C++
  • HTML
  • Laboratory Skills
  • python
  • Quantum Computing (Qiskit)
  • SQL

Work Experience

Undergraduate Research Assistant
Dayalbagh Educational Institute, Agra
• Analyzed linear and non-linear time series data and interpreted its result • Responsible for subject recruitment, designing, implementation, data analysis and documentation

Education & Training

BSc (Physics honors)
Dayalbagh Educational Institute agra
Linear algebra, Mathematics Analysis, Statistics, Quantum Mechanics, Electronics, Solid State Science, Network theory, and other mathematical and physics courses were completed in a timely manner.
Qiskit Global Summer School
• Developed understanding of quantum chemistry • Applied quantum computing and its application to quantum simulations
Qiskit Global Summer School
• Studied concepts of Classical Machine Learning and linked them to Quantum Computing • Developed fundamental knowledge of Quantum Machine Learning and applied quantum algorithms in the hands-on laboratory session
Qiskit Global Summer School
• Introduced to the world of Quantum Computing, explored and implemented Quantum algorithms in the laboratory sessions. • Completed a project on the V.Q.E model
Introduction to Quantum Computing Course
Qubit by Qubit
• Strengthened concepts of Quantum Computing, explored possible applications and completed all homework • Passed this course with 98 percent
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