Sphoorthy Nadimpalli

About Sphoorthy

I am a biotechnology graduate with exposure to bioinformatics, immunology, pharmaceutical biotechnology, molecular biology, biochemistry, biophysics, and laboratory instrumentation. During my undergraduate years, I also gained experience in mathematics and computation using C and Python, which helped me start putting the pieces of the puzzle together. In one of the workshops conducted by IIT Kharagpur, I was introduced to computer-aided drug discovery. With the workshop I gained knowledge about various drug design methods. For the final year project seminar, I presented Quantum Computing potential for in-silico protein folding. With specializations in deep learning and courses on machine learning, I was accepted as a junior developer for Cognizant in the Artificial Intelligence and Analytics domain. I worked with Cognizant first as an intern. I worked as a full-time Data Analyst for the next year. With this experience I was accepted as a Data Scientist- biomedical engineering with Paninian India Pvt Ltd I worked on a solution architecture for clinical trial optimization using a digital twin of the human heart.

Later, I decided to embark on a journey into quantum computing due to its potential impact on my field, especially in the area of protein folding. I enrolled for a course “Introduction to Quantum Computing”, taught by MIT researchers and sponsored by IBM Quantum in collaboration with the coding School. And I was given the Student Assistantship for the same. I implemented a few quantum algorithms like Grover’s Search and protocols like Quantum Secure Direct Communication, VQE, etc. I then participated in hackathons to connect with peers of similar interests. Our team Sybil-Sys was the winning team in Quantum Science and Technology Hackathon 2022, named “Qule”- exploring chemical infinities where we used hybrid Quantum Generative Adversarial Networks to generate small molecules. With this project I understood the need for efficient algorithms in molecular sciences and the computational complexity the current algorithms have, to deal with the size of systems.

We were the runner-up team for IEEE 11th International Conference where we explored the market for computational methods in novel drug discovery, which currently takes around 2.5 billion US5D and 10-15 years of time. We got an opportunity to present our work on Quantum Computing for drug discovery to one of the best startup incubators of India T-hub and a Quantum startup incubator Qubit Ventures USA.

I also got the opportunity to give a talk at Quantum Tech APAC conference Singapore, which was an invite-only conference with the leaders of quantum. Now I am gaining a deeper understanding in Quantum Chemistry, and Quantum material design at Kyushu University.

I wish to globalize and work with people of similar interests, share and build ideas that can impact the domain and in turn contribute to the society around, in the best of my capacity. To this end, I am looking to connect with researchers at Japanese pharmaceutical companies working on:
1. Quantum chemistry in drug delivery design methodologies;
2. Ab initio quantum chemistry modeling;
3. Computational methods to support drug efficacy testing across imaging modalities, including high throughput assays, PBMCs, PET, and other structural imaging methods, such as cryoEM.
If this is you, please reach out to me! I would love to schedule some time to chat.