"Dear Niyar R Barman, On behalf of the EMNLP 2023 Program Committee, we are delighted to inform you that the following submission has been accepted to appear at the conference."
Upon receiving the e-mail that my submission was accepted for the EMNLP 2023 conference, I had a profound realization about my career path. This moment marked a turning point in my journey, leading me to choose research and academia over the corporate sector. After a challenging year due to COVID-19 restrictions in India, I began my college journey in July 2022. I soon noticed that many of my peers were trying to secure corporate positions and were intensely focused on solving competitive
programming questions. It reminded me of the high-pressure environment of the Joint Entrance Examination (JEE), a path I had already traversed and was eager to leave behind.
My initial plan was to complete my bachelor's degree and pursue an MBA, tempted by the high salaries in the corporate world. However, I soon realized that this path did not align with my passion and interests. I have always been deeply fascinated by mathematics and physics, subjects that have held a special place in my heart. My introduction to CERN and the remarkable Large Hadron Collider (LHC) particle accelerator during high school left me in awe. The idea that such groundbreaking scientific endeavors existed truly amazed me.
It was during my freshman year that an opportunity emerged. A college friend invited me to attend a Machine Learning Club orientation, which I initially joined just to accompany him. Little did I know that this would become a turning point in my life. I had previously heard of machine learning and artificial intelligence but was entirely new to the concept of deep learning. The orientation introduced me to the possibilities of this field, and I was inspired by the achievements of our seniors, one of whom
had worked at Amazon as an applied scientist, while another had secured admission to a master's program in Paris. This was my chance to escape the relentless rat race and the monotonous corporate life.
I began my journey with Andrew Ng's machine learning course and deep learning course, followed by participation in basic projects and hackathons. Although I did not win any hackathons initially, my primary goal was not victory but learning and completing projects within tight deadlines and learning to work within a team environment. I led multiple groups in this period and even won a few hackathons even though that was not my goal. This allowed me to become proficient in various machine learning
and deep learning frameworks such as Keras, PyTorch, Tensorflow, and gain expertise in deployment using FastAPI, Flask, AWS, Heroku, and more. I have worked on projects in diverse domains including Computer Vision, Natural Language Processing, and Generative AI. I have also explored Quantum Machine Learning, although my knowledge in this domain is still developing and has not yet made its way onto my resume. I have also gained research experience through internships at Artificial Intelligence Institute of UofSC (AIISC) and Xu lab at Carnegie Mellon University. Working at AIISC, I have had experience working with multiple domains. I have worked with diffusion models, large language models and classical methods at AIISC. In one of the projects I worked on, I developed a pipeline for generating hateful images through stable diffusion, integrated diffusion attentive attribution map to pinpoint areas impacted by hate words. At CMU, I am working on deep learning models for Cryo-ET data analysis and exploring the possibilty of implementing a Visual Question Answering pipeline tailored for single particles from Cryo-EM. I have authored two published papers, one in EMNLP and another in IEEE.
The ongoing research projects at CERN have captured my attention, thanks to their compelling fusion of particle physics and machine learning. "Colliding particles not cars: CERN's application of machine learning for self-driving cars" represents a fascinating convergence of these fields. It demonstrates how advanced machine learning techniques are being harnessed to address challenges that extend beyond the realm of particle physics. Additionally, the project titled "Speeding up machine learning for
particle physics" is equally intriguing. This endeavor harmonizes with my background in data analysis and my proficiency in handling extensive datasets. It offers a distinctive opportunity to contribute to the acceleration of machine learning techniques in the context of particle physics. My strong background in data analysis, along with experience in handling substantial datasets, could be a valuable asset for the innovative research conducted at CERN. I am deeply committed to pursuing a M.S/Ph.D. after completing my bachelor's degree, and I believe that working at a world-renowned research institution like CERN, alongside some of the finest
scientists in the world, would be instrumental in achieving my long-term career goals.
Furthermore, I am drawn to the international working environment at CERN. The prospect of interacting with individuals from diverse cultural backgrounds and experiences is an exciting opportunity for me.
In conclusion, CERN represents the ideal environment for me to further my academic and research aspirations. I bring a strong analytical background and a genuine passion for mathematics and physics, which I believe aligns with the goals and spirit of CERN. Additionally, I've been on a delightful 150-day Duolingo streak to grasp the basics of one of CERN's official languages, French. I might not be ready to debate existential philosophy with a French philosopher just yet, but I can confidently order a
croissant without breaking a sweat!
Merci d'avoir pris en compte ma candidature et j'attends avec impatience de vos nouvelles.
Thank you for your time and consideration
Upon receiving the e-mail that my submission was accepted for the EMNLP 2023 conference, I had a profound realization about my career path. This moment marked a turning point in my journey, leading me to choose research and academia over the corporate sector. After a challenging year due to COVID-19 restrictions in India, I began my college journey in July 2022. I soon noticed that many of my peers were trying to secure corporate positions and were intensely focused on solving competitive
programming questions. It reminded me of the high-pressure environment of the Joint Entrance Examination (JEE), a path I had already traversed and was eager to leave behind.
My initial plan was to complete my bachelor's degree and pursue an MBA, tempted by the high salaries in the corporate world. However, I soon realized that this path did not align with my passion and interests. I have always been deeply fascinated by mathematics and physics, subjects that have held a special place in my heart. My introduction to CERN and the remarkable Large Hadron Collider (LHC) particle accelerator during high school left me in awe. The idea that such groundbreaking scientific endeavors existed truly amazed me.
It was during my freshman year that an opportunity emerged. A college friend invited me to attend a Machine Learning Club orientation, which I initially joined just to accompany him. Little did I know that this would become a turning point in my life. I had previously heard of machine learning and artificial intelligence but was entirely new to the concept of deep learning. The orientation introduced me to the possibilities of this field, and I was inspired by the achievements of our seniors, one of whom
had worked at Amazon as an applied scientist, while another had secured admission to a master's program in Paris. This was my chance to escape the relentless rat race and the monotonous corporate life.
I began my journey with Andrew Ng's machine learning course and deep learning course, followed by participation in basic projects and hackathons. Although I did not win any hackathons initially, my primary goal was not victory but learning and completing projects within tight deadlines and learning to work within a team environment. I led multiple groups in this period and even won a few hackathons even though that was not my goal. This allowed me to become proficient in various machine learning
and deep learning frameworks such as Keras, PyTorch, Tensorflow, and gain expertise in deployment using FastAPI, Flask, AWS, Heroku, and more. I have worked on projects in diverse domains including Computer Vision, Natural Language Processing, and Generative AI. I have also explored Quantum Machine Learning, although my knowledge in this domain is still developing and has not yet made its way onto my resume. I have also gained research experience through internships at Artificial Intelligence Institute of UofSC (AIISC) and Xu lab at Carnegie Mellon University. Working at AIISC, I have had experience working with multiple domains. I have worked with diffusion models, large language models and classical methods at AIISC. In one of the projects I worked on, I developed a pipeline for generating hateful images through stable diffusion, integrated diffusion attentive attribution map to pinpoint areas impacted by hate words. At CMU, I am working on deep learning models for Cryo-ET data analysis and exploring the possibilty of implementing a Visual Question Answering pipeline tailored for single particles from Cryo-EM. I have authored two published papers, one in EMNLP and another in IEEE.
The ongoing research projects at CERN have captured my attention, thanks to their compelling fusion of particle physics and machine learning. "Colliding particles not cars: CERN's application of machine learning for self-driving cars" represents a fascinating convergence of these fields. It demonstrates how advanced machine learning techniques are being harnessed to address challenges that extend beyond the realm of particle physics. Additionally, the project titled "Speeding up machine learning for
particle physics" is equally intriguing. This endeavor harmonizes with my background in data analysis and my proficiency in handling extensive datasets. It offers a distinctive opportunity to contribute to the acceleration of machine learning techniques in the context of particle physics. My strong background in data analysis, along with experience in handling substantial datasets, could be a valuable asset for the innovative research conducted at CERN. I am deeply committed to pursuing a M.S/Ph.D. after completing my bachelor's degree, and I believe that working at a world-renowned research institution like CERN, alongside some of the finest
scientists in the world, would be instrumental in achieving my long-term career goals.
Furthermore, I am drawn to the international working environment at CERN. The prospect of interacting with individuals from diverse cultural backgrounds and experiences is an exciting opportunity for me.
In conclusion, CERN represents the ideal environment for me to further my academic and research aspirations. I bring a strong analytical background and a genuine passion for mathematics and physics, which I believe aligns with the goals and spirit of CERN. Additionally, I've been on a delightful 150-day Duolingo streak to grasp the basics of one of CERN's official languages, French. I might not be ready to debate existential philosophy with a French philosopher just yet, but I can confidently order a
croissant without breaking a sweat!
Merci d'avoir pris en compte ma candidature et j'attends avec impatience de vos nouvelles.
Thank you for your time and consideration
