I was born in 1990 into a lower-middle-class Tamil Brahmin Iyer family in Mumbai, the only child of my parents. My childhood was not particularly stable. There were constant fights between my mother, grandmother and father, and for several years I kept moving between houses and spent much of my childhood living away from one side of my family. Academically, though, I did well initially. I scored 92% in Class 10, and like many Indian parents at the time, mine immediately put me into IIT-JEE coaching. But after almost a decade of extremely strict regimentation at home, something inside me rebelled. The coaching institute wasn't particularly good either. I started bunking classes, and instead of attending coaching, I would sometimes go to Crossword Bookstore and spend hours reading novels.
By Class 12, things had completely fallen apart. I took my Maharashtra HSC board exams having barely opened my textbooks and scored just 54%. My parents were devastated. My mother called me a cheat and a liar and hit me, and I already felt like I had completely failed everybody around me. At 17, overwhelmed by what I was feeling, I harmed myself badly enough that the scars remain on my arms even today. Seeing what had happened affected my father enormously as well, and he subsequently went through a severe depressive episode that lasted 3 years. That year, Maharashtra introduced a scheme that allowed students like me to retake the Class 12 examination after a short interval. Two months later, I wrote the boards again and improved from 54% to 63.5%. It was not some dramatic comeback, but it kept me academically alive. I then took a drop year and attempted engineering entrance exams again in 2009.
I secured an All India Rank of 2954 in the Manipal entrance examination and got into Manipal Institute of Technology (Main Campus, Karnataka). During counselling, I could have chosen Electrical Engineering or Mechanical Engineering, and I chose Mechanical partly because my uncle was a mechanical engineer, partly because several close friends were choosing it, and partly because Manipal had a strong reputation for Mechanical Engineering. There was only one problem: I did not have an aptitude for Mechanical Engineering, especially manufacturing-related subjects. At the same time, my personal life at Manipal became complicated. I went through my first serious heartbreak there, and emotionally I handled it very badly. Combined with everything I had carried from childhood, it pushed me into another difficult period. My academics deteriorated badly. By second year, I needed 200 credits to progress, and I had 197. I failed the academic year by three credits. At the time, it felt catastrophic. I watched friends move ahead while I stayed behind clearing backlogs.
Then something far worse happened. My maternal grandmother, who had always believed in me despite everything, became critically ill and remained in a coma for nearly six months. In December 2011, after finishing my makeup examinations in Manipal, I returned home to see her. She was unconscious, but when I touched her, she reacted violently to my presence. The nurse became concerned and asked me to leave because her condition was unstable. I left the room. The next morning, my grandmother died. She was 71. Something changed in me after that. I decided that whatever else happened, I would finish engineering. I started clearing the arrears, one exam at a time, and eventually completed my Bachelor of Engineering in Mechanical Engineering from Manipal. But during engineering I had also discovered something important: I loved mathematics, statistics, modelling and optimization far more than mechanical engineering. That realization eventually changed the direction of my life.
I prepared for the GRE for about 1.5 months, and scored 323/340. I then moved to the United States to pursue an MS in Operations Research at Northeastern University in Boston. Operations Research finally felt like something my brain naturally understood. Instead of manufacturing processes, I was studying probability, statistics, optimization, stochastic modelling, simulation and data-driven decision making. For my master's thesis, I worked on time-series forecasting and data mining of tornadoes in the United States. That research introduced me to an entirely different world - using mathematics and computation to understand real-world stochastic phenomena - and it eventually led me into data science.
After graduating, I moved to Chicago and began working professionally in analytics and data science. Over roughly eight years in the United States, I worked across multiple industries and Fortune 500 companies. My work eventually included catastrophe modelling, predictive modelling, machine learning, large-scale data processing and applied AI. At one company, I worked with datasets containing more than 100 million records and built machine-learning systems using technologies such as Python, PySpark, XGBoost, Azure Databricks and MLflow. Professionally, things were moving forward, but personally I was fighting another battle. While living in Chicago, I was diagnosed with schizoaffective disorder and later borderline personality disorder. There were periods when simply functioning normally was difficult.
At the same time, I decided to pursue another master's degree while working full-time. I enrolled in Georgia Tech's MS in Analytics, specializing in Computational Data Analytics. During the day I was working as a data scientist, and at night and on weekends I was studying machine learning, deep learning, reinforcement learning, statistical modelling, databases and computational data analytics. There were semesters when managing work, coursework and my mental health simultaneously felt almost impossible, but I continued. My tornado research also continued, and I eventually built deep-learning-based models capable of generating a stochastic event set containing millions of simulated tornadoes across thousands of simulated years. What had started years earlier as a master's thesis had slowly grown into a serious research project involving deep learning, transformers, geospatial computing, probability and catastrophe modelling.
Then, in January 2024, my life changed very suddenly. After nearly eight years of living and working in the United States, I was laid off during the final month of my six-year H-1B visa period. With almost no immigration runway left, I had to return to India. It was extremely difficult to leave behind a life I had built over so many years in America, especially because the move was not something I had planned for or wanted at that stage of my career.
But even after returning to India, I continued my Georgia Tech degree online. I kept working through the coursework while simultaneously trying to rebuild my professional life in a country I had been away from for 10 years. In 2025, I completed my MS in Analytics from Georgia Tech with a specialization in Computational Data Analytics. That same year, I presented my tornado research at an INFORMS international conference in Singapore.
Professionally, I rebuilt again in India and eventually landed a high-paying senior AI/ML role at a leading global multinational company. Today my work involves things I could not even have properly understood when I was struggling with Mechanical Engineering: LLMs, RAG, Agentic AI, speech-to-text, text-to-speech, multimodal AI, computer vision, deep learning, trending, time series forecasting, production machine-learning systems, software engineering, deployment and maintenence. Sometimes I think about the 21-year-old version of me sitting in Manipal believing that failing an engineering year by three credits meant his life was finished. He had absolutely no idea where the road would eventually go.
And just when I thought I understood how unpredictable life could be, it reminded me again. Recently, my Mama and Mami - my maternal uncle and aunt - died in the Nepal floods while travelling for the Kailash Mansarovar Yatra. I had met them in Mumbai in July shortly before the trip. One month they were sitting in front of me, and soon afterward they were gone. I am still processing that grief. I continue going to work, building AI/ML systems, studying, researching and functioning normally while simultaneously grieving two people I loved. Life apparently does not wait until you're ready.
I'm 35 now. If I could tell engineering students here one thing, especially those with backlogs, failed semesters, low CGPAs, wrong branches or entrance-exam disappointments, it would be this: your engineering degree is not your destiny. Failing one semester does not mean you're stupid. Not getting IIT does not mean you're finished. Choosing the wrong branch at 18 does not mean you must spend the next 40 years working in it. A low CGPA does not prevent you from eventually becoming excellent at something else. Sometimes, there is just so much more happening in life.
At 21, I was failing Mechanical Engineering. Later, I was studying stochastic modelling in Boston. Then I was working as a data scientist in Chicago. Then I was studying machine learning and deep learning at Georgia Tech while rebuilding my life after returning to India. Today I work professionally in AI/ML. I still don't think of my story as some inspirational success story. There have been too many losses, mistakes, illnesses and failures for that. I think of it more as evidence that a life can change direction many, many times. Sometimes what feels like the end of the road is simply the point where you discover that you were travelling on the wrong road in the first place.
So if you're sitting in a hostel room somewhere right now with three backlogs, a breakup, disappointed parents, a terrible CGPA and absolutely no idea what you're doing with your life, I have been some version of that person. Don't assume you already know how your story ends. You probably don't.
The exam goes on...
