The Boy Who Took Apart Toys to Satisfy His Curiosity and Became an AI Professor
पुस ६, २०८२ १५:८
Kathmandu: Almost five decades ago, a boy would often stare out the classroom window at Vishwaniket, one of the capital’s old schools. He showed little interest in what the teacher wrote on the board. The lessons felt outdated. The teaching felt dull. But once he returned home, his room turned into a laboratory.
He could not keep a new toy intact for more than a week. Toys bought lovingly by his father were taken apart piece by piece. He examined their inner mechanisms. The toys broke. His curiosity did not. Each dismantled toy answered one question: “How does it work?” That boy was Dr. Suresh Manandhar, who today teaches artificial intelligence at Madan Bhandari University of Science and Technology.
His parents worried about his childhood shyness and lack of interest in formal studies. They feared for his future. “This boy won’t even pass SLC. He never studies. What will become of him?” they would wonder. Time proved them wrong. For the past 35 years, the boy once labeled a failure has been teaching AI at universities in Nepal and abroad.
Having spent much of his academic life in the UK, he is now leading efforts to position Nepal as a serious player in artificial intelligence.
The Foundation of Engineering Built on Curiosity
Manandhar’s academic journey was far from smooth. He struggled during school and passed SLC in the second division. Concerned that his son might stagnate, his father made a difficult decision. He sent Suresh to Delhi. “My father decided not to keep me in Nepal after I passed SLC,” Manandhar recalls. “He sent me to Delhi so I would focus on my studies.”
The academic environment in Delhi was far more competitive than in Kathmandu. At first, he struggled to cope. But his desire to create and understand never faded. Through persistence, he adapted. He later completed his bachelor’s degree in Electrical and Electronics Engineering from South India. “The level of education there was very different,” he says. “I had to work much harder. That effort made the rest of my studies easier.”
Toward the end of his engineering program, he encountered programming for the first time. Computers were rare. FORTRAN programs were written on paper and fed into machines using binary input. This world fascinated him. He realized he could create complex systems without wires or soldering irons. “I felt this field was made for me,” he recalls. “I could build things just by thinking and writing code.”
After completing his studies, he returned to Nepal in 1983, eager to work. At the time, the National Computer Center in Singha Durbar needed technical manpower. Following a brief interview, he was hired immediately. “I wanted to apply what I had learned,” he says. “They told me to start work the very next day.”
This marked his first professional step. Computer technology was just entering Nepal. Programming was done using punch cards.
A minor error could cause the machine to throw cards into the air, forcing programmers to start over.
“If even one card was lost, the entire program was ruined,” he recalls. During this period, a question kept troubling him. “Why does the computer only understand machine language? Why can’t it understand human language? Why not Nepali?”
That question led him to artificial intelligence.
Discovering AI and Building Nepal’s First Language System
Around 1985, he began studying AI through libraries and research papers. He realized this was a field he could dedicate his life to. He later went to the University of Essex, where he completed his master’s degree in AI.
After returning to Nepal in 1987, he co-founded Professional Computer Systems (PCS) with Suresh Regmi, Sushil Pradhan, and Deepak Lal Shrestha. The company began in a small space near his kitchen. PCS went on to develop Nepal’s first Nepali-language data processing system. It was later used in the 1991 (2048 BS) national census.
Despite this success, Manandhar felt drawn to deeper research. “I wanted to be a researcher and an academic rather than an entrepreneur,” he says. “There was still so much to learn and teach.”
He handed over PCS to his colleagues and returned to the UK in 1988 to pursue a PhD at the University of Edinburgh, then a global hub for AI research. He focused on natural language processing and completed his PhD by 1993. He formally graduated in 1994.
Teaching, Research, and the AI Winter
After working as a research fellow in Edinburgh from 1992 to 1996, he joined the University of York as a lecturer. The next 23 years were among the most productive of his life. He rose from lecturer in 1996 to Reader in Computer Science in 2013. From 2015 to 2019, he led the university’s AI Research Group and supervised around 24 PhD students.
This period also coincided with the global “AI Winter.” Governments and funding agencies lost faith in AI. “Even other computer scientists looked at us as if we were wasting time,” he recalls. “The UK government stopped funding AI research.” Still, he persisted. He shifted from symbolic AI to statistical machine learning and later to deep learning. After 2012, advances in GPU computing transformed the field. AI surged. His research became part of the foundation of modern AI systems.
Returning Home to Teach Nepal
Despite professional success and comfort in the UK, his commitment to Nepal never faded. In 2019, he returned home, a decision that surprised many. “I could learn anywhere,” he says. “But in Nepal, I could teach AI to a new generation and strengthen the country’s tech ecosystem.”
After returning, he immersed himself fully in Nepal’s AI movement. He served as director of the NAAMII AI Research Institute from 2019 to 2020, working to connect Nepali students with global research. He also worked as Head of AI Research at Fusemachine from 2019 to 2025, helping expand AI education nationwide.
His most prominent entrepreneurial venture is WiseYak, founded in 2017. He serves as its CEO, Chief Scientist, and Co-Founder. Through WiseYak, he is applying AI to healthcare. The company is developing AI-based cervical cancer screening technology aimed at developing countries. The system allows even basic healthcare workers to detect early signs of cancer.
He is also working on digitizing hospital records according to international standards, enabling secure data transfer between hospitals. “IT in Nepal cannot be limited to outsourcing,” he says. “We must build original products here and compete globally.”
Looking Ahead
Currently, Prof. Manandhar is working on a voice-to-voice AI system capable of understanding Nepali, Maithili, and other local languages. The goal is to make AI accessible to people with limited literacy or technical knowledge. “If a farmer can ask AI about crop diseases in his own language and get spoken answers, that is true democratization of technology,” he says.
This initiative is supported by Madan Bhandari University of Science and Technology, where he serves as honorary chair of AI and continues to help develop high-level AI manpower.
His journey began with punch cards 35 years ago. Today, it spans generative and agentic AI. “In the future, software will not just be a tool,” he says. “It will be a helper. We will talk to software and make it work. My goal is to prepare Nepal for that future.”
The boy once dismissed as boring, who broke household items in search of answers, is now a pioneer of Nepal’s technology sector. Through his work, he continues to mentor and support more than 40 professionals dedicated to advancing AI in Nepal.
पछिल्लो अध्यावधिक: पुस ७, २०८२ ९:५८
