About
About me
I am an artist and an engineer with a passion for both Artificial Intelligence (AI) and Very Large Scale Integration (VLSI) engineering.
AI algorithms and VLSI
With a solid foundation in AI, I specialize in developing intelligent systems that harness the power of machine learning and data analysis. Simultaneously, my proficiency in VLSI engineering enables me to design and optimize complex integrated circuits for cutting-edge technology. Explore my projects and portfolio to witness the seamless integration of AI and VLSI in my work.
My Skills
Experience
Senior Design Engineer, Machine Learning
I contribute to the Hexagon Tensor Processor (HTP) team, focusing on deep learning operation kernels and model graph optimization. HTP is the neural processing unit (NPU) designed from the ground up for generative AI, integrated into all Snapdragon chipsets, including the Snapdragon X Series. This role requires me to stay current with state-of-the-art deep learning and generative AI models.
Senior AI Design Engineer 1
I was a part of an esteemed multidisciplinary team with a focus on life sciences. Leading the software team involved in developing deep learning models, I was also engaged in architecting and designing a compiler for analog compute circuits in this domain.
AI Design Engineer
As a member of an exceptional research and development team under Prof. Boris Murmann, I contributed to patented AI-driven security algorithms. I innovated a power-efficient algorithm for certain fused deep learning layer operations for hardware and filed for a patent (see portfolio). My other contributions span quantization of neural nets and posit numbers.
Junior Research Fellow
I collaborated within an exceptional research team. My focus included studying Neural Network Hardware accelerators, providing mathematical insights into Binary Neural Nets, co-designing a specialized memory architecture, and publishing a paper (see portfolio). I delved into Capsule Networks and explored reinforcement learning.
Education
M.Tech Electrical Engineering (Microelectronics and VLSI):
My thesis was on "Energy Efficient Architectures for Neural Networks," guided by Prof. Joycee Mekie. I derived a formula for minimum exponent size in floating-point weight representation, ensuring accuracy. Furthermore, I have provided a mathematical rationale for a specific correlation between the mantissa and the depth of a model, proposing methods to enhance resilience to bit errors. My academic background encompasses a diverse range of subjects, including Pattern Recognition, Machine Learning, Artificial Intelligence, 3D Computer Vision, VLSI Design, Physics of Transistors, and CMOS Analog IC Design.
B.E. Electronics and Telecommunication Engineering [Gold Medal]
My final year project was on "Prediction Of Water Usage Based On Weather Data Pattern Using Neural Network", guided by Prof. Rashi Borgohain and Mr. Tanmoy Goswami. I constructed a device with Raspberry Pi, interfaced sensors for soil type and water usage data, and implemented a neural network. I created a web interface with RESTful APIs for user interaction. Additionally, I worked on a project involving human presence detection with a robot (AmigoBot) using machine learning during an internship at IITG. Upon detection, the robot would go and collect litter as directed.