I’m a Director at Oxford Biomedica focusing on digital transformation for biological and experimental data. I lead all software development activities and data science efforts across the company, driving innovation and delivering impactful solutions. Before this, I worked as a Senior Researcher in the Health Intelligence Group at Microsoft Research where I developed frameworks to help build and understand gene networks in Synthetic Biology.
I received my PhD in Computer Engineering from Boston University in 2019. I was part of the Cross-Disciplinary Integration of Design Automation Research ( CIDAR) Lab and worked under Prof. Douglas Densmore (PhD). My PhD Dissertation - “Functional Synthesis of Genetic Systems” focussed on developing computational and mathematical frameworks for the synthesis and design of genetic circuits.
I also recieved an MS degree in Computer Engineering from Boston University, Boston, MA, USA in 2014, and a BE (Hons.) degree in Electrical and Electronics engineering from the Birla Institute of Technology and Science in 2012.
PhD in Computer Engineering, 2019
Boston University
MS in Computer Engineering, 2014
Boston University
BE in Electronics and Electrical Engineering, 2012
Birla Institute of Technology and Science, Pilani
Computation can be performed in living cells by DNA-encoded circuits that process sensory information and control biological functions. Their construction is time-intensive, requiring manual part assembly and balancing of regulator expression. We describe a design environment, Cello, in which a user writes Verilog code that is automatically transformed into a DNA sequence. Algorithms build a circuit diagram, assign and connect gates, and simulate performance. Reliable circuit design requires the insulation of gates from genetic context, so that they function identically when used in different circuits. We used Cello to design 60 circuits for Escherichia coli (880,000 base pairs of DNA), for which each DNA sequence was built as predicted by the software with no additional tuning. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts), and across all circuits 92% of the output states functioned as predicted. Design automation simplifies the incorporation of genetic circuits into biotechnology projects that require decision-making, control, sensing, or spatial organization.
A tool to automate the selection of fluorescent reporters
Automated design of genetic circuits with temporal verification
Genetic Engineering of Living Cells
An F# implementation for the Synthetic Biology Open Language data structure
A metric to compute the distance between two bounded Signal Temporal Logic formulas
A Temporal Logic Inference tool to infer temporal properties from data
A tool for Genetic circuit design automation
A Logic Synthesis and Logic Minimization tool for Synthetic Biology and Microuidics
A platform to Store, Exchange, and Interact with Synthetic Biological Data
An RC car that autonomously followed a remote, Infrared (IR) emitting beacon
An embedded device to monitor vital signs for infants
A multi-platform data storage and retrieval system to store patient medical data.