C, C++, x86/ ARM Assembly, Python- Accelerating software security applications by efficiently utilizing debug hardware components- Adept with reverse engineering tools and Linux operating systems at all layers (boot, kernel space, user space)

- Led weekly lab on the Systems Security course for 40 undergraduate and graduate students (live demos on various attacks based on buffer overflows, memory corruption bugs, format string vulnerabilities and other)- Created and graded homework and lab exercises

C, C++, Python, Assembly- Successfully utilized the Intel Processor Trace hardware to achieve 52% acceleration compared to existing software instrumentation approaches when collecting the execution flow of applications running inside SDT/ JIT environments.- Developed Deep Packet Inspection tools executing entirely on GPUs and achieving accelerated detection of malware signatures; 3x faster than CPU implementations.- Accelerated various security applications using GPGPU programming; achieved speedup of up to 60x.- Performed study on Amazon products to discover Price Discrimination through statistical analysis; results show that prices can be affected by certain attributes like OS, location, browsing history etc.

C, C++, CUDA- Successfully reduced GPU monitoring overhead by 20% by developing monitoring tools on NVIDIA GPUs through GPGPU Programming- Designed a GPU scheduling profiler which imposes fairness between concurrently executing applications by efficiently distributing the available resources. This innovation resulted in increased speeds by 30x.

- Courses taught: Introduction to Secure Systems, Internet Measurements, Applied Stochastic Processes & Applied Mathematics for Engineers- Created course material, held various lectures and lab sessions, created and graded homework and project material

- Participated in a DARPA funded, advanced development project aiming to accelerate data-flow tracking of applications by 30%, using hardware-assisted tracing for monitoring events of interest.