.: Reconfigurable Computing Laboratory, Members


Ilkin Aliyev (M.S)- since Fall'19

Research Interests: Real-time scheduling for DSSoC Architectures

CV (pdf) / Personal Web Page

John Mixter (Ph.D)- since Fall'17

Research Interests: Neuromorphic computing, machine learning, neural networks

CV (pdf) / Personal Web Page

Joshua Mack (Ph.D)- since Fall'18

Research Interests: Reconfigurable computing, domain specific architectures, high performance computing

Joshua Mack is a doctoral student in the Electrical and Computer Engineering program. Born in Iowa, he grew up in Peoria, Arizona, and attended the University of Arizona, where he earned dual degrees in Electrical and Computer Engineering and Mathematics. After graduation, he worked as a software engineer in Phoenix before returning to academia. His research interests include the intersection of high performance computing and reconfigurable systems; emerging architectures; and intelligent and/or autonomous workload partitioning across heterogeneous systems. Joshua aims not only to enable better and more efficient computation through designing or choosing the right kind of processor for every job, but also to create environments and structures that allow end users to make these decisions without needing to be experts.

CV (pdf) / Personal Web Page

Nirmal Kumbhare (Ph.D) - since Fall 2014

Nirmal Kumbhare is a Ph.D. candidate at the University of Arizona under the supervision of Dr. Ali Akoglu. His research interests involve reconfigurable and heterogeneous systems, high-performance computing, and power-aware resource management. During his Ph.D., he worked as a summer intern with Lawrence Livermore National Labs (computation intern) and Phtotmetrics/Qimaging (emulation intern). Prior to joining the Ph.D. program, he worked with Intel for four years as an emulation and validation engineer. He earned his M.Tech in Electronic systems from the Indian Institute of Technology, Mumbai in 2010 and Bachelor Degree in Electronics and Instrumentation Engineering from the Institute of Engineering and Technology in 2008. In 2018, he received the College of Engineering Outstanding Teaching Assistant award.

CV (pdf) / Personal Web Page


Sahil Hassan Unal (Ph.D)- since Fall'18

Research Interests: Reconfigurable computing, adaptive hardware architectures for error correciton codes

CV (pdf) / Personal Web Page

Edward Richter (M.S)- since Fall'17

Edward Richter attended the University of Arizona where he earned both a BS and MS in Electrical and Computer Engineering in 2018 and 2019 respectively. He held the position of Signal Processing Intern at Raytheon Missile Systems in the Summers of 2017 and 2018 where he researched and developed emerging hardware platforms for signal processing algorithms. Since January 2017, he has been a Research Assistant in the Reconfigurable Computing Laboratory at the University of Arizona working under Dr. Ali Akoglu conducting research on the architecture of neuromorphic platforms. Eddie’s research interests lie at the intersection of intelligent algorithms and hardware design where he aims to both enable the deployment of computationally expensive algorithms at the edge as well as decrease the power of these algorithms in the datacenter. To obtain these goals, he is interested in both utilizing algorithm-hardware codesign methodologies to design efficient implementations of algorithms with the underlying hardware in mind as well as developing tools that automatically map and optimize intelligent algorithms to various hardware platforms. In Fall 2019, Eddie will be attending the University of Illinois Urbana-Champaign where he will be pursuing a doctoral degree in Electrical and Computer Engineering

CV (pdf) / Personal Web Page

Ruben Purdy (M.S)- since Fall'17

Ruben Purdy is a research specialist in the department of Electrical and Computer Engineering at the University of Arizona. Born and raised in Tucson, he attended the University of Arizona, where he earned a bachelor degree in Electrical and Computer Engineering. In the fall he will begin pursing a Ph.D. at Carnegie Mellon University. His research interests include computer architectures and algorithms for energy efficient machine learning systems.

CV (pdf) / Personal Web Page

Spencer Valancius (M.S)- since Fall'17

Spencer Valancius is a graduate student in the Electrical and Computer Engineering program. In 2010 he joined the United States Army, Active Component as an Infantryman. From 2010 to 2015 he was stationed at Fort Stewart, Georgia where he performed the duties of a Squad Automatic Rifleman, attended Tactical Explosive Detector Dog Handler School, and would be promoted to the rank of Sergeant in 2013. As a Sergeant he performed the duties of a Team Leader, Squad Leader, Barrack Non-Commissioned Officer In-Charge (NCOIC), Suicide Prevention NCOIC and Environmental Compliance NCOIC. In 2015 he was honorably discharged at the end of his term of service. Following his discharge, he immediately returned to school, attending the University of Arizona where he obtained his Bachelors of Science in Electrical and Computer Engineering, and graduating with the College of Electrical and Computer Engineering’s Distinguished Graduating Senior Award. His research interests include emerging computer architectures and memory technologies, neuromorphic computing, artificial intelligence, and machine learning. Spencer is a driven and self-motivating individual with aspirations of working in a field with close ties to his areas of interest

CV (pdf) / Personal Web Page

Kris Rockowitz (M.S)- since Fall'19

Kris Rockowitz is currently an Undergraduate and Accelerated Master’s Student at the University of Arizona in the department of Electrical and Computer Engineering. Kris is originally from California and served in the United States Marine Corps as an Infantry Mortarman where he calculated targeting information for the deconfliction of air and ground assets. Fascinated by science and technology, he chose to pursue his degree at the University of Arizona and has contributed to research in Space Situational Awareness at Steward Observatory since 2017. He has investigated and employed software to determine the rotational period of Resident Space Objects in Geostationary Orbit from light curves, aiding in their characterization. He is currently assisting in the development of a custom photometric reduction pipeline for processing multi-color channel, high speed astronomy data and has designs to optimize with GPU acceleration. Kris seeks projects that include a blending of software and hardware engineering aimed at yielding better science. He is captivated by research fields which host a combination of high-performance computing, artificial intelligence and machine learning as they exude high potential to revolutionize the human experience

CV (pdf) / Personal Web Page


Nirmal Kumbhare(Ph.D.) Spring 2019, @ Post Dcotoral Researcher, University of Arizona Power-Aware Value-Based Resource Management in High Performance Computing Systems
Burak Unal(Ph.D.) Spring 2019, @ Assistant Professor, Karabuk University, Turkey Low-Density Parity-Check Code Decoder Design and Error Characterization on an FPGA Based Framework
Elnaz T. Yazdi (MS) Fall Spring 2018, @ Photometrics PDeveloping A Highly Parallelized TCR Synthesis Algorithm on GPGPU and FPGA For Accelerating the Study of Immune Systems
Ehsan Esmaili (MS) Spring 2018, @ Micron Scalable Autonomic Management of 3D Cardiac Simulations
Arpit Soni (MS) Spring 2016, @ Intel PAnalytical Model for Relating FPGA Logic and Routing Architecture Parameters to Post-routing Wirelength
Cihan Tunc (Ph.D.) Spring 2014, @ Assistant Professor, University of North Texas Fall 2020, Prior: Research Assistant Professor, University of Arizona Autonomic Cloud Resource Management
Nilanshu Bidyanta (MS) Spring 2014, @ Qualcomm Real-time GPU based Video Segmentation with Depth Information
Burak Unal (MS) Spring 2013 Contrast Limited Adaptive Histogram Equalization (CLAHE) and Shadow Removal for Controlled Environment Plant Production Systems
Yoon Kah Leow (Ph.D.) Spring 2013, @ Synopsys Post-Routing Analytical Models for Homogeneous FPGA Architectures
Gregory Streimer (Ph.D.) Spring 2013, @ DHS TCRβ Repertoire Modeling Using a GPU-Based In-Silico DNA Recombination Algorithm
Audip Pandit (MS) Fall 2007, @ Intel Pre-Placement Net Length Prediction and Improvements for the FPGA Clustering Stage
Sandeep Venishetti (MS) Fall 2007, @ Intel FPGA Based Implementation of IEEE754 Compliant Double Precision Floating Point Arithmetic Units
Deepak Sreedharan (MS) Spring 2008 @ TI Hybrid Processing Element based Reconfigurable Architectures for Cryptography Algorithms
Jeff Josiah (MEng) Spring 2008, @ Honeywell Development of Partial Reconfiguration Based Self-Healing system Using Xilinx Virtex-5 FPGA
Andrew Lotti (MEng) Fall 2008, @ Honeywell Development of Wireless Self-Healing Architecture Based on Mesh Networks
Ruchika Verma(MS) Spring 2009 @ TRX Systems, Maryland Coarse Grained and Hybrid Reconfigurable Architecture with Flexible Noc Router For Variable Block Size Motion Estimation
Adarsha Sreeramareddy(MS) Fall 2009 @ Indigo Quotient Labs, Co-Founder Scalable Self-Configurable Architecture for Reusable Space Systems
Hanyu Liu (MS) Fall 2009, @ DataDomain Wire-Length Prediction Based Clustering for the FPGA CAD Flow
Arjun Hary (MS) May 2010, @ TI Design of fault tolerant scientific workflows with Kepler
Lakshmi Easwaran (MS) May 2010, @ Intel Wirelength prediction based power aware clustering for FPGA CAD
Yang Song (Ph.D) May 2011, @ NVIDIA Adaptive Motion Estimation Architecture for H.264/AVC Video Codec
Senthilkumar Thoravi Rajavel (MS) Summer 2011, @ Lattice Semiconductor Design of multi-objective clustering and energy modeling for FPGAs
Janhavi Sabnis (MS) Summer 2011, @ Intel PUF Based FPGA Bitstream Protection
Gregory Striemer(Ph.D) Spring 2013 GPU Based DNA Recombination
Burak Unal (M.S) Summer 2013 Contrast Limited Adaptive Histogram Equalization for Greenhouse Based Plant Production Systems


Kris Rockovitz Mapping Vector Matrix Multiplication onto Truenorth(Spring 2020)
Spencer Valancius FPGA-based emulation of Neuromorphic Architectures,(Fall 2019)
Sebastian Thiem Performance Comparisons of Traditional Branch Prediction Methods and Perceptron Based Branch Prediction,(Fall 2018)
Brandon Lee Black Branch Prediction using Artificial Neurons,(Fall 2018)
Ben Johnson (UG) Development of Parallel 3D Heart Simulations based on Graphics Processing Unit (GPU),(Spring 2017)
Jonathan Watson (UG) Web-Based Interactive Simulation Environment Pipelined Datapath Design,(Fall 2016)
Andrew Appel (UG) Design and Development of Instruction Level Modular ARM/MIPS ISA Simulator,(Fall 2016)
Scott Marshall (UG) Honors Independent Study: Development of Highly Parallel Modulation Classification Hardware Architecture based on Graphics Processing Unit (GPU),(Fall 2015)
Julian Bostick (UG) Performance Evaluation of FPGA Based Signal Processing),(Spring 2014)
Nathanial Sema (UG) Modeling 3D FPGA Architecture,(Fall 2013)
Kyle T. Province (UG) Depth-supported Video Segmentation with the Kinect Sensor Using Nvidia Graphics Processing Unit,(Fall 2013)
Wellington Lee (UG) Parallel Implementation of the Peridynamic Force Theory for Crack Simulation Using Nvidia Graphics Processing Unit,(Spring 2013)
Brian Smith (UG) DGPGPU Based Shadow Removal in Greenhouse Based Plant Health Monitoring,(Spring 2013)
Jonathan Gross (UG) Development of Highly Parallel Singular Value Decomposition (SVD) Method for Solving Partial Differential Equations using Graphics Processing Unit (GPU),(Fall 2010)
Garrett Weaver (UG) Development of Highly Parallel Conjugate Gradient Method for Solving Partial Differential Equations using Graphics Processing Unit (GPU),(Fall 2010)
Andrew James Bozzi (UG) Low Density Parity Check Code on GPU (Fall 2009)
Jamie Williamson (UG)

Direct Simulation Monte Carlo (DSMC) on Graphics Processing Unit (GPU) using CUDA Development Platform on TESLA (Fall 2008)

Gregory Striemer (UG) Smith-Waterman Sequence Alignment Optimization on Graphics Processing Unit (GPU) using CUDA Development Platform on TESLA (Fall 2008)
John Walton (UG) Integration of Micron CMOS Camera with FPGA (Summer 2008)
Izuchukwu Nwachukwu (UG) Development of Memory Controller for Camera Integrated FPGA Platform (Summer 2008)
Angelica Jacobs (UG) Development and Synthesis of Single Cycle Datapath for MIPS Instruction Set Architecture (Summer 2008)
Andrew Lotti (MEng) Field Programmable Gate Array (FPGA) Based Healing with Partial Configuration Techniques (Spring 2008)
Jeff Josiah (MEng) Performance Enhancement of Wireless Mesh Network Towards Network Level Healing (Spring 2008)
Jeremy Wright (UG) FPGA Based Camera Integrated Object Tracking System with a Video Display Interface (Spring 2008)
Kevin Carr (UG) FPGA Based Camera Integrated Image Recognition System with a Video Display Interface (Spring 2008)