ACME Center Researchers

Jayeeta Chaudhuri (Member, IEEE) received the B.E. degree from the Department of Electronics and Telecommunication Engineering, Jadavpur University, India, in 2020. She joined Duke University, North Carolina, USA to pursue the Ph.D. degree in the Department of Electrical and Computer Engineering. In 2023, she received the MS degree from Duke University and transitioned to Arizona State University, Arizona, USA to continue her PhD. Her current research interests include cloud FPGA security, analog IC security, and ML-assisted countermeasures for hardware Trojan detection.

I am Ashish, currently in my second year of Ph.D. program in Computer Engineering under the supervision of Dr. Krishnendu Chakrabarty. Before joining the ACME Center as a Ph.D. student, I worked in the ACEG group at AMD as a Software Development Engineer. I completed my Bachelor’s degree in Electrical and Communication Engineering at the Indian Institute of Technology Bhubaneswar in 2021. My research interests include Processing In-Memory ML Accelerators, Reliability, and Computer Architecture

My name is Peter Domanski. I studied electrical engineering and received my Bachelor’s and Master’s degrees at the University of Stuttgart. I am a Ph.D. student at the Department for Parallel and Distributed Systems (Institute: Scientific Computing) at the University of Stuttgart and currently a visiting researcher at ASU. My research focus is the application of ML methods (especially Reinforcement Learning approaches) in semiconductor testing or related research fields for example digital healthcare.

I am Biplove Baral, currently a senior in the aerospace engineering undergraduate program. My research interests are in IP protection for Digital Microfluidic Biochips, using reinforcement learning. My research interests are in developing reinforcement learning frameworks that enhance the security and efficiency of emerging technologies. I am also interested in multi-agent reinforcement learning and its applications in autonomous systems, robotics, and next-generation AI-driven technologies.

Abhishek Bhattacharya is a Master’s student in Computer Science at Arizona State University. He holds a Bachelor of Engineering in Instrumentation and Control from Netaji Subhas Institute of Technology (Delhi University). Before joining ASU, he worked as a C++ developer for nearly four years at Cadence Design Systems, where he contributed to the development and optimization of Electronic Design Automation
(EDA) tools. His work focused on enhancing power integrity solutions, implementing multithreading techniques for performance improvements, and developing self-heating analysis tools for semiconductor design.

Throughout his career, Abhishek has been deeply involved in optimizing large-scale software systems, improving computational efficiency, and ensuring the scalability of critical applications. His expertise includes advanced C++ programming, parallel computing, and software debugging. At ASU, he aims to expand his knowledge in software optimization techniques and explore new approaches for improving EDA tool performance. He is passionate about solving complex engineering problems and contributing to innovative software solutions that enhance the efficiency and accuracy of semiconductor design and verification processes.

Krishna Pramod Madabhushi is pursuing PhD at Arizona State University supervised by Dr. Krishnendu Chakrabarty. He holds a M.S.E degree in Electrical Engineering from Arizona State University and a Bachelor of Technology degree in Electronics and Communications Engineering from JNTU Hyderabad. He is currently working as a Principal IC Design Engineer at Medtronic, where he actively works on the design and verification of ultra-low-power implantable medical devices. His work is critical in developing technologies that deliver life-enhancing therapies such as pacing, sensing, defibrillation, pain management, and neuromodulation. Drawing on more than a decade of experience, Krishna is committed to excellence and demonstrates a meticulous focus on quality. He holds a patent on improving neurostimulation resolution and he has presented a paper on BIST methodology to test linearity of sigma-delta modulators (SDMs) at ITC and a paper on chip-level IDDQ current estimation at the Synopsys User Group (SNUG). His technical contributions in self-test strategy for implantable devices were recognized by Medtronic with the Technical Excellence Award in 2022. An active member of IEEE, Krishna is continuously driven to expand his expertise and make meaningful contributions to his field.

Pragya Sharma is a Ph.D. student in Electrical and Computer Engineering at Arizona State University, advised by Dr. Krishnendu Chakrabarty. She holds a Bachelor of Science in Computer Engineering and a Master of Science in Electrical Engineering from Mercer University. Her research focuses on machine learning, hardware acceleration, and system optimization. Pragya has worked in both academia and industry, with experience at Boeing, Cisco, and multiple research labs, where she has developed AI-driven solutions and optimized embedded ML systems. She enjoys working at the intersection of software and hardware, constantly exploring ways to make machine learning more efficient and scalable.

Agastya Seth is an MS Computer Science student with three years of software development experience in Electronic Design Automation (EDA). He is currently conducting research on LLMs for EDA at the ACME Lab, exploring how AI can enhance hardware design and verification. Additionally, he is involved in AI-driven healthcare projects, focusing on signal processing and predictive analytics. Passionate about the intersection of AI, hardware, and real-world applications, Agastya aims to push the boundaries of intelligent systems in both EDA and healthcare.

Shail Dave is a final-year Ph.D. candidate at the School of Computing and Augmented Intelligence, Arizona State University. His research techniques and infrastructures enable efficient processing of critical applications like machine learning on hardware accelerators in an agile and sustainable manner. His research is published and referenced in flagship conferences and journals in computing design automation, computer architecture, and embedded systems and invited to premier international conferences and industrial forums. Shail has piloted several projects in national/global competitive programs with academics and industry researchers, including for designing/supporting heterogeneous and AI computing systems. He has received several honors, awards, and fellowships, including Silver Medal at ACM SIGBED Student Research Competition, Outstanding Research and Teaching Assistant Awards, and Doctoral Dissertation Fellowship from Graduate College at ASU. His research has been featured by several media and technical forums, including ASU news, ACM tech news, IEEE HKN, Communications of the ACM news, and insideHPC. He regularly serves in mentorship programs, vision workshops and panels for emerging computing systems research, and as a reviewer and organization/program committee member for the related flagship ACM/IEEE conferences, workshops, and journals

Tasneem Khan Shifa is pursuing Ph.D. in Electrical Engineering at Arizona State University. She received her Master’s in Electrical Engineering from Texas State University. Also, She completed her Bachelor’s in Electronics and Communication Engineering From Khulna University of Engineering and Technology (KUET) from Bangladesh.

Gitanjali Mukherjee completed her Bachelors in Electronics and Communication engineering from National Institute of Technology in Calicut, India in 2018. She is currently a Masters student at Arizona State University specializing in Computer Engineering (Electrical Engineering). Prior to this she had been working as a DFT Engineer for over 4 years at Synopsys, working on DFT insertion, ATPG, Simulations etc. She is also currently doing an internship at Nvidia as a DFT engineer.

Fan Guo received the B.E. degree in Electronic Science and Technology from Huazhong University of Science and Technology, Wuhan, China, in 2009, and M.S. degree in Electrical Engineering from Technical University of Delft, Delft, the Netherlands, in 2011. He is currently pursuing the Ph. D. degree in Electrical Engineering with Arizona State University. From 2012 to 2017, he was an Analog Design Engineer at Melexis, Tessenderlo, Belgium, where he was involved in designing pressure sensor and current sensor interfaces. He worked as a Design Consultant at IMEC Belgium in 2018 where he led the design optimization activities for a 3-stage driver tailored for coaxial cables. He was an Analog Design Intern at Kilby Labs, Texas Instruments, Dallas, TX, USA, in 2019, where he was involved in high-power high-efficiency buck converter design focusing on the gate-charge loss reduction. He was an Analog Design Intern at NXP Semiconductors, Chandler, AZ, USA in 2021 and 2022, where he worked on the system level modeling and block level optimization of high-performance fast transient dc-dc buck converter IP. Since 2023, he has been working as an Analog Circuit Engineer with NXP Semiconductors, Chandler, AZ, USA, where he is involved in the block level design and top-level verification of the dc-dc buck converter IPs. His current research interests include analog and mixed-signal design as well as power-management IC design and system modeling.

Balaji Yadav Battu is a PhD student in Electrical Engineering at Arizona State University, specializing in analog and mixed-signal design with a focus on switching converters under the guidance of Dr. Bertan Bakkaloglu. He has a robust background in power management ICs, voltage/current references, and LDOs. Balaji has published papers in prestigious conferences like ISCAS, ISVLSI, and VLSID. His expertise spans both academic research and industrial experience, including internships at Qualcomm and a role as a DFT engineer. Prior to ASU, Balaji completed his Master’s in Electronics and Communication Engineering at IIIT Hyderabad, India, and his undergraduate degree at R.V.R. & J.C. College of Engineering, India.

I am currently pursuing a master’s degree in electrical engineering at Arizona State University. I completed my bachelors degree in electronics and communications engineering from KLE Technology University from Hubballi, India. I worked as an IO circuit design engineer at Infineon Technologies Bangalore for 4 years. Here I worked on high-speed IO circuits, ESD protection cells, IP deliverables and on-chip IO noise debug. Currently, I am doing research under Dr. Bertan on load-sharing DC-DC converters.

I am a first-year PhD student at Arizona State University. Before joining ASU, I completed my BSc in Engineering from the Bangladesh University of Engineering and Technology (BUET) in 2022. My current research is dedicated to pioneering test solutions for advanced technologies, including 3D heterogeneous and neuromorphic systems as well as silicon photonics. Outside the laboratory, I am passionate about hiking, traveling to new destinations, and playing badminton, activities that provide a perfect balance to my research endeavors.

I’m Nikhil Sagar Modala, currently pursuing my Master’s thesis. My research interests involve Analog & mixed signal circuit design, Fault simulation/modelling, Design for test, and Built-in-self test methodologies. I’m passionate about exploring innovative solutions in these domains to address real-world challenges and contribute to advancing technology. I also have a keen interest in high-speed SerDes systems and aspire to delve deeper into this field as part of my research journey.

Aritra Ray is a Ph.D. student in the Department of Electrical and Computer Engineering at Duke University, US (2021-24). His research focuses on resource orchestration for cloud computing, the Internet of Things, health informatics (deep learning for type-1 diabetes prediction and uncertainty quantification of autoencoders), large language models, and privacy-preserving machine learning. He earned his Bachelor of Technology in Information Technology from the University of Calcutta, India (2017-21) and his Master of Science in Electrical and Computer Engineering from Duke University, US (2021-23).

Aritra Ray is a Ph.D. student in the Department of Electrical and Computer Engineering at Duke University, US (2021-24). His research focuses on resource orchestration for cloud computing, the Internet of Things, health informatics (deep learning for type-1 diabetes prediction and uncertainty quantification of autoencoders), large language models, and privacy-preserving machine learning. He earned his Bachelor of Technology in Information Technology from the University of Calcutta, India (2017-21) and his Master of Science in Electrical and Computer Engineering from Duke University, US (2021-23).