Jyotikrishna Dass
Assistant Professor
Department of Electrical and Computer Engineering
University of Arizona
1230 E. Speedway Blvd., P.O. Box 210104
Tucson, AZ 85721-0104
E-mail: jdass [@] arizona [DOT] edu
Biography
Jyotikrishna Dass is an assistant professor in the Department of Electrical and Computer Engineering at The University of Arizona. His research integrates machine learning, parallel computing, and hardware design to create efficient algorithms and systems for distributed edge intelligence. His work has been featured in the IEEE International Conference on Machine Learning (ICML), IEEE International Conference on Distributed Computing Systems (ICDCS), IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE International Symposium on High-Performance Computer Architecture (HPCA), IEEE Micro and IEEE Transactions on Computers (TC). He has served as instructor-of-record for several courses during his graduate studies and is eager to contribute to the department's new computer science and engineering program.
Prior to joining U of A, Dr. Dass was a research scientist and executive director at Rice University, leading the Center for Transforming Data to Knowledge (D2K). From 2021-2022, he was a postdoctoral research associate at Rice, co-writing grant proposals for NSF Core Programs ($1.2 million), META Network for AI ($50K), and Rice University Creative Ventures Fund ($10K).
Dr. Dass earned his PhD in Computer Science and Engineering from Texas A&M University in 2021. His research was recognized with the Best PhD Dissertation Poster Award at the Annual Computing Conference, 2019 among fourteen SEC universities. He was also a College of Engineering Graduate Teaching Fellow in 2020 and received the CSE Teaching Assistant Excellence Award in 2018. He holds a B.Tech degree in Electronics and Communication engineering with a Minor in CSE from the Indian Institute of Technology (IIT) Guwahati.
News
Aug, 2026 Dr. Dass (co-PI, Award Credit: 50%) has been awarded his first National Science Foundation (NSF) grant ($498,627 for 3 years) to launch a Research Experiences for Undergraduates (REU) site ARISE: AI Research for Intelligent Systems and Efficiency beginning Summer 2027. Thank you NSF! | Post | News.
Aug, 2026 SpikeFed: Federated Training of Spiking Neural Networks for Event-Based Vision paper has been featured on Flower Labs behind the leading open-source framework for training better AI on distributed data | Post 1 | Post 2.
Aug, 2026 AI SPARK Workshop Series and AI IGNITE Research Showcase have been featured on ECE News | News | Video.
Jul, 2026 Lydia Obeng and Vimal William attended DAC 2026 at Long Beach, CA, USA as part of University of Arizona Herbold Fellowship Travel Grant. Vimal was also selected as DAC Young Fellows 2026 | Post.
Jun, 2026 Dr. Dass attended ACM GLSVLSI co-located with ACM IGSC 2026 at Lake Canandaigua, NY, USA where he chaired Special Session on Sustainable Distributed AI Systems on served on Best Paper Award committee for ACM IGSC 2026. | Post.
May, 2026
Megan Zupancic (Undergraduate Student) mentored and nominated by Dr. Dass has been honored as Outstanding Senior in Software Engineering award for 2025-2026 | Post.
May, 2026 SpikeFed: Federated Training of Spiking Neural Networks for Event-Based Vision has been accepted for publication at ACM IGSC 2026 (Canandaigua, NY, USA). Congratulations Lydia and Hariharan for this collaboration of DASS Lab with Dr. Ramtin Zand from University of South Carolina.
May, 2026 FedLLM4HW: Carbon-Aware Federated Triage of Hardware Weaknesses in LLM-Generated Verilog has been accepted for publication at ACM IGSC 2026 (Canandaigua, NY, USA). Congratulations Hariharan for this collaboration of DASS Lab with Dr. Soheil Salehi, Dr. Pratik Satam, and Dr. Rozhin Yasaei at University of Arizona.
May, 2026 Spectral Transformation for Layer-wise Global Rank Discovery in Federated LoRA for Vision Transformers has been accepted for publication at ECML-PKDD 2026 (Naples, Italy). Congratulations Hariharan on his second PhD paper as first author! Thank you NVIDIA Academic Grant!
May, 2026 FLoRIST: Singular Value Thresholding for Efficient and Accurate Federated Fine-Tuning of Large Language Models was presented as oral (and later in poster session) by Hariharan at MLSys 2026 in Seattle, WA, USA. Dr. Dass, Hariharan and Vimal from DASS Lab attended the conference.| Post.
May, 2026 Dr. Dass is serving as a reviewer for NeurIPS 2026.
May, 2026 Dr. Dass is recognized as Gold Reviewer (Free Registration) by ICML 2026 for being among the Top 25% (4439) reviewers! | Post.
May, 2026 Dr. Dass launched a new annual ECE event, AI IGNITE Research Showcase as a celebration of AI in ECE comprising AI Faculty Lightning Talks and Student Poster Competition on AI research and course projects. | Post | Pictures.
April, 2026 Dr. Dass will chair Special Session on Sustainable Distributed AI Systems at ACM IGSC 2026.
April, 2026 Dr. Dass is serving on Technical Program Committee for ACM IGSC 2026.
April, 2026 Dr. Dass is serving as a reviewer for ACM GLSVLSI 2026.
Apr, 2026 Dr. Dass along with Hariharan Ramesh (PhD student, DASS Lab) conducted the second session of AI SPARK: Igniting AI Curiosity and Building Networks Workshop series on topic Deploying Your First Large Language Model.. | Post | Pictures.
Mar, 2026 We have received our "second" NVIDIA Academic Grant Award in 6-months !! Our project titled, "Hardware-Aware Digital Twin for Federated Generative AI " has been awarded 4x RTX PRO 6000 Blackwell Max-Q Workstation Edition and 2x Jetson AGX Orin Dev Kits (equivalent to USD 40,000) as a part of "Robotics and Edge AI" call. This project is being led by our incredible PhD student, Lydia! Thank you NVIDIA for supporting our research on FL x Digital Twin! | Post.
Mar, 2026 Dr. Dass along with Hariharan Ramesh (PhD student, DASS Lab) kicked-off Spring season of AI SPARK: Igniting AI Curiosity and Building Networks Workshop series with topic Unlocking the Mystery of Large Language Models.. | Post | Pictures.
Feb, 2026 FLoRIST: Singular Value Thresholding for Efficient and Accurate Federated Fine-Tuning of Large Language Models has been accepted for publication at MLSys 2026 (Seattle, WA, USA). Congratulations Hariharan on his first PhD paper and our first paper at DASS Lab! Thank you NSF ACCESS and NVIDIA Academic Grant!
Feb, 2026 Dr. Dass is serving as a reviewer for ICML 2026.
Feb, 2026 Dr. Dass was selected to attend the 2026 CRA Career Mentoring Workshop in Washington, D.C.
Jan, 2026 Dr. Dass was invited to participate at NSF LEVEL UP AI (Launching an Educational Vision to Expand Leadership, Understanding, and Progress in Artificial Intelligence - Phase 2) workshop in Phoenix, AZ hosted by Computing Research Association (CRA) following the virtual roundtable discussions in Phase 1.
Nov, 2025 Dr. Dass along with Dr. Huanrui Yang (ECE, UofA) launched a new hands-on workshop, AI SPARK: Igniting AI Curiosity and Building Networks for the campus community with 100+ participants. | Post | Event Flyer.
Nov, 2025 Dr. Dass gave presentation on ECE Undergraduate Programs to 100+ freshman students as part of ENGR 102A, University of Arizona.
Nov, 2025 Dr. Dass gave Guest Lecture on Distributed Edge Computing in the course ECE 369A – Fundamentals of Computer Organization, University of Arizona.
Nov, 2025 Lydia and Vimal represented DASS Lab at the ECE Graduate Student Poster Session at UofA Homecoming 2026 where they presented their current research on Visual and Interactive Platform for Distributed AI and Memory-Efficient LLM with KV Cache, respectively.
Oct, 2025 Congratulations to Hariharan for being nominated and awarded the 2025 College of Engineering Outstanding Graduate Teaching Assistant Award in CSE. We are immensely proud that Hari now continues the TA Award legacy of his advisor, Dr. Dass (CSE TA Excellence Award – 2018, Texas A&M University)!
Sep, 2025 Launched new course ECE 425/525: Introduction to Deep Learning - An Engineering Persepctive. The course attracted 20 Undergraduate and 29 Graduate Students. Course Flyer. The teaching materials designed by Dr. Dass are being used to support the 2026 AI/ML course for Microcampus students at Sampoerna University, Jakarta, Indonesia.
Sep, 2025 DASS Lab welcomes its first cohort of PhD students, Hariharan Ramesh (PhD in CSE), Lydia Obeng (PhD in ECE), and Vimal William (PhD in ECE). More information can be found here.
Sep, 2025 We have received NVIDIA Academic Grant Award (12K A100 GPU-Hours) under "Research: Gen AI Training and Model Development" call for the project, titled, "Efficient Federated Fine-Tuning of Gen AI via Adaptive Low-Rank Aggregation". This project will be led by our incredible PhD student, Hari! Thank you NVIDIA for supporting our research! | Post.
Sep, 2025 Invited to join India Advisory Network initiative to deepen University of Arizona long-term engagement with India. The India Advisory Network will play a central role in efforts to expand academic and research collaborations, strengthen industry and government partnerships, advance student mobility, and activate our vibrant alumni community across India.
Aug, 2025 Served as Reviewer for 8th Workshop on Visualization for AI Explainability at IEEE VIS 2025.
Jun, 2025 Served as Reviewer for NSF Computer and Information Science and Engineering Graduate Fellowship Program (CSGrad4US) 2025.
Jun, 2025 Served on PhD Dissertation Committee of Jesse Friedbaum (advised by: Prof. Ravi Tandon), University of Arizona.
May, 2025 Served as Session Chair for MLSys 2025 at Santa Clara, CA.
Apr, 2025 Participated in NSF LEVEL UP AI (Launching an Educational Vision to Expand Leadership, Understanding, and Progress in Artificial Intelligence) Roundtable (part of NSF EducateAI initiative) hosted by CRA.
Mar, 2025 Dr. Dass welcomed and joined the selected group of PhD students at ECE Graduate Recruiting Weekend over a fun-filled dinner.
Feb, 2025 Serving as a reviewer for KDD 2025.
Oct, 2024 Selected to attend the NSF CISE MSI Aspiring PI Workshop at UNT, Denton, TX.
Oct, 2024 Serving in Technical Program Committee for DAC 2025.
Sep, 2024 Serving as a reviewer for ICLR 2025.
Aug, 2024 Joined Dept. of ECE at University of Arizona as Tenure-Track Assistant Professor, #BearDown Wildcats!
Mar, 2024 Serving as a reviewer for Transactions on Computers.
Feb, 2024 Serving as a reviewer for ICML 2024.
Oct, 2023 Our work on “NetDistiller: Empowering Tiny Deep Learning via In-Situ Distillation” has been accepted for publication in IEEE Micro Special Issue on tinyML.
Oct, 2023 Serving as a reviewer for ICLR 2024.
Mar, 2023 Serving as Local Chair for the 11th IEEE International Conference on Healthcare Informatics (ICHI 2023) to be held from June 26th-June 29th in Houston, TX.
Feb, 2023 Presented our work “ViTALiTY” at IEEE HPCA in Montréal, CA.
Oct, 2022 Our work on “ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention” has been accepted for publication in IEEE HPCA 2023 (25%).
Oct, 2022 Serving as a reviewer for ICLR 2023.
Oct, 2022 Attended the META Communication and Networking Faculty Summit as an awardee of META:Network for AI RFP.
Aug, 2022 Joined The Rice University Data to Knowledge (Rice D2K) Lab as a Research Scientist.
Aug, 2022 Our proposal “SHF:Medium:DILSE:Codesigning Decentralized Incremental Learning System via Streaming Data Summarization on Edge” has been accepted for NSF CISE Core Programs grant ($1,200,000).
Aug, 2022 Our proposal “MILES: Multi-device Incremental Learning on Edge via Summarization” has been accepted for META:Network for AI funding ($50,000).
Jul, 2022 Our proposal “Tutorial on Automated Tools for Fast Development of Deep Learning Networks and Accelerators” has been accepted for MICRO 2022, Chicago, IL.
Jul, 2022 Chaired the research session on “Machine Learning for Resource Management: From Edge to Cloud” at DAC 2022 in San Francisco, CA.
Mar, 2022 Our proposal “Workshop on Automated AI Tools for Computing and Communication” has been accepted for Creative Ventures Fund: Conference and Workshop Development ($10,000) from Rice University.
Sep, 2021 Moved to Houston and joined Rice University as a Postdoctoral Associate.
Aug, 2021 Graduated from Texas A&M University with a PhD degree in Computer Engineering.
June, 2021 Defended my PhD disertation on “Efficient and Scalable Machine Learning for Distributed Edge Intelligence”.
May, 2021 Our work on “Householder Sketch for Accurate and Accelerated Least-Mean-Squares Solvers” has been accepted at ICML 2021.
May, 2021 Joining Dr. Yingyan Lin's lab at Rice University as a postdoc in Fall 2021.
Apr, 2021 Serve as invited reviewer in the Program Committee for NeurIPS 2021.
Dec, 2020 Serve as invited reviewer for ICML 2021.
Aug, 2020 Teaching CSCE 312: Computer Organization as Graduate Assistant Lecturer for Fall 2020 | Syllabus
May, 2020 Our work on distributed training of SVM on multiple-FPGA system has been accepted for publication in IEEE Transactions on Computers, Impact factor: 3.131 with acceptance rate 21% in Special Issue on Machine-Learning Architectures and Accelerators.
Apr, 2020 As a part of community service during COVID-19,
- Organized a free and synchronous online educational inititiative ShiP.py: Learning to Py while Shelter-in-Place with a team of undergraduate and PhD student volunteers | Course Playlist
- Organize and co-instructed a free online course Stay Home and Learn AI with a team of volunteers comprising professors, industry professionals, and students working in data science, machine learning, and deep learning | My SHALA Lectures | Course Playlist.
- Organized a free and synchronous online educational inititiative ShiP.py: Learning to Py while Shelter-in-Place with a team of undergraduate and PhD student volunteers | Course Playlist
- Organize and co-instructed a free online course Stay Home and Learn AI with a team of volunteers comprising professors, industry professionals, and students working in data science, machine learning, and deep learning | My SHALA Lectures | Course Playlist.
Feb, 2020 Wrote my first blog inspired by Yoshua Bengio and Carl-Johann SIMON-GABRIEL | Decentralizing Academic Conferences for a Better Climate.