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. 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 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.
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" |
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.
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 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.
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.
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.
