Mike Ferdman
Associate Professor, CS, Stony Brook University
I am an Associate Professor of Computer Science at Stony Brook University. I direct the Computer Architecture Stony Brook (COMPAS) Lab. Prior to joining Stony Brook, I completed my Ph.D. at Carnegie Mellon University (CMU) under the supervision of Babak Falsafi. While completing my dissertation, I spent several years working remotely from Ecole Polytechnique Fédérale de Lausanne (EPFL).
My research interests are in the area of computer architecture, with emphasis on the design of server systems. I work on the entire computing stack, from server software and operating systems, to networks and processor microarchitecture. My current research projects include FPGA accelerator integration into server environments (e.g., Intel HARP, Microsoft Catapult, and Amazon F1), FPGA programmability (e.g., virtual memory and high-level synthesis), accelerators for machine learning (e.g., transformers and convolutional neural networks), efficient network processing and software-defined networking, speculative performance and energy-enhancing techniques for high-performance processors, and programming models and mechanisms for emerging memory technologies (e.g., HBM and 3D XPoint).
If you are a PhD student at Stony Brook and want to work with me, please send me email to arrange an appointment.
publications
| 2019 | |
| [7] | x86-64 Instruction Usage Among C/C++ Applications , In 12th ACM International Conference on Systems and Storage (SYSTOR), 2019. [bib] [pdf] |
| [6] | Swarm Model Checking on the GPU , In 26th International SPIN Symposium on Model Checking of Software, Springer International Publishing, 2019. [bib] [pdf] |
| [5] | Sorting Large Data Sets with FPGA-Accelerated Samplesort , 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM poster), 2019. [bib] [pdf] |
| [4] | An Efficient, Scalable and Exact Representation of High-Dimensional Color Information Enabled via de Bruijn Graph Search , In 22nd Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2019. [bib] [pdf] |
| [3] | Massively Parallel Server Processors , In Computer Architecture Letters (CAL), 2019. [bib] [pdf] |
| [2] | Argus: an End-to-End Framework for Accelerating CNNs on FPGAs , In IEEE Micro, volume , 2019. [bib] [pdf] |
| [1] | Runtime-Programmable Pipelines for Model Checkers on FPGAs , In 29th International Conference on Field Programmable Logic and Applications (FPL), 2019. (nominated for the Best Paper award) [bib] [pdf] |
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teaching
Courses I have taught or teaching currently:
- Spring '24 - CSE 356 - Cloud Computing
- Spring '24 - CSE 502 - Computer Architecture (grad)
- Fall '22 - CSE 356 - Cloud Computing
- Spring '22 - CSE 502 - Computer Architecture (grad)
- Spring '22 - CSE 356 - Cloud Computing
- Spring '20 - CSE 502 - Computer Architecture (grad)
- Fall '19 - CSE 356 - Cloud Computing
- Spring '19 - CSE 356 - Cloud Computing
- Spring '19 - CSE 502 - Computer Architecture (grad)
- Spring '18 - CSE 356 - Cloud Computing
- Fall '17 - CSE 506 - Operating Systems (grad)
- Spring '17 - CSE 502 - Computer Architecture (grad)
- Spring '17 - CSE 356 - Cloud Computing
- Fall '15 - CSE 506 - Operating Systems (grad)
- Fall '15 - CSE 391(356) - Cloud Computing
- Spring '15 - CSE 506 - Operating Systems (grad)
- Fall '14 - CSE 602 - Advanced Computer Architecture (grad)
- Spring '14 - CSE 502 - Computer Architecture (grad)
- Fall '13 - CSE 506 - Operating Systems (grad)
- Spring '13 - CSE 502 - Computer Architecture (grad)
- Fall '12 - CSE 59x(602) - Datacenters (grad)
CV
Michael Ferdman
Associate Professor, Computer Science, Stony Brook University
Director, Computer Architecture at Stony Brook (COMPAS) Laboratory
Curriculum Vitae - March 2025
http://compas.cs.stonybrook.edu/~mferdman/
mferdman@cs.stonybrook.edu
+1 (631) 632-8449
mferdman@cs.stonybrook.edu
+1 (631) 632-8449
Department of Computer Science
343 New Computer Science
Stony Brook, NY 11794-2424
343 New Computer Science
Stony Brook, NY 11794-2424
Research Interests
Computer architecture, with particular emphasis on the design of efficient server systems. Most recently, my main focus has been on Machine Learning Accelerators, developing hardware techniques to enable fast and efficient implementations of deep learning, and making FPGA-based accelerators more practical and easier to program. More broadly, my work seeks to understand the fundamental properties and interactions of application software, operating systems, networks, processor microarchitecture, and datacenter dynamics, to enable software and hardware co-design of high-performance, power-efficient, and compact servers.
Education
- Carnegie Mellon University Pittsburgh, PA
- Ph.D. in Electrical and Computer Engineering June 2012
- M.S. in Electrical and Computer Engineering December 2002
- B.S. in Electrical and Computer Engineering December 2002
- B.S. in Computer Science May 2002
Honors and Awards
- ACM SIGARCH/SIGPLAN/SIGOPS ASPLOS 2023 Influential Paper (test-of-time) Award
- 2020 Young Academic Inventor's Award from the National Academy of Inventors SBU Chapter
- Undergraduate Teaching Award (2019)
- David R. Smith Young Scholar in Computer Science Award (2016)
- NSF CAREER Award (2015)
- Graduate Teaching Award (2014)
- Best Paper Award at the 11th International Conference on Virtual Execution Environment (VEE)
- IEEE Micro Top Picks from Computer Architecture Conferences of 2013
- Best Paper Award at the 17th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)
- Best Paper Finalist at the 17th International Symposium on High-Performance Computer Architecture (HPCA)
- Paper Award from the European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC)
- Two papesrs in IEEE Micro Top Picks from Computer Architecture Conferences of 2009
- 2005 DARPA Grand Challenge driverless desert race, 2nd and 3d place autonomous vehicles
Publications
Patents
- US 10,726,330 B2: System, Method, and Accelerator to Process Convolutional Neural Network Layers
Michael Ferdman, Peter Milder, Manoj Alwani.
Academic Employment
- Microsoft Corporation Redmond, WA
- Visiting Researcher (academic sabbatical) June 2020-June 2021
- Stony Brook University Stony Brook, NY
- Associate Professor September 2018-present
- Assistant Professor August 2012-August 2018
- Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland
- Research Assistant July 2008-June 2012
- Carnegie Mellon University Pittsburgh, PA
- Research Assistant August 2004-June 2012
Teaching
- Stony Brook University Stony Brook, NY
- CSE 502 - Graduate Computer Architecture Spring 2024
- CSE 356 - Cloud Computing Spring 2024
- CSE 356 - Cloud Computing Fall 2022
- CSE 502 - Graduate Computer Architecture Spring 2022
- CSE 356 - Cloud Computing Spring 2022
- CSE 502 - Graduate Computer Architecture Spring 2020
- CSE 356 - Cloud Computing Fall 2019
- CSE 356 - Cloud Computing Spring 2019
- CSE 502 - Graduate Computer Architecture Spring 2019
- CSE 356 - Cloud Computing Spring 2018
- CSE 506 - Graduate Operating Systems Fall 2017
- CSE 502 - Graduate Computer Architecture Spring 2017
- CSE 356 - Cloud Computing Spring 2017
- CSE 506 - Graduate Operating Systems Fall 2015
- CSE 356(391) - Cloud Computing Fall 2015
- CSE 506 - Graduate Operating Systems Spring 2015
- CSE 602 - Graduate Advanced Computer Architecture Fall 2014
- CSE 502 - Graduate Computer Architecture Spring 2014
- CSE 506 - Graduate Operating Systems Fall 2013
- CSE 502 - Graduate Computer Architecture Spring 2013
- CSE 602 - Graduate Advanced Computer Architecture Fall 2012
- Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland
- TA - Advanced Topics on Memory Systems (graduate) Spring 2009 (Babak Falsafi)
- TA - Multiprocessor Architecture (graduate) Fall 2008 (Babak Falsafi)
- Carnegie Mellon University Pittsburgh, PA
- TA - Multiprocessor Architecture (graduate) Spring 2006 (Babak Falsafi)
- TA - Advanced Techniques in Microprocessors (PhD) Fall 2005 (Babak Falsafi)
- TA - Operating Systems (undergraduate) Fall 2001 (Gregory Kesden)
- TA - Embedded Systems (undergraduate) Fall 2001 (Raj Rajkumar)
Industry Employment
- Microsoft Corporation Redmond, WA
- Visiting Researcher 2020-2021
- T elinta, Inc. Springfield, NJ
- Chief Technology Officer 2002-present
- Cadence Design Systems Pittsburgh, PA
- Software Engineer April 2004-August 2007
- Neolinear, Inc. (startup acquired by Cadence) Pittsburgh, PA
- Software Engineer March 2003-April 2004
- Automatika, Inc. Pittsburgh, PA
- Independent Contractor September 2002-January 2003
- National Robotics Engineering Consortium Pittsburgh, PA
- Circuit Designer and Software Engineer February 2001-May 2002
Professional Service
- Organizing committees: ASPLOS Steering Committtee Chair (2022-2024), ASPLOS'22 (co-general chair), ISPASS'21 (general chair), ISPASS'20 (program committee chair), HPCA'20 (registration chair), DPC'19 (program committee chair), ISCA'17 (finance chair), IISWC'17 (travel grant chair), HPCA'17 (workshops & tutorials chair), ISPASS'17 (workshops & tutorials chair), ISPASS'16 (publication chair), ACM SRC at CGO'15 (local organizer), ISPASS'15 (publication chair), MICRO'14 (publication chair), ISPASS'14 (web chair)
- Steering Committees: Architectural Support for Programming Languages and Operating Systems (ASPLOS), International Symposium on Performance Analysis of Systems and Software (ISPASS)
- Program committees: IEEE MICRO's Top Picks'25, ASPLOS'25, MICRO'24, IISWC'24, ICS'24, ASPLOS'24, MICRO'23, HotInfra'23, SIGMETRICS'23, SIGMETRICS'22, MICRO'22, ISCA'21, IEEE MICRO's Top Picks'21, MICRO'20, IPC'20, USENIX ATC'20, IISWC'19, ISCA'19, HPCA'19, MICRO'18, ICCD'18, IISWC'18, ISCA'18, DAC'18, GLSVLSI'18, HPCA'18, MICRO'17, ISCA'17, HPCA'17, CRC'17, ISCA'16, IISWC'16, ISPASS'16, MICRO'15, IISWC'15, ISCA'15, CGO'15, MICRO'14, ICS'14, ICPP'14, HiPEAC'14, ICCD'13, WIVOSCA'13, DATE'13, CCGrid'13, ISPASS'13, IPDPS'13
- University Service: College of Engineering and Applied Sciences Dean's Advisory Council, Graduate Council Representative for CS (F'21-S'24), College of Engineering and Applied Sciences Executive Committee (S'21), CS Executive Committee (S'19-), CS Operations Committee (S'17, F'16, S'16), Graduate Committee (S'17, F'16, S'16), Undergraduate Committee (S'16), Open House Chair (S'17, S'16, S'15), Graduate Admission Committee (S'20, F'19, S'19, F'18, S'18, F'17, S'17, F'16, S'16, F'15, S'15, S'14, F'14, F'13, S'13, F'12), Faculty Recruitment Committee (S'17, S'14, F'14), Department Orientation Organizer (F'16)
- NSF invited workshops: Workshop on Sustainable Data Centers '15, XPS Workshop on Exploiting Parallelism and Scalability '15
- External reviewer: HPCA'23, MICRO'21, ASPLOS'21, SIGMETRICS'21, ISCA'20, CAL'19, IEEE Micro'19, TECS'19, MICRO'19, CAL'19, TACO'19', CAL'18, TOCS'18, TACO'18, CAL'17, IEEE Micro'17, ACM TACO'17, ACM TOS'16, MICRO'16, ACM TACO'16, HPCA'16, ACM TACO'15, CAL'15, HPCA'15, ASPLOS'15, CF'14, ISCA'14, TC'14, HPCA'14, PPoPP'14, CAL'13, DAC'13, HPCA'13, JCST'13, MICRO'12, IISWC'12, CAL'12, HPCA'12, IISWC'11, MICPRO/DSD'11, ICS'11, ISCA'11, HPCA'11, HiPEAC'10, ISCA'10, HPCA'10, JPDC'09
- NSF service: 2025 (panelist), 2023 (panelist), 2022 (panelist x2), 2021 (panelist), 2020 (panelist), 2019 (panelist), 2016 (panelist, reviewer), 2014 (panelist)
- Invited Lectures and Talks: Cloud Computing course at HiPEAC ACACES'17, Keynote at RAPIDO'13
- PhD committees: Yilun Wu (Cross-stack System Design for Energy Efficient Intermittent Computing) Ivan Miketic (Hardware Security Techniques against Information Leakage and Counterfeiting in Integrated Circuits), Prashant Pandey (Fast and Space-Efficient Maps for Large Data Sets), Weicheng Liu (Low Voltage Clocking Methodologies for Nanoscale ICs), Tan Li (Harness Multicore Parallelism for High Performance Data Replication), Fatima Zarinni (Understanding and Improving Performance in Next-Generation WiFi and Cellular Networks), Mingwei Zhang (Static Binary Instrumentation with Applications to COTS Software Security), Niranjan Hasabnis (Infrastructure for Architecture-independent Binary Analysis and Transformation), Vasily Tarasov (Multi-dimensional Analysis of I/O Workloads for Modern Storage Systems), Zhichao Li (GreenDM: A Versatile Tiering Hybrid Drive for the Trade-Off Evaluation of Performance, Energy, and Endurance), Cheng-Chun (William) Tu (Memory-based Rack-area Network)
- MS committees: Amogh Dadhich (Minimizing Checkpointing Costs in Intermittent Computing Systems using SRAM), Bharath Kumar Reddy Vangoor (To FUSE or not to FUSE?), Kavita Agarwal (A Study of Virtualization Overheads), Arun Olappamanna Vasudevan (Finding the right balance - Security vs Performance with Network Storage Systems)
- Co-developer of CloudSuite, a benchmark suite for scale-out workloads.
- Co-developer of FLEXUS, a scalable, full-system, cycle-accurate multi-processor and multi-core simulation framework between 2005 and 2012.
- SIMFLEX and ProtoFlex: Fast, Accurate, and Flexible Simulation of Computer Systems Tutorial at
- 2010 IEEE International Symposium on Workload Characterization (IISWC). Atlanta, GA, December 2010 with Eric Chung, Pejman Lotfi-Kamran, and Michael Papamichael.
- 42st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO). New York, NY, December 2009 with Eric Chung and Michael Papamichael.
- 17th International Conference on Parallel Architectures and Compilation Techniques (PACT), Toronto, Canada, October 2008 with Eric Chung and Nikos Hardavellas.
- Organizer of the Fall 2009 weekly seminar of the Systems Labs at Ecole Polytechnique Fédérale de Lausanne.
- Organizer of the Fall 2007 weekly seminar of the Computer Architecture Lab at Carnegie Mellon (CALCM).
- Senior Member: IEEE, Member: ACM SIGARCH, ACM SIGMICRO, ACM SIGOPS, HiPEAC Associate.
Funding
- Missile Defence Agency - Energy Efficient and Fault Tolerant Acceleration of Deep Neural Networks
Co-PI, $4,660,791, 3/13/2025 - SUNY-IBM AI Collaborative Research Alliance
PI, $100,000, 6/01/2024 - AMD Corporation - FPGA Hardware for research
Donation, equipment ($7,717), 6/25/2023 - Ampere Computing - ARM Server Hardware for research
Donation, equipment ($17,400), 1/10/2023 - Stony Brook University-Brookhaven National Lab Seed Grant - Exploration of FPGAs for Real-Time ML-Based Data Compression in sPHENIX
Co-PI ,$37,000, 8/1/2022 - 3/1/2023 - National Science Foundation - SHF: Small: Massively Parallel Server Processors
PI, $600,000 (+$10,000 REU), 6/15/2022 - 5/31/2025 - OVPR Revise&Resubmit - Distributed Protocol Offload using FPGA SmartNICs
Co-PI, $13,000, 4/22/2022 - AMD Corporation - FPGA Hardware for research
Donation, equipment ($13,195), 3/9/2022 - Ampere Computing - ARM Server Hardware for research
Donation, equipment ($32,000), 5/28/2021 - National Science Foundation - SHF: Small: Sparsity-Aware Hardware Accelerators for Natural Language Processing with Transformers
Co-PI, $500,000, 10/01/2020 - 9/30/2023 - Stony Brook University-Brookhaven National Lab Seed Grant - Software Assist for Hardware-Managed Virtual Memory on FPGA Accelerators
PI, $37,000, 8/1/2020 - 3/1/2022 - Xilinx Corporation - FPGA Hardware for research
Donation, equipment ($6,495), 6/16/2020 - Xilinx Corporation - FPGA Hardware for research
Donation, equipment ($6,495), 2/20/2020 - National Science Foundation - MRI: Acquisition of Heterogeneous Computer System for Machine Learning
Co-PI, $561,000, 7/15/2019 - 7/14/2022 - National Science Foundation / Intel Corporation - FoMR: IPC Improvement through Hardware Memoization
PI, $400,000, 8/1/2019 - 7/31/2022 - Telluric Labs LLC / Department of Energy - IP Access Gateway
PI, $168,000, 4/8/2019 - 4/7/2020 - National Science Foundation - CSR: Medium: Approximate Membership Query Data Structures in Computational Biology and Storage
Co-PI, $1,200,000, 8/15/2018 - 8/14/2022 - Intel Corporation - FPGA Hardware for research
Donation, equipment ($5,500), 6/22/2018 - National Science Foundation - SPX: Harnessing the Power of High-Bandwidth Memory via Provably Efficient Parallel Algorithms
PI, $750,000 ($500,000 SBU, $250,000 WUSTL), 9/15/2017 - 8/14/2021 - Xilinx Corporation - FPGA Hardware for research
Donation, equipment ($7,000), 7/28/2017 - Samsung - SSD Hardware for research
Donation, equipment ($2,000), 7/6/2017 - National Science Foundation - Domestic student travel grant funding for IISWC
PI, $15,000, 6/01/2017 - 12/31/2017 - National Science Foundation - EAGER: Measuring the Stability of Web Links
Co-PI, $89,200, 4/15/2017 - 10/15/2017 - National Science Foundation - Research Experiences for Undergraduates: Secure and Efficient Cloud Infrastructure and Accessibility Services
PI, $21,900, 8/10/2016 - 8/9/2017 - National Science Foundation - EAGER: Preliminary Study to Demonstrate Feasibility and Advantages of Massively Parallel Server Processors
Co-PI, $146,000, 10/1/2016 - 9/30/2017 - Oracle Labs - Exploring Custom Graph Algorithms with PGX and Green-Marl
Gift, $55,000, 8/17/2016 - Google - Taming the Killer Microsecond
Gift, $58,500, 9/2/2016 - National Science Foundation - XPS: FPGA Cloud Platform for Deep Learning, Applications in Computer Vision
PI, $875,000 ($574,000 SBU, $301,000 UNC), 9/1/2015 - 8/31/2019 - Intel Corporation - Hardware for research
Donation, equipment ($21,600), 8/6/2015 - National Science Foundation - CAREER: Leveraging temporal streams for micro-architectural innovation in data center servers
PI, $500,000, 2/15/2015 - 1/31/2020 - National Science Foundation - EAGER: Preliminary Study to Demonstrate the Performance and Power Advantages of FPGAs for Deep Learning in Computer Vision
PI, $95,000, 8/1/2014 - 7/31/2016 - Altera Corporation - FPGA Hardware for research
Donation, equipment ($16,000), 10/22/2014 - Cavium - Support of research activities
Gift, $34,400 + equipment, 7/17/2014 - National Science Foundation - CRI: Secure and Efficient Cloud Infrastructure and Accessibility Services
PI, $200,000, 9/1/2014 - 8/31/2017 - Semiconductor Research Corporation - Flexible Hardware Acceleration of the Network Stack for Performance and Energy Efficiency
PI, $300,000, 1/1/2014 - 1/31/2017
Advisees
PhD (6 students)- Ahmad Javadi, 2025-present
- Kevin Wei, 2024-present
- Natheesan Ratnasegar, 2022-present
- Hieu Mai, 2021-present
- Farid Samandi, 2019-present
- Reza Ali Modadi, 2018-present
- Yongming Shen, 2014-2021
- Shenghsun Cho, 2014-2021
- Varun Agrawal, 2013-2020
- Sergey Madaminov, 2016-2022
- Zavosh Mottahedeh, 2019-2023
- Raveendra Soori, 2018-2020, NUCAlloc: Fine-Grained Block Placement in Hashed Last-Level NUCA Caches
- Mina Abbasi Dinani, 2016-2020, Massively Parallel Server Processors
- Raghav Dogra, 2017-2018, Predictive Batching for Deep Learning Inference Servers
- Manoj Alwani, 2015-2016, Fused Convolutional Neural Network Accelerators
- Tapti Palit, 2014-2015, Benchmarking Network-Intensive Applications
- Aakshintala Amogh, Aavuty Rajesh, Abhiroop Dabral, Abhishek Chauhan, Abhishek Patil, Aditi Singh, Ajay Gopal Krishna, Ajay Paddayuru Shreepathi Akshay Kale, Alok Thatikunta, Anirudh Mallick, Anish Philip, Ankit Dewan, Anurag Porripireddi, Arjun Mathew Dan, Arnabjyoti Kalita, Balaji Srinivasan, Basavaraj Kaladagi, Bhavya Agarwal, Bhuvnesh Kumar Biswaranjan Panda, Chaitanya Chakka Krishna, Chidambaram Ramanathan, Devashish Thakur, Dhruva Kumar Devineni, Dylan Scott, Gangabarani Balakrishnan, Gaurav Aggarwal, Harinath Kanchu, Heta Ashit Saraiya, Jacob Samuel Harder, Jashwanth Sajja, Jerrin Shaji George, Jiemin Zeng, Jihyu Yang, Kai-Chieh Huang, Karan Pugla, Komal Agrawal, Kunal Chadha, Kushal Dhar, Malvika Modi, Mandar Naik, Manthan Singh, Michael Laurence Anderson, Mingchen Zhang, Mitesh Kumar Singh, Neeraj Dixit, Palit Tapti, Parag Gupta, Parikshit Bhattacharjee, Paul Mathew, Pratik Sudarshan Pantode, Priyanka Nath, Pruthvi Kumar Madugundu, Rahul Gadi, Rajendra Kumar Raghupatruni, Ravi Prakash Pandey, Ravikiran Patil, Rohit Chandramohanan, Romeyo Dsouza, Sahil Parmar, Sai Brahmadevara, Sai Gaddam, Sai Madan Mohan Reddy Patlolla, Sai Shashank Gaddam, Saptarshi Sen, Saraj Munjal, Sayli Yogesh Karnik, Scott Harvey, Shantanu Potdar, Shanuj Shekhar, Shihao Wen, Shreyas Prabhu Binnamangala, Shubham Jawandhiya, Shubham Pandurang Zope, Shubham Rajesh Jawandhiya, Shubhanga Narasimha, Shyam Sundar Chandrasekaran, Sneha Pathrose, Sri Krishna Jayadev Peddibhotla, Srinath Battula Yagna Reddy, Steven Maggio, Subin Mathew, Sumeeth Kyathanahalli, Sunad S Bhandary, Tamilmani Manoharan, Taylor Giles, Toby Babu, Vaibhav Srivastav Bandikatla, Vamshi Muthineni, Varsha Venkatesh, Vertika Vaid Vinay Krishnamurthy, Vinay Shetty, Vishal Nayak, Yigong Wang, Yu-Jiun Kao, Yuxuan Shui
- Alan Hao, David Pokryvailo, Dylan Scott, Julian Shin, Kevin Zhao, Lise Ho, Mehrab Hoque, Tahsin Ahmed, Yang Sheng Fang
- Alan Hau, Benjamin Michalowicz, Brandon Paradiso, Edgar Samudio, Eniola Abdul, Gabriel Kim, Haonan Huang, Jacky Xie, Janet Vorobyeva, Jessica Chan, John Ranzie, Julian Leung, Kevin Wei, Kihoon Kim, Lawrence Lin, Matthew Ng, Minqi (Jason) Shi, Mrunal Patel, Nikitha Kannan, Qi Zhang, Roman Scher, Surya Patil
personal
Travel
These days, it seems like everyone's favorite hobby is to travel. Below is a map that shows the countries I visited.
Office
New Computer Science building, office 343343 New Computer Science
Stony Brook University
Stony Brook, NY 11794-2424
Phone
Office: (631) 632-8449Fax: (631) 632-8334
If you need to speak with me, please feel free to drop by my office at any time. However, to ensure that I will be there and not busy, it's always best to send an email ahead of your visit.
If you prefer to explicitly schedule an appointment, please send me email. You can check my general availability by consulting my calendar.
Latest News
March 13, 2025: The MDA funds our work toward Energy Efficient and Fault Tolerant Acceleration of Deep Neural Networks.
December 2, 2024: A Case for Hardware Memoization in Server CPUs will appear in CAL.
October 10, 2024: Ready or Not, Here I Come: Characterizing the Security of Prematurely-public Web Applications will appear at ACSAC'24.
September 6, 2024: Xipeng Shen and I will be serving as co-Program Chairs for International Conference on Supercomputing (ICS'25). Please submit your best work!
June 1, 2024: The SUNY-IBM AI Research Alliance funds our work on MLISA, an instruction set architecture extension for AI Accelerators.
April 26, 2024: Our paper NUCAlloc: Fine-Grained Block Placement in Hashed Last-Level NUCA Caches will appear at ICS'24.