James C. Hoe is Professor of Electrical and Computer Engineering at Carnegie Mellon University (College of Engineering). He is on sabbatical at MangoBoost and directs research in computer architecture, reconfigurable computing, and high-level hardware design. Education Ph.D., Electrical Engineering and Computer Science, MIT (2000) M.S., Electrical Engineering and Computer Science, MIT (1994) B.S., Electrical Engineering and Computer Science, UC Berkeley (1992) Research Interests Professor Hoe’s work spans computer architecture , reconfigurable computing , FPGA architectures , and high-level hardware synthesis . His group created the CoRAM abstraction for virtualized FPGA computing and leads efforts in power-efficient accelerators, in-network computing, and security-oriented FPGA systems. Scientific Awards IEEE Fellow (2013) Intel Outstanding Researcher Award (2021) Research Funding & Projects Intel / VMware Crossroads 3D-FPGA Academic Research Center – co-leading exploration of FPGA roles in future datacenters. DARPA BRASS program ($2.7 M, 4 years) – ensuring long-lived software systems remain robust to resource changes. Pigasus open-source IDS – world’s fastest FPGA-accelerated intrusion-detection system (100 Gb/s on one server). Labs & Teams He heads activities within the Computer Architecture Lab at Carnegie Mellon (CALCM) , supervising graduate researchers on CoRAM++, SPIRAL autotuning, and FPGA overlays for stream processing.
Weiping Tang is a Professor of Pharmaceutical Sciences and Chemistry at the University of Wisconsin-Madison, holding the Janis Apinis Professorship in the School of Pharmacy and the Vilas Distinguished Achievement Professorship. He also serves as Director of the Medicinal Chemistry Center at the School of Pharmacy and maintains a faculty appointment with the Department of Chemistry in the College of Letters and Science. Janis Apinis Professor of Pharmaceutical Sciences Vilas Distinguished Achievement Professor Director of Medicinal Chemistry Center Faculty Appointment with Department of Chemistry Dr. Tang received his B.S. in Chemistry from Peking University in 1997, M.S. in Chemistry from New York University in 1999, Ph.D. in Organic Chemistry from Stanford University in 2005, and completed a postdoctoral fellowship in Medicinal Chemistry, Chemical Biology and Drug Discovery at Harvard University in 2007. Dr. Tang's research program focuses on drug discovery for cancer, infectious diseases, and neurodegenerative disorders through three interconnected areas: Organic Synthesis (advancing glycoscience through novel carbohydrate synthesis technologies), Medicinal Chemistry (developing small molecules that selectively remove disease-associated proteins), and Chemical Biology (dissecting biological pathways using novel small molecule probes). His group operates as an interdisciplinary team where chemists and biologists collaborate closely on drug discovery projects, with particular emphasis on developing novel degraders for disease-causing proteins. Analysis of Dr. Tang's publication record reveals a significant shift toward targeted protein degradation technologies, particularly PROTACs and molecular glues, while maintaining strong foundations in carbohydrate chemistry. His most impactful recent work includes developing degraders for extracellular and membrane proteins (previously considered 'undruggable'), creating rapid synthesis platforms like Rapid-TAC and Rapid-Glue, and advancing understanding of ternary complex formation for novel PROTAC design. His research spans both chemical methodology development and therapeutic applications across multiple disease areas. Vilas Distinguished Achievement Professorship Janis Apinis Professorship Numerous high-impact publications in leading chemistry and pharmacology journals Editor's pick and hot paper designations for significant contributions Dr. Tang mentors a diverse team of graduate students, postdoctoral fellows, and staff scientists with expertise spanning synthetic chemistry, medicinal chemistry, carbohydrate chemistry, computational chemistry, biochemistry, and cell biology. His group has developed innovative platforms for the rapid synthesis of protein degraders and has made significant contributions to understanding the mechanisms of action for these novel therapeutics. Current research includes developing selective degraders for cancer targets like RIPK1, BRD4, and CARM1, as well as advancing delivery systems for clinical translation. The Tang Research Group maintains state-of-the-art facilities within the School of Pharmacy at UW-Madison, equipped for comprehensive chemical synthesis, compound characterization, and biological evaluation. The group actively collaborates with researchers across campus and with industry partners to advance discoveries toward clinical applications, with particular focus on cancer therapeutics and protein degradation technologies.
Dr. Damien Charrieras is an Associate Professor at the School of Creative Media , City University of Hong Kong, where he serves as Program Leader for the Master of Art in Creative Media and deputy program leader for the PhD in Creative Media. His work bridges cultural studies, new media theory, and the intersection of financial technologies with artistic practices through the ACIM Laboratory for Interventions in Speculative Finance . Doctoral research on digital artists' trajectories in Montreal FRQSC Postdoctoral Fellowship at McGill University Research spans game engine design , datafication of creativity , blockchain in art , and post-anthropocentric creative processes . With over HK$3.14M in grants as Principal Investigator, he explores situated digital creativity in urban contexts, critical worldbuilding pedagogy , and the mediation of technical systems in cultural production. His publications in Cities , Organized Sound , and Human Relations analyze the reconfiguration of artistic practices through software infrastructures and automation paradigms. Scientific awards include: FRQSC Postdoctoral Fellowship
Kuldeep S. Meel is the Stephen Fleming Early-Career Associate Professor at the School of Computer Science, Georgia Institute of Technology, and an Associate Professor at the University of Toronto (on leave). He previously held a NUS Presidential Young Professorship at the National University of Singapore. His research focuses on automated reasoning, aiming to enable computing systems to handle uncertain real-world environments through scalable techniques integrating randomized algorithms, statistical inference, formal methods, distribution testing, and software engineering. Core research areas: Automated Reasoning, Formal Methods, Approximate Model Counting, Probabilistic Inference, Constraint Solving His research group has achieved significant recognition in both individual awards and publications. Key trends in his recent work include advancing model counting algorithms, developing frameworks for probabilistic explanations, and improving scalability in formal verification and constraint satisfaction. His tools have consistently ranked top in international competitions, demonstrating practical impact in automated reasoning. 2019 NRF Fellowship for AI 2022 ACP Early Career Researcher Award 2020 IEEE Intelligent Systems AI's 10 to Watch Top placements in Model Counting, SAT, and CAV competitions He mentors a diverse group of PhD and Master's students and collaborates with institutions worldwide. His group's publications span premier conferences in AI, formal methods, and design automation, reflecting interdisciplinary contributions to theoretical and applied computer science.
David Bindel is an Associate Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences, College of Engineering, and Cornell Ann S. Bowers College of Computing and Information Science. He earned his Ph.D. in Mathematics from the University of California, Berkeley in 2006. His research focuses on applied numerical linear algebra, eigenvalue problems, and their applications in plasma physics, network analysis, and nonlinear systems. He develops methods for analyzing complex systems, including magnetic confinement in stellarators, stability of MHD systems, and community detection in networks. His work bridges theoretical foundations with practical computational tools, such as formal verification of linear algebra algorithms and scalable Gaussian process models. Bindel’s research explores the interplay between structure and computation, leveraging eigenvalue analysis to address challenges in computer vision, opinion dynamics, and engineering design. He has contributed to advancements in numerical methods for large-scale systems, including iterative solvers, spectral approximation techniques, and stochastic optimization. His interdisciplinary approach spans applied mathematics, computer science, and physics, with applications in fusion energy, machine learning, and network science. Recent work highlights include high-order expansions for magnetic confinement, adaptive filtering for dynamical systems, and Bayesian optimization strategies. His publications emphasize rigorous analysis alongside computational scalability, addressing both theoretical and practical aspects of modern scientific computing. Despite no explicitly listed awards, his contributions reflect significant impact in his fields.
Jeannette Bohg is an Assistant Professor of Computer Science at Stanford University, directing the Interactive Perception and Robot Learning Lab. Previously, she was a group leader at the Autonomous Motion Department (AMD) of the MPI for Intelligent Systems (2012-2017). She holds a PhD from KTH Royal Institute of Technology (Stockholm) and degrees from Chalmers University and TU Dresden. Her research focuses on perception, learning, and real-time multi-modal methods for autonomous robotic manipulation and grasping, aiming to bridge principles of human sensorimotor coordination with robotic implementation. Education: PhD in Robotics (KTH), MSc in Art & Technology (Chalmers), Diploma in Computer Science (TU Dresden) Research interests include developing goal-directed, real-time robotic systems capable of meaningful feedback for execution and learning. Key areas are dexterous manipulation, imitation learning, and cross-embodiment policy transfer. Notable contributions include the TidyBot platform and work on force-aware surgical robotics. Awards include the 2019 IEEE ICRA Best Paper Award, 2019 IEEE RA Early Career Award, and 2020 RSS Early Career Award. Her lab explores intersections of robotics, ML, and computer vision. Advising: Actively mentoring students/postdocs in manipulation, perception, and learning. Grants and collaborations span NSF, Stanford AI Lab, and industry partnerships. Future work emphasizes robust real-world deployment and human-robot collaboration. Labs/Teams: Leads the Interactive Perception and Robot Learning Lab, contributing to Stanford’s AI ecosystem. Previously managed the MPI AMD group, fostering interdisciplinary research in autonomous systems.
John Evans is an Associate Professor and Jack Rominger Faculty Fellow in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, affiliated with the Applied Mathematics program. He serves as Associate Chair for Undergraduate Curriculum and is part of the Aerospace Mechanics Research Center (AMREC). His research focuses on computational mechanics, particularly fluid dynamics, fluid-structure interaction, and turbulence modeling using high-order and structure-preserving methods. Evans holds a PhD (2011) and MS (2008) in Computational and Applied Mathematics from the University of Texas at Austin, and dual BS/MS degrees in Mathematics and Applied Mathematics from Rensselaer Polytechnic Institute (2006). Before joining CU Boulder, he was a postdoctoral fellow at the Institute for Computational Engineering and Sciences (ICES). His research interests include isogeometric analysis, immersed methods, and data-driven turbulence modeling. Notable contributions include development of divergence-conforming discretizations for incompressible flows, stabilized collocation methods, and invariant subgrid stress models. He leads the AMREC lab and collaborates on plasma-fueled propulsion systems and geometrically sensitive simulations. Key Awards: 2021: Rocky Mountain AIAA Educator of the Year 2021: Gallagher Young Investigator Medal 2019-2021: Clarivate Highly Cited Researcher Professional Activities: Editor of Engineering Computations, Senior AIAA Member, Simons Visiting Professor (2019) Evans' work bridges advanced numerical methods with real-world engineering challenges. His lab develops open-source tools like XIGA for multi-material problems and focuses on immersive simulation environments. Current projects explore turbulence closure models, plasma propulsion, and topology optimization with B-spline-based approaches.
Shiri Azenkot is an Associate Professor at the Jacobs Technion-Cornell Institute at Cornell Tech and Cornell University, affiliated with the Information Science Department and Technion’s Computer Science Department. Her research focuses on accessibility innovations in emerging technologies, particularly addressing needs of people with vision impairments and neurodiverse populations. She holds a PhD from the University of Washington, advised by Richard Ladner and Jacob Wobbrock, and has been recognized with prestigious awards including the NSF Graduate Research Fellowship. Education: PhD in Computer Science & Engineering from University of Washington (advisors: Richard Ladner, Jacob Wobbrock). Research interests include VR/AR accessibility, assistive technology design, inclusive education tools, and ethical AI applications. Current projects explore social VR avatars for invisible disabilities, AR navigation aids, and AI moderation systems against ableist hate speech. Her work is funded by NSF, AOL, Verizon, and Facebook. Recent publications address video accessibility for ADHD users, AI-driven scene descriptions for blind users, and tactile learning materials co-designed with educators. She leads the XR Access initiative promoting inclusive virtual/augmented reality. Awards include the UW Graduate Medal (2020), NSF CRII Award (2017), and AT&T Labs Fellowship (2014). Her research bridges academic innovation with industry impact through collaborations with tech companies and disability advocacy groups.
André DeHon is the Oliver C. Boileau Jr. and Nan Eleze Boileau Professor of Electrical Engineering at the University of Pennsylvania, affiliated with Electrical and Systems Engineering (ESE) and Computer and Information Science (CIS). He chairs the Computer Engineering (CMPE) program and directs the CyberSavvy Security Center. His research focuses on reconfigurable computing, FPGA architectures, computer security, and energy-efficient hardware design. He holds a Ph.D. and M.S. from MIT and a B.S. from MIT's Lincoln School. Research interests include reconfigurable computing, FPGA interconnect, hardware security, and fault-tolerant systems. Notable achievements include the SEVER & PROTECT DARPA award and IEEE/ACM Fellowships. Recent work addresses fast FPGA compilation (HiPR, PLD), security through compartmentalization (μSCOPE, SCALPEL), and partial reconfiguration techniques. Teaching includes courses on hardware security, system-on-chip architecture, and digital audio basics. Over 200 publications span FPGA design, network-on-chip optimization, and molecular-scale computing. His labs (Implementation of Computation Group) explore physical implementation of computations through hardware-software co-design.
Michael S. Brown is a Professor and Canada Research Chair at York University's Department of Electrical Engineering and Computer Science (EECS). He also serves as Senior Director at the Samsung AI Center in Toronto, Canada. His research focuses on computer vision, image processing, and computer graphics, with a deep specialization in camera imaging pipelines, color theory, and AI-driven ISP optimization. He has organized major conferences like ProCams, eHeritage, WACV, and ICCV, and holds editorial roles in journals like TPAMI and IJCV. He is renowned for his work on computational color constancy, ISP hardware algorithms, and AI-based image enhancement techniques. His recent ICCV 2023 tutorial detailed modern camera pipelines and AI applications in ISP components. His research is supported by grants from NSERC, Samsung, Adobe, Google, and Microsoft. Brown advises numerous graduate students and has mentored over 30 alumni now in academia and industry roles at Meta, Samsung, Microsoft, and startups. His lab focuses on camera systems, noise modeling, and cross-platform color management, with contributions to open-source datasets and software platforms for ISP experimentation.
Pinchuan Ong is an Assistant Professor in the Strategy and Policy Department at the National University of Singapore (NUS) Business School. He holds dual bachelor’s degrees from NUS (B.Eng. and B.Soc.Sci.) and a Ph.D. in Economics from Northwestern University. Prior to academia, he worked as an economist at Singapore’s Ministry of Trade and Industry. His research focuses on labor economics, public economics, and applied microeconomics. Key areas include labor supply disincentives from child support obligations, taxation effects on labor participation, automation’s impact on labor markets, and the socioeconomic consequences of energy pricing on health outcomes. He has investigated winter mortality linked to heating costs and housing market risks influencing labor demand. Recent research trends emphasize policy-relevant analyses of taxation, automation, and public goods provision. His work bridges theoretical economic frameworks with empirical policy evaluation, often addressing labor market dynamics and welfare outcomes. Ong’s upcoming speaking engagements include the Hong Kong Labor Symposium (June 2024), ROCKWOOL Foundation visits in Berlin, and the BSE Summer Forum in Barcelona. He is open to collaborations during these travels. His full CV and publications are accessible via his personal webpage.
Deval Desai serves as Reader in International Economic Law at the University of Edinburgh's Edinburgh Law School, a position he has held since 2020 after serving as Lecturer from 2020-2023. His academic career includes research positions at Harvard Law School and the Geneva Graduate Institute. Dr. Desai also brings extensive practical experience from a decade working with the World Bank on rule of law and governance in sub-Saharan Africa, as well as advising the United Nations on rule of law issues. Dr. Desai's educational background includes an MA in History and French Literature from Oxford University, followed by legal training at City University/BPP Law School (PGDipL and PGDipLP), and advanced law degrees (LLM and SJD) from Harvard Law School. At Harvard, he held prestigious fellowships including the Byse Fellowship, Program on Negotiation Next Generation Fellowship, and Institute for Global Law and Policy Fellowship. MA (Oxon), History and French Literature PGDipL, PGDipLP, City University/BPP Law School LLM, Harvard Law School SJD, Harvard Law School Dr. Desai's research centers on law and development, administrative law and regulation, theories of the state, and patterns of knowledge and authority across the Global North and South. His work examines institutional reform processes, particularly how expertise and knowledge operate within rule of law initiatives. His interdisciplinary approach draws from legal and social theory, development studies, international relations, and performance studies, as evidenced in his monograph Expert Ignorance (Cambridge University Press). His recent work focuses on fiscal sociology, administrative law in the Global South, and the politics of social welfare provision. Dr. Desai's publications span leading journals in law, political science, and development studies, revealing a consistent focus on the intersections between legal institutions, governance, and development. His work demonstrates increasing engagement with comparative methodologies and critical perspectives on knowledge production in global governance. Recent articles show particular attention to fiscal policy, welfare systems, and responses to global crises like the Covid-19 pandemic, with comparative studies between India and European contexts. Dame Muriel Spark Medal (2024, Royal Society of Edinburgh) Chancellor's 'Rising Star' Award (2023, University of Edinburgh) Member of the Young Academy of Scotland Fellow of the Royal Society of Arts Fellow of the Young Academy of Europe Dr. Desai has secured significant research funding from diverse international sources, including a £2.1 million Swiss National Science Foundation Sinergia grant titled 'Reversing the Gaze: Towards Post-Comparative Area Studies' where he serves as PI. He also leads projects funded by the British Academy, University of Edinburgh's Big Ideas Accelerator, Scottish Funding Council, and Foreign, Commonwealth, and Development Office. His commitment to mentoring is evident through his recognition with the Susan Manning Award for Inspiring Mentor and his leadership in establishing programs like the Global Scholars' Academy at the Geneva Graduate Institute and the Global Justice summer school at CEU. As editor-in-chief of the Cambridge University Press book series 'Elements in Legal Theory and the Global South' and serving on multiple editorial boards, Dr. Desai plays a significant role in shaping scholarly discourse. His current research projects examine 'loss' in legal institutions guiding transitional processes, constitutional implications of fiscal arrangements in fragile contexts, and social welfare provision in India and Italy.
Affiliation & Education Scott Hauck is a Professor at the University of Washington's Department of Electrical & Computer Engineering and an Adjunct Professor in Computer Science & Engineering. He leads the Adaptive Computing Machines and Emulators (ACME) Lab . He earned his BS in EECS from UC Berkeley (1990), and MS/PhD in CSE from the University of Washington (1992/1995). Research Focus Dr. Hauck specializes in FPGA-based reconfigurable computing with applications in: Quantum Computing: FPGA controllers for trapped-ion quantum systems enabling precise laser control and quantum state readout. Medical Imaging: Portable radiation sensors for personalized cancer therapy and PET scanner enhancements. High-Energy Physics: FPGA readout systems for ATLAS pixel detectors at CERN's Large Hadron Collider. AI Acceleration: Real-time machine learning inference for scientific applications via projects like hls4ml. His work bridges hardware innovation with computational physics, emphasizing real-time processing and low-latency systems. Publication Trends Recent research focuses on FPGA-accelerated machine learning for particle physics (e.g., transformer networks for LHC trigger systems) and quantum computing instrumentation. Earlier work established foundations in reconfigurable computing architectures and medical imaging electronics. Awards & Recognition Distinguished Teaching Award, University of Washington (2010) Advising & Funding Leads the ACME Lab with extensive funding from NSF, DARPA, NIH, DOE, and industry partners including Intel, Xilinx, and Microsoft. Mentored over 30 MS/PhD students in VLSI, reconfigurable systems, and scientific computing. Collaborations & Labs Directs the ACME Lab (EE1-307), collaborating with UW Radiology (Prof. Robert Miyaoka), UW Physics (Prof. Shih-Chieh Hsu), and Drexel University (Prof. Josh Agar). Projects include quantum control systems, LHC readout electronics, and medical sensor networks.
Richard Jochelson serves as Dean of Law at the Faculty of Law, University of Manitoba (Robson Hall), a position he has held since July 1, 2016. Previously, he taught criminal law for 10 years at the University of Winnipeg. Dr. Jochelson holds a Ph.D. in Law from Osgoode Hall Law School at York University, an LLM from the University of Toronto Faculty of Law, an LL.B. with Gold Medal from the University of Calgary Faculty of Law, and a B.Sc. in Zoology with Distinction from the same institution. He completed his legal training as a clerk at the Alberta Court of Appeal and Court of Queen's Bench before working at a major Canadian law firm. Dr. Jochelson's research program centers on critical issues in criminal justice and constitutional law, with primary interests in police powers jurisprudence, sexual regulation (particularly obscenity and indecency law), jury systems and representativeness, and legal pedagogy. His interdisciplinary approach bridges law with sociology and psychology, bringing empirical and theoretical rigor to legal scholarship. His work consistently addresses social justice concerns, examining how vulnerable populations interact with the justice system and how concepts like risk, precaution, and visibility shape legal decision-making. He has developed a distinctive methodology combining doctrinal analysis with empirical research on judicial behavior and jury decision-making. His recent publications reveal evolving scholarly priorities that respond to contemporary legal challenges. The 2025 article "Morbid Matters" addresses medical assistance in dying within federal corrections, while his 2024 works on youth terrorism cases and agnotology demonstrate expansion into new interdisciplinary territories. His longstanding commitment to police powers scholarship continues with "Ancillary Police Powers in Canada" (2024). The pandemic period saw significant contributions to understanding digital justice, mental health in legal education, and remote court proceedings. His criminal law scholarship maintains focus on jury representativeness, particularly regarding Indigenous inclusion following Bill C-75's elimination of peremptory challenges. Students' Teacher Recognition Award (CATL) - 2018 Dr. Jochelson has secured multiple SSHRC Insight Grants as both Principal and Co-investigator, demonstrating his ability to lead interdisciplinary research teams. His mentorship extends to junior academics and students, with several publications co-authored with emerging scholars. He has built significant research infrastructure, notably assembling nearly 40 interdisciplinary scholars across Canada for Robsoncrim.com, which has elevated the Criminal Law Edition of the Manitoba Law Journal to prominence as one of Canada's preeminent criminal law publications. As Dean of Law, Dr. Jochelson provides leadership in academic governance and legal education innovation. His service includes extensive committee work on academic affairs, workload policy, and hiring/tenure committees. His commitment to universal design principles informs both his teaching approach and administrative leadership, emphasizing accessibility and student-centered pedagogy that allows flexible evaluation methods tailored to individual learning preferences.
Sainyam Galhotra is an Assistant Professor in the Department of Computer Science at Cornell University. His research focuses on developing data science tools for trustworthy analytics, integrating causal inference, data management, and machine learning to enhance robustness, explainability, and fairness in algorithmic systems. PhD: University of Massachusetts Amherst (2020), advised by Barna Saha B.Tech: Indian Institute of Technology Delhi (2014), advised by Amitabha Bagchi Postdoctoral Research: University of Chicago (Computing Innovation Fellow) His work spans artificial intelligence, causal inference, and responsible data science, emphasizing ethical algorithm design and reliable data integration. Recent publications highlight advancements in fair clustering, causal feature selection, and entity resolution frameworks. His research trends from 2023–2024 include contributions to spatio-temporal data correlation, community detection in geometric graphs, and distribution-aware dataset search. Key themes are fairness in machine learning, causal modeling, and scalable data management solutions. Computing Innovation Fellowship (2021) DAAD AInet Fellow (2021) ACM SIGMOD Entity Resolution Programming Contest Finalist (2021) Krithi Ramamritham Computer Science Scholarship (2019) BEST Paper Award in SIGSOFT FSE 2017 He actively seeks PhD or Master’s students interested in data science and trustworthy AI. Contact via email: sg@cs.cornell.edu .
