2026 Pre-Conference Workshops

Bio-IT World is pleased to offer morning and afternoon pre-conference on Tuesday, May 19. They are designed to be instructional, interactive and provide in-depth information on a specific topic. They allow for one-on-one interaction and provide a great way to explain more technical aspects that would otherwise not be covered during the main conference tracks that take place Thursday-Friday.

Engage directly with industry experts and thought leaders.
Apply new methodologies in interactive, small-group settings.
Gain hands-on experience with cutting-edge tools and technologies shaping the future of life sciences.

Separate registration required.

Workshops

Tuesday, May 19, 2026 9:00 AM – 12:00 PM

W1 W1: Building Workflows and Advancing FAIR Bioinformatics Practices: A Practical Lab Using the Playbook Workflow Builder (PWB)

This hands-on workshop introduces the Playbook Workflow Builder (PWB), guiding participants through step-by-step recipes to create reusable, transparent, and interoperable bioinformatics workflows aligned with FAIR principles. Attendees will analyze genes, gene sets, and other omics datasets, generate hypotheses, and build shareable workflow components without coding. Working in groups, participants will develop use cases for discovery and leave able to extend PWB, contribute reproducible analyses, and support collaborative research ecosystems.

9:00 AM Chairperson's Remarks

Ishwar Chandramouliswaran, Program Director, Office of Data Science Strategy, NIH

9:10 AM Building Workflows and Advancing FAIR Bioinformatics Practices: A Practical Lab Using the Playbook Workflow Builder (PWB)

Daniel Clarke, Biomedical Software Developer, Icahn School of Medicine at Mount Sinai

WORKSHOP OBJECTIVES:Â The Playbook Workflow Builder (PWB) is a web-based platform that facilitates the interactive construction of bioinformatics workflows by enabling users to utilize an ever-growing network of input datasets, semantically annotated API endpoints, and data visualization tools. Via a user-friendly web-based user interface, workflows can be constructed from contributed building blocks without technical expertise. Workflows can be alternatively created using a chatbot. The output of the workflows includes an interactive online report, a publication-like PDF file, and a YouTube video. The workshop will demonstrate how to use the platform via interactive sessions, as well as introduce ways for the community to contribute workflow building blocks to the platform.Â

OUTCOMES:Â Participants will gain hands-on experience analyzing genes, gene sets, and other datasets; forming hypotheses from omics data; and building workflows designed for reuse, provenance tracking, and FAIR compliance. Working in groups, participants will be able to create use cases for drug and target discovery and ask questions that would be answered by community experts. Participants will leave with the ability to conduct analysis and visualization without coding, extend PWB capabilities, and contribute workflows that are discoverable, shareable, and reproducible.Â

AUDIENCE AND PRE-REQUISITES: This workshop serves anyone seeking help analyzing omics datasets or contributing to a community ecosystem of FAIR-aligned tools and workflows. No prerequisites necessary to register for this workshop.Â

AGENDA:

9:10 â€“ 10:00 am Presentations: Tour of the Platform and Use Cases

10:00 â€“ 11:00 am Hands-On Session*: Building and Publishing Workflows with PWB

User guide: https://github.com/MaayanLab/Playbook-Workflow-Builder/blob/main/docs/user/index.mdÂ

11:00 am â€“ 12:00 pmÂ Hands-On Session*: Creating Building Blocks to Add to the PWB Platform

Developer guide: https://github.com/MaayanLab/Playbook-Workflow-Builder/blob/main/docs/index.mdÂ

*PleaseÂ bring your laptopÂ to participate in the interactive sessions.

The Playbook Workflow Builder project is partially funded by the NIH grant OT2OD036435 for the CFDE Data Coordination Center (DRC) of the CFDE. Please visit the CFDE Workbench website for more details about the CFDE and the DRC: https://info.cfde.cloud/.

PWB Website:Â https://playbook-workflow-builder.cloud/Â Â

PWB Publication:Â https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1012901

INSTRUCTOR BIOGRAPHIES:

Photo of Avi Ma'ayan, PhD, Professor & Director, Center for Bioinformatics, Pharmacological Sciences, Icahn School of Medicine at Mount Sinai — **Avi Ma'ayan, PhD, Professor & Director, Center for Bioinformatics, Pharmacological Sciences, Icahn School of Medicine at Mount Sinai**
Dr. Maâ€™ayan is a Mount Sinai Endowed Professor in Bioinformatics, Director of the Mount Sinai Center for Bioinformatics, Professor in the Department of Pharmacological Sciences, Professor in the Department of Artificial Intelligence and Human Health, and faculty member of the Icahn Genomics Institute. Dr. Ma'ayan is also a Principal Investigator of the NIH Common Fund Data Resource Center (DRC) for the Common Fund Data Ecosystem (CFDE), a NCI-funded ITCR resource center, a NIDDK-funded diabetes hypothesis platform, and the NCI-funded Mount Sinai Proteogenomic Data Analysis Center. The Ma'ayan Laboratory applies computational methods to study the inner workings of regulatory networks in mammalian cells. His research team applies machine learning and other statistical mining techniques to study how intracellular regulatory systems function as networks to control cellular processes such as differentiation, dedifferentiation, apoptosis and proliferation. The Ma'ayan Laboratory develops bioinformatics software applications to enable experimental biologists to form novel hypotheses from high-throughput omics datasets, while aiming to better understand the structure and function of regulatory networks in mammalian cellular and multi-cellular complex systems.

Photo of Daniel Clarke, Biomedical Software Developer, Icahn School of Medicine at Mount Sinai — **Daniel Clarke, Biomedical Software Developer, Icahn School of Medicine at Mount Sinai**
Daniel J. B. Clarke (MS) is a data scientist in the Maâ€™ayan Laboratory at the Icahn School of Medicine at Mount Sinai, where he develops computational methods and software systems that support biomedical data analysis. He is a lead developer of Playbook Workflow Builder (PWB), an interactive platform that composes bioinformatics workflows from modular, semantically annotated components spanning APIs, datasets, enrichment tools, and visualization modules. His broader contributions include data-driven methods, open-source research software, and infrastructure that enables scalable and reproducible analyses. He also works on tools that help researchers integrate diverse datasets and apply computational approaches across a range of biomedical research contexts.

Photo of Ishwar Chandramouliswaran, Program Director, Office of Data Science Strategy, NIH — **Ishwar Chandramouliswaran, Program Director, Office of Data Science Strategy, NIH**
Ishwar Chandramouliswaran is a Program Director and technical lead for the strategy, planning, coordination and oversight of establishing a FAIR data ecosystem at the NIH Office of Director, Office of Data Science Strategy (ODSS).

Photo of Nick Lynch, PhD, Founder & CTO, Curlew Research; Member, FAIRplus Consortium — **Nick Lynch, PhD, Founder & CTO, Curlew Research; Member, FAIRplus Consortium**
Dr. Lynch has over 25 yearsâ€™ experience in Data science & Informatics in various start-ups and biopharma. He is interested in making data more accessible for better analysis, and established Curlew Research in 2014, working with pharma/biotech and life science informatics/data science companies.

W2 W2: How to Standardize Data Science Ways of Working to Unlock Your Data Science Teamâ€™s Creativity

Build high-performing biotech data science teams in an AI-driven world. This interactive workshop covers workflows, delivery models, and hiring strategies that balance best practices with innovation, helping you select team members who thrive alongside AI tools.

9:00 AM How to Standardize Data Science Ways of Working to Unlock Your Data Science Teamâ€™s Creativity

Eric Ma, PhD, Principal Data Scientist, Moderna, Inc.

How do you standardize workflows without stifling innovation? How do you hire in an age where AI can write code? This interactive workshop explores strategies for building data science teams in biotech. Through facilitated discussion and examples, we'll examine delivery models, tactics, and hiring approaches that balance standards with creativity. Discover how to make best practices the path of least resistance while selecting members who thrive alongside AI tools.

INSTRUCTOR BIOGRAPHIES:

Photo of Eric Ma, PhD, Principal Data Scientist, Moderna, Inc. — **Eric Ma, PhD, Principal Data Scientist, Moderna, Inc.**
As Principal Data Scientist at Moderna Eric leads the Data Science and Artificial Intelligence (Research) team to accelerate science to the speed of thought. Prior to Moderna, he was at the Novartis Institutes for Biomedical Research conducting biomedical data science research with a focus on using Bayesian statistical methods in the service of discovering medicines for patients. Prior to Novartis, he was an Insight Health Data Fellow in the summer of 2017 and defended his doctoral thesis in the Department of Biological Engineering at MIT in the spring of 2017. Eric is also an open-source software developer and has led the development of pyjanitor, a clean API for cleaning data in Python, and nxviz, a visualization package for NetworkX. He is also on the core developer team of NetworkX and PyMC. In addition, he gives back to the community through code contributions, blogging, teaching, and writing. His personal life motto is found in the Gospel of Luke 12:48.

Photo of Jackie Valeri, PhD, Data Scientist, Moderna, Inc. — **Jackie Valeri, PhD, Data Scientist, Moderna, Inc.**
As a Senior Data Scientist at Moderna, I work on machine learning-guided library design for small molecules and proteins. I obtained my PhD in Biological Engineering from MIT and have worked on sequence-to-function machine learning models for RNA sequences and on graph neural networks for small molecule antibiotics discovery.

W3 W3: Next-Gen AI for Drug Discovery: From LLMs to Multi-Agent Systems

This workshop explores how artificial intelligence is advancing drug discovery. The focus is on how next-generation, agentic AI frameworks move beyond standalone large language models (LLMs) to connect data, design, and decision-making across the R&D pipeline. Attendees will gain an understanding of how next-generation, agentic AI frameworks integrate predictive modeling, generative design, and experimental validation through connections with knowledge graphs, FAIR data standards, and ELN/LIMS platforms. The session will highlight how agentic AI enables unified, AI-ready workflows spanning molecular design to translational research, driving measurable impact by accelerating discovery, enhancing traceability, and improving decision quality. Through presentations and real-world examples, participants will learn how to assess their organizationâ€™s readiness for multi-agent AI and how to apply these technologies to build smarter, reliable, and compliant R&D workflows.

Instructors:

Parthiban Srinivasan, PhD, Professor and Director, Centre for AI in Medicine, Vinayaka Mission's Research Foundation, India

Petrina Kamya, PhD, Global Head of AI Platforms & Vice President, Insilico Medicine; President, Insilico Medicine Canada

INSTRUCTOR BIOGRAPHIES:

Photo of Parthiban Srinivasan, PhD, Professor and Director, Centre for AI in Medicine, Vinayaka Mission's Research Foundation, India — **Parthiban Srinivasan, PhD, Professor and Director, Centre for AI in Medicine, Vinayaka Mission's Research Foundation, India**
Parthiban Srinivasan, an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics and later an AI consultancy, Vingyani. Then he returned to academia as a Professor of Data Science at the Indian Institute of Science Education and Research, Bhopal. Currently, Parthiban is a Professor and Director at the Center for AI in Medicine, Vinayaka Missions Research Foundation, AV Medical College and Hospital, Puducherry, India

Photo of Petrina Kamya, PhD, Global Head of AI Platforms & Vice President, Insilico Medicine; President, Insilico Medicine Canada — **Petrina Kamya, PhD, Global Head of AI Platforms & Vice President, Insilico Medicine; President, Insilico Medicine Canada**
Petrina Kamya, PhD, is the Head of AI Platforms and President of Insilico Medicine, Canada an end-to-end artificial intelligence-driven drug discovery company. Before joining Insilico, Dr. Kamya spent eight years in various roles at Chemical Computing Group that involved scientific and business-related aspects of preclinical drug discovery. In addition to establishing the corporate strategy for the sales and business development of molecular modeling software for academia, she also played an active role as an application scientist working on real-world discovery projects and finally in a senior role in strategy and business development for pharma and biotech companies. Following her time at CCG, Petrina moved to Certara as a Market Access Manager, where she learned first-hand the challenges of getting drugs to market. Petrina has been with Insilico Medicine since August 2020. She holds a PhD in Chemistry (specializing in computational chemistry) from Concordia University.

Tuesday, May 19, 2026 1:15 PM – 4:15 PM

W4 W4: Making Data AI-Ready: Building Reliable, Interoperable Foundations for Discovery

AI is only as good as the data behind it. In R&D, data is often fragmented, inconsistently annotated, and hard to harmonize. This workshop covers practical strategies, tools, and frameworks for improving data readiness, so models perform reliably, ethically, and within regulatory constraints. Through real-world examples and live demos, attendees will learn how to unlock the full value of public and proprietary datasets to accelerate discovery.

Presentation to be Announced

Wisdom Akpan, Scientific Systems Engineer, BioTeam

Unlocking Public Data at Scale
Public datasets promise scale. Delivering on that promise requires serious work. This session highlights common pitfalls, including inconsistent formats, missing metadata, and quality gaps, then introduces an approach using OpenClaude to transform raw public data into structured, standardized datasets ready for downstream use.

Data Representation & the Cost of Standardization
A deep dive into data modeling: the role of standard dictionaries, schemas, and the decisions that shape them. This talk examines the real trade-offs in harmonization: what you gain in interoperability and scalability, and what you lose along the way.

From Raw to Ready: Designing for Data Readiness at Scale
Data preparation isn't just a scripting problem; it's a systems design problem. This session steps back from individual tools and workflows to examine the architectural choices that determine how efficiently a team can move data from raw to ready. Attendees will see how decisions made at the pipeline and infrastructure level directly shape AI performance, reproducibility, and team velocity.

INSTRUCTOR BIOGRAPHIES:

Photo of Ari E. Berman, Chief Science Officer, Starfish Storage — **Ari E. Berman, Chief Science Officer, Starfish Storage**
Ari received his Ph.D. in Molecular Biology with a focus on Neuroscience in 2005 from the University of Texas at Austin (UT). His graduate work focused on studying the effects of genetics on addictive behaviors such as alcoholism. His postdoctoral fellowships at the University of California, San Francisco (UCSF) and the Buck Institute for Research on Aging focused on improving our understanding of neurodegenerative diseases of aging (specifically, Parkinsonâ€™s and Alzheimers Disease) by utilizing a combination of laboratory science and animal models, as well as bioinformatics and computational biology. Ari is also an expert in Scientific Computing specializing in high performance computing (HPC), high-performance networks, data centers, storage, cloud, general IT infrastructure, and bioinformatics and data analytics. He has been designing, building, and operating scientific computing environments for 27 years and strives to advocate for science and empower researchers to make discoveries from their complex datasets. His ultimate goal is to help create a dynamic enough abstraction of flexible infrastructure from research end-users to enable anyone to analyze and gain knowledge from very complex datasets.

Photo of Brian Osborne, PhD, Senior Principal Consultant, BioTeam, LLC — **Brian Osborne, PhD, Senior Principal Consultant, BioTeam, LLC**
At BioTeam, Brian brings over twenty five years of experience working in scientific and technical settings with expertise in bioinformatics and biology. Brian received his Ph.D. in Biology from M.I.T. focusing on transcriptional control elements in Saccharomyces. Prior to working at BioTeam, he worked in pharma and biotechnology in different technical and leadership roles, with a focus on scientific software application and platform development, either for internal research purposes or for commercial purposes. He is a long-time core contributor to the open-source community, including BioPython and BioPerl. He has provided tactical and strategic consulting on research and clinical data management to the NIH Intramural Program, NIH HEAL Initiative, NHLBI, NHGRI, NIH STRIDES program, and the NIH Clinical Center.

Photo of Fernanda Foertter, MSc, Executive Director, The University of Alabama High Performance Computing and Data Center — **Fernanda Foertter, MSc, Executive Director, The University of Alabama High Performance Computing and Data Center**
Fernanda Foertter is currently the Executive Director of The University of Alabama High Performance Computing and Data Center. She previously held roles as the Senior Scientific Consultant for BioTeam and GPU Developer Advocate for Bioinformatics at NVIDIA in the Healthcare group where she fostered an emerging community in AI and GPU computing. Before NVIDIA, Foertter held roles as an HPC Data Scientist in the Biomedical Sciences and Engineering group and was an HPC Programmer and Training Coordinator at the Oak Ridge National Lab's Leadership Computing Facility. She participated in the CORAL project that selected Summit as the next supercomputer to replace Titan, was co-PI of Kokkos Exascale Computing Project, served in OpenACC and OpenMP language standards, and is the â€œinventorâ€ of the GPU Hackathon training series. Other interests include the intersection of HPC and AI, facilitating data integration workflows, and productivity in scientific application development.

Photo of Wisdom Akpan, Scientific Systems Engineer, BioTeam — **Wisdom Akpan, Scientific Systems Engineer, BioTeam**

W5 W5: Quantum Computing in Life Sciences: From Fundamentals to Future Applications

Quantum computing is set to reshape how we approach complex problems in life sciences. In this workshop, Christopher Bishop will provide an accessible overview of quantum computing, explore its potential for accelerating computational biology and drug discovery, and highlight emerging applications across research and technology. Attendees will leave with a clear understanding of quantum principles and how they may transform the life sciences landscape.

1:15 PM Quantum Computing in Life Sciences: From Fundamentals to Future Applications

Christopher Bishop, Chief Reinvention Officer, Improvising Careers

This workshop introduces the essentials of quantum computing and its emerging role in life sciences. Participants will learn how quantum methods differ from classical approaches and explore early applications in drug discovery, molecular modeling, and complex data analysis. The session highlights realistic timelines, current capabilities, and future opportunities, offering a clear foundation for understanding quantumâ€™s potential impact on research and industry.

1:25 PM The Future of Healthcare in the Quantum Era

Gopal Karemore, PhD, Global Quantum Lead, Healthcare & Life Sciences, IBM Research

1:50 PM Accelerating Drug Discovery Today with QuADDâ€™s Quantum Computing Platform

Shahar Keinan, PhD, Co-Founder & CEO, POLARISqb

Quantum Computers are emerging as the next technology to accelerate drug design. We will discuss both QuADD (Quantum-Aided Drug Design), the next-generation SaaS platform that leverages quantum annealing to rapidly explore vast chemical spaces of 10^30 molecules and identify novel, synthesizable drug candidates with unprecedented speed and accuracy, as well as using Quantum ML to improve the prediction of molecular toxicity.

2:15 PM Running Real-World Computational Chemistry on Real Quantum Computers

Stig Elkjaer Rasmussen, Senior Quantum Algorithms Scientist, Kvantify

2:30 PM Unlocking Molecular Complexity: The Emerging Role of Quantum in Drug Discovery

Wes Roberts, Quantum Hardware and Physics Specialist, Alice and Bob

2:45 PM PANEL DISCUSSION:
When Quantum Meets Pharma: Inside the Race to Design Drugs

Christopher Bishop, Chief Reinvention Officer, Improvising Careers

Shahar Keinan, PhD, Co-Founder & CEO, POLARISqb

Nima Leclerc, Principal Investigator and Quantum Research Scientist, MITRE

Zoran Krunic, Former, Senior Manager, Data Science, R&D, Amgen, Inc.

Wes Roberts, Quantum Hardware and Physics Specialist, Alice and Bob

Panel Moderator

Christopher Bishop, Chief Reinvention Officer, Improvising Careers

Panelists

Nima Leclerc, Principal Investigator and Quantum Research Scientist, MITRE

Shahar Keinan, PhD, Co-Founder & CEO, POLARISqb

Wes Roberts, Quantum Hardware and Physics Specialist, Alice and Bob

Zoran Krunic, Former, Senior Manager, Data Science, R&D, Amgen, Inc.

Join informal roundtable discussions where speakers and attendees dive into the quantum landscape in drug discovery at Bio-IT. Open to everyone in the room, these interactive sessions encourage idea sharing, lively conversation, and fresh perspectives: making them a great way to connect, network, and spark thought leadership.

INSTRUCTOR BIOGRAPHIES:

Photo of Christopher Bishop, Chief Reinvention Officer, Improvising Careers — **Christopher Bishop, Chief Reinvention Officer, Improvising Careers**
I describe myself as a nonlinear multimodal careeristâ€”I have had 8 so farâ€”from touring rock musician in the 70s to 15 years at IBMâ€”and with several others along the way. My most recent career finds me engaged as a deep tech MC for various quantum events in Silicon Valley, Montreal, Washington, D.C, New York, London, and Singapore. I also host the Quantum Tech Pod, where I have interviewed over 55 senior execs at leading quantum companies. I am also passionate about helping people reinvent themselves and prepare for the future of workâ€”focusing on career guidance and life design skills. Based on how I successfully navigated my own atypical career path, I have developed a Future Career Toolkit designed to enable learners to be successful when pursuing their own nonlinear, multimodal career path. I conduct workshops titled "How to succeed at jobs that don't exist yet" using the toolkit to excite and empower students at universities as well as in Millennial/Gen Z workplaces. With over 14 years of experience as a Chief Reinvention Officer at Improvising Careers, I help learners of all ages and stages prepare for the 21st century's global borderless workplace.

Photo of Gopal Karemore, PhD, Global Quantum Lead, Healthcare & Life Sciences, IBM Research — **Gopal Karemore, PhD, Global Quantum Lead, Healthcare & Life Sciences, IBM Research**
Gopal Karemore is the Quantum Lead for Healthcare and Life Sciences at IBM Research, based at the T. J. Watson Research Centre in New York. He leads efforts to drive the adoption of quantum computing in life sciences and healthcare, working with IBM teams and external partners to deliver high-impact solutions. He holds a Ph.D. in Computer Science from the University of Copenhagen in 2011 and has contributed to shaping innovation and business development across pharmaceutical R&D. Prior to joining IBM, he held research and leadership roles at Novo Nordisk, Spanish National Centre for Cardiovascular Research, Danish Stem Cell Centre, Novo Foundation Centre for Protein Research, Fraunhofer Institute, and Penn Medicine.

Photo of Nima Leclerc, Principal Investigator and Quantum Research Scientist, MITRE — **Nima Leclerc, Principal Investigator and Quantum Research Scientist, MITRE**
Quantum Research Scientist and Head of the Adaptive Quantum Sensing Program at MITRE, where I lead development of quantum sensing technologies in partnership with NVIDIA and advise senior government officials on quantum technology strategy. My research develops AI-driven frameworks that predict and optimize quantum sensor performance, reducing development cycles from years to months. At MITRE, I developed Walsh Imagingâ€”a novel quantum sensing technique that enables nanoscale electromagnetic imaging with applications in semiconductor security and neuroimaging. Prior to being recruited by MITRE from my doctoral research at the University of Pennsylvania, I worked at PsiQuantum, Kepler Computing, Lawrence Berkeley National Lab, and Caltech. I founded the Penn Quantum Engineering Graduate Association and have briefed Congressional committees on post-quantum cryptography standards at Springer Nature's Science on the Hill, informing federal quantum R&D strategy. I've delivered invited talks at NVIDIA GTC, The Economist, and IEEE Quantum Week. I hold a B.S. in Materials Science from Cornell University and did my M.S./Ph.D. work in Electrical Engineering at the University of Pennsylvania, specializing in silicon spin qubits.

Photo of Shahar Keinan, PhD, Co-Founder & CEO, POLARISqb — **Shahar Keinan, PhD, Co-Founder & CEO, POLARISqb**
An accomplished leader with a keen understanding of the dynamics that impact developing and bringing products to market. 15+ years of computational chemistry experience, including the previous 10 years in senior scientific and operational leadership positions. Experienced at working at multiple stages of R&D process with experience leading multiple, concurrent projects at varying stages of development. Excels at integrating scientific goals and capabilities with business objectives to craft a cohesive go-to-market strategy. Outstanding communication skills, leadership ability, and business acumen

Photo of Wes Roberts, Quantum Hardware and Physics Specialist, Alice and Bob — **Wes Roberts, Quantum Hardware and Physics Specialist, Alice and Bob**
I'm a theoretical physicist and Quantum Hardware Specialist at Alice & Bob, where I work to make fault tolerant quantum computing a reality. Prior to this I was a postdoctoral researcher at US Army Research Lab, based at MIT's Institute for Soldier Nanotechnology. I currently study nonlinear optical responses, which are both a way to probe the unique quantum geometry of a system and are of interest for their potential technological applications, particularly in quantum sensing. My research relies on tools from quantum field theory, condensed matter physics, statistical mechanics, electrodynamics, and diverse mathematical subjects such as linear algebra, differential equations, complex analysis, differential geometry, group theory, and statistics. I'm motivated by a love of these subjects, insatiable curiosity, an appetite for constant learning, and the desire to do impactful work. I completed my PhD in condensed matter theory with the Fiete Group at Northeastern University. Here I studied quantum magnetism, with a particular focus on theoretical questions pertaining to the development of quantum technologies, such as spintronics, magnonics, and quantum information technology. Before this I completed a master's degree in Philosophy of Physics at Oxford University, with a particular focus on foundational problems in quantum theory and statistical mechanics. I have general interests in the creative application of mathematical modeling to domains as various as quantum physics, finance, and ethics.

Photo of Zoran Krunic, Former, Senior Manager, Data Science, R&D, Amgen, Inc. — **Zoran Krunic, Former, Senior Manager, Data Science, R&D, Amgen, Inc.**
Since joining Amgen's R&D in 2018, I've applied Machine Learning to boost patient outcomes and optimize clinical trial enrollment, leveraging Electronic Health Records. Leading in Quantum Machine Learning, I authored "Quantum Kernels for Real-World Predictions Based on Electronic Health Records," (https://ieeexplore.ieee.org/document/9779984 ) in collaboration with IBM, integrating ML with quantum computing. Most recently, I co-authored the paper â€œ"Robust Quantum Reservoir Computing for Molecular Property Prediction" (available at https://lnkd.in/g6WaVjGD) in collaboration with QuEra. I have broadened my research to deeply study quantum kernels, analyzing their effects on the variability and reproducibility of small clinical datasets. I've launched several projects in quantum computing, expanding into various aspects of Quantum Machine Learning and Quantum Computing disciplines. Before Amgen, I developed Machine Learning algorithms at Optum to predict failures within complex enterprise architectures. My background covers data engineering and systems development, contributing significantly to large-scale projects (Capital Group, ARCO Petroleum). Presently I lead efforts in Quantum Computing and generative AI technologies. Within Quantum Computing, the areas include Quantum Machine Learning and Quantum Monte Carlo methods. Within AI, my focus is on OpenAI's GPT and Anthropic's Claude models. My work spans prompt engineering, code generation, advanced document analysis, process management, and I'm committed to ethical AI practices and data privacy. Recently, I've expanded my focus to include reproducibility using generative AI. I frequently present at industry conferences and serve on panels discussing the Quantum Computing, generative AI and their integration within the Health Sciences sector. I firmly believe in the deep and comprehensive synergy of these new technologies. I have successfully initiated and managed multiple connections and projects with various quantum computing and AI vendors. My engagements have led to substantial collaborations that enrich the research and development landscape in healthcare technology. My deep understanding of AI and quantum computing enables me to provide insightful guidance to pharmaceutical companies and related enterprises, helping to identify and implement the most effective technological solutions.

W6 W6: AI Upskilling for Computational Biology Teams

AI is rapidly transforming how computational biology teams design experiments, analyze data, and generate insightsâ€”but most scientists havenâ€™t had the opportunity to build hands-on proficiency with these new tools. This interactive workshop bridges that gap, providing practical guidance on how to apply AI and agentic coding frameworks in real-world research settings. Participants will learn how to build, test, and deploy simple AI agents, connect biological data to large language models, and explore no-code or low-code platforms that accelerate productivity. Designed for computational biologists, bioinformaticians, and data scientists, this session focuses on applied learning to help teams confidently integrate AI into their daily workflows.

1:15 PM AI Upskilling for Computational Biology Teams

Ryan Bellmore, Owner/Founder, Right Bionic